42 Exciting Python Project Ideas & Topics for Beginners in 2024 With Source Code [Latest]

Updated on 05 May, 2024

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Python Project Ideas & Topics

Summary:

In this article, you will learn the 42 Exciting Python Project Ideas & Topics in 2024. Take a glimpse below.

  1. Mad Libs Generator
  2. Number Guessing
  3. Text-based Adventure Game
  4. Dice Rolling Simulator
  5. Hangman
  6. Contact Book
  7. Binary search algorithm
  8. Desktop Notifier App
  9. Python Story Generator
  10.  Python Website Blocker
  11. Spin a Yarn
  12. What’s the word?… and more…

Read the full article to know more about all the 42 project Ideas & Topics in detail.

Python Project Ideas for Final Year Students

Python is one of the most popular programming languages currently. It looks like this trend is about to continue in 2022 and beyond. So, if you are a Python beginner, the best thing you can do is work on some real-time Python project ideas. Also, you can check out some of our data science free courses that may help you understand python better.

We, here at upGrad, believe in a practical approach as theoretical knowledge alone won’t be of help in a real-time work environment. In this article, we will be exploring some interesting Python project ideas which beginners can work on to put their Python knowledge to the test. In this article, you will find 42 top python project ideas for beginners to get hands-on experience with Python. 

Moreover, project-based learning helps improve student knowledge. That’s why all of the upGrad courses cover case studies and assignments based on real-life problems. This technique is ideal for, but not limited to, beginners in programming skills. Also, check out our Python Programming Bootcamp which is for beginners in coding who want to explore a career in Data Science. 

After completing this course, you can choose from job roles like python intern, Jr python developer, and much more.

But first, let’s address the more pertinent question that must be lurking in your mind: why build Python projects?

When it comes to careers in software development, it is a must for aspiring developers to work on their own projects. Developing real-world projects is the best way to hone your skills and materialize your theoretical knowledge into practical experience. Learn Python Programming with SQL and explore a career in Data Science. If you work on live projects, it will help:

To boost your confidence

As you work with real tools and technologies, you will become more confident about your strengths while also identifying your weak points. 

To experiment

You will need to acquaint yourself with new tools and technologies while working on a python project. The more you learn about cutting-edge development tools, environments, and libraries, the broader will be your scope for experimentation with your projects. The more you experiment with different python project ideas, the more knowledge you gain.

To know the nitty-gritty of SDLC

When you develop a project from scratch, you will gain a deeper understanding of how the software development life cycle functions. With time you will learn how to plan before writing the code, execute the code, manage the testing process, fix bugs, deploy the code, and also update your software product from time to time.

To master the concepts of programming

One of the biggest advantages of building real-world projects is that with continuous practice, you will master the concepts and patterns of programming in different languages. 

  • Python -The most sought-after industry application

As per Python project reports, enterprises have significantly focused on analytics and data science hiring in the past few years. Candidates excelling in Python programming skills attained more preference than ever before. As one of the leading industry technologies, beginner Python projects offered excellent opportunities and benefits to young minds. 

  • Earning Potential

As per recent statistics, Python turned out to be the highest-paying computer language, with students doing python small projects. Due to this reason, the average remuneration of a candidate excelling in Python is comparatively skyrocketing, simply by having python mini project topics. Many information technology experts showed interest in gaining and honing their skills in Python to attain a career boost with doing projects in python or doing best python projects

  • Robust Community Support

Python is an advanced programming language that was introduced several years back. It already built a community that can significantly aid programmers with several varied levels of experience. Python small project is an ideal platform for both specialists and rookies in the field. The community of Python helped it expand and develop much more rapidly compared to the other languages.

The programming language of Python comes with various instructions and guides. They also include interesting explanatory videos, which makes them easy to understand for beginners. The documentation is quite easy to understand and assists developers in learning languages efficiently and rapidly, especially those doing their final year project on various final year project topics.

  • Rapid and Major Development

Another strong advantage of Python is that users are able to generate innovative applications with the help of a particular programming language. Due to its versatile nature, the language allows an operator to try out and experiment with new aspects. One can prefer Python Projects if they are looking for liberty and flexibility when it comes to executing their skills. 

  • Easy learning ad using the interface

If you are a newbie in the world of Python, the good news is it offers a simple interface for learners. One can pick up skills quite rapidly and also experiment with the significantly progressive language program. The language is quite easy to adapt due to its systematic and rational process of operation. The fundamentals of Python can easily be executed compared to that of different programming languages, especially for simple python projects or python mini projects for college students

Looking to challenge yourself or expand your portfolio? Check out our curated list of computer science project ideas to inspire your next groundbreaking project.

  • Offers High Flexibility to Learners

Basic python project is not just easy to explore and learn, but it also provides great flexibility. A large percentage of the third-party libraries of Python are still operated and allow the use of the application in machine learning. It also supports areas like biology and web processing.

The data-centric libraries such as matplotlib, Numpy, and Pandas make it quite capable when it comes to visualizing, processing, or manipulating data in Python Projects. Due to its highly accommodating nature, it is often known as the leading entity among computer languages.

So, here are a few Python Projects for beginners can work on:

Python Project Ideas For Beginners 

This list of python project ideas for students is suited for beginners, and those just starting out with Python or Data Science in general. These python project ideas will get you going with all the practicalities you need to succeed in your career as a Python developer.

Our learners also read: Excel online course free!

Further, if you’re looking for Python project ideas for a final year, this list should get you going. So, without further ado, let’s jump straight into some Python project ideas that will strengthen your base and allow you to climb up the ladder. 

Here are some python topics list that will help beginners build a strong foundation in Python.

Alternatively, you can also enroll yourself in Free Python Certification Course.

1. Mad Libs Generator

One of the best ideas to start experimenting with your hands-on python projects for students is working on Mad Libs Generator. This is the perfect project for beginners who are just starting out with software development. Primarily focused on strings, variables, and concatenation, this project will teach you how to manipulate user-inputted data. The program design is such that it will ask users to enter a series of inputs that will be considered a Mad Lib. Mab lib is one of the python projects for beginners.

The input could be anything, an adjective, a noun, a pronoun, etc. Once all the inputs are entered, the application will take the data and arrange the inputs into a story template form. Sound fun, right?

Our learners also read – python online course for free!

Source code – Github

2. Number Guessing

This is one of the simple python projects yet an exciting one. You can even call it a mini-game. This project is particularly useful for beginners. Make a program in which the computer randomly chooses a number between 1 to 10, 1 to 100, or any range. Then give users a hint to guess the number. Every time the user guesses wrong, he gets another clue, and his score gets reduced. The clue can be multiples, divisible, greater or smaller, or a combination of all.

You will also need functions to compare the inputted number with the guessed number, to compute the difference between the two, and check whether an actual number was inputted or not in this python project. The main aim of this coding project idea from the Python projects list is to introduce beginners to coding basics. 

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Source code – Github

3. Text-based Adventure Game

This is a basic version of the Adventure game. It is completely text-based. In this version of the game, users can move about through different rooms within a single setting, and based on the user input, it will provide descriptions for each room. This is one of the more interesting python projects for beginners.

Movement direction is crucial here – you must create walls and set the directions in which the users can move through the rooms, set movement restrictions, and also include a tracker that can track how far a user has walked or moved in the game. Mentioning Python projects can help your resume look much more interesting than others.

Source code – Github

Check out all trending Python tutorial concepts in 2024

4. Dice Rolling Simulator

As the name of the program suggests, we will be imitating rolling dice. This is one of the interesting python projects and will generate a random number for each dices the program runs, and the users can use the dice repeatedly for as long as he wants. When the user rolls the dice, the program will generate a random number between 1 and 6 (as on a standard dice).

The number will then be displayed to the user. It will also ask users if they would like to roll the dice again. The program should also include a function that can randomly grab a number between 1 to 6 and print it. This beginner-level python project allows you to explore programming fundamentals and different coding concepts.

Source code – Github

5. Hangman

This is more of a “guess the word” game. The core concepts you have to use while developing this project are variables, random, integer, strings, char, input and output, and boolean. In the game, users have to enter letter guesses, and each user will have a limited number of guesses (a counter variable is needed for limiting the guesses). The Hangman is among the most highly recommended projects to master python for beginners. 

You can create a pre-organized list of words that users can grab words from. Also, you must include specific functions to check whether or not a user has entered a single letter or if the input letter is in the hidden word, so if the user has actually inputted a single letter, and to print the correct outcomes (letters).

Source code – Github

Must read: Data structures and algorithms free course!

6. Contact Book

This is one of the excellent python projects for beginners. Everyone uses a contact book to save contact details, including name, address, phone number, and even email address. The main objective of this project is to generate a contact book using python where users can add a new contact, edit, or delete existing contacts and view the details of all their contacts. This is one of the coolest project ideas in python for beginners to help strengthen their command of the programming language.

This is a command-line project where you will design a contact book application that users can use to save and find contact details. The application should also allow users to update contact information, delete contacts, and list saved contacts. The SQLite database is the ideal platform for saving contacts. Handling a project with Python for beginners can be helpful to build your career with a good start.

Source code – Github

7. Email Slicer

This is one of the convenient python projects that has a lot of use in the future. To create an Email slicer with python, users have to generate a program to retrieve the username and domain of the email.  You can even customize the application and send a message to the host with this information. Although it is a simple coding project idea, it is instrumental in enhancing your coding skills.

Source code – Github

8. Binary search algorithm

Have you ever heard the proverb, “finding a needle in a haystack.” This program is designed to do just that- by using a binary search algorithm. You can create a list of random numbers between 0 to 100, with every succeeding number having a difference of 2 between them.

When the user inputs a random number, the program will check if that number is included in the list. It will do so by creating two halves of the list. If the program finds the number in the first half of the list, it will eliminate the other half and vice versa. The search will continue until the program finds the number input of the user or until the subarray size becomes 0 (this means that the number is not in the list). This python project idea will help you create and implement an algorithm that searches for an element in a list. 

Source code – Github

9. Desktop Notifier App

Have you ever wondered how notifications work? This small python project idea will throw some light on this. The desktop notifier apps run on your system and send you a piece of information after a fixed interval of time. We suggest you use libraries such as notify2, requests, etc. to build such a program.

Source code – Github

10. Python Story Generator

Did you think the most complex way of using a random module in python is random sampling? This idea cannot be further from the truth. It is also possible to create random stories and even beyond using the random module. 

Here, the aim is to create a random story each time the user runs the program. The story will be the same always but with little variation in the input. This is a fun but exciting python project which will work wonders with beginners to gain confidence in python.

In a nutshell, the program will ask users for inputs such as the name of a place, action, etc., and then build a story around the data.  

Source code – Github

11. YouTube video downloader

One of the best ideas to start experimenting with your hands-on python projects for students is working on a YouTube video downloader. This is the best example of introducing python to beginners in a fun way. More than a billion people watch YouTube every month. Sometimes there are videos we like to download permanently. YouTube doesn’t give you that option, but you can create an app with a simple UI and the ability to download YouTube videos in different formats and video quality. This project looks tough, but it is straightforward when you start working on it.

Source code – Github

12. Python Website Blocker

When we surf the internet, many unwanted websites keep showing up. In this real-life python project, you build a program that blocks unwanted websites from showing up when you are working. Building such programs will boost the confidence of beginners in Python as they master its fundamentals. This program is beneficial for students who want to study without any social media distractions and also for those who do not want to be bugged by unwanted websites while working.  Having this kind of python project on the resume can help your resume look much more interesting than others.

Source code – Github

13. Spin a Yarn

Things get more interesting here since strings are infinitely more complex to play with at the beginning.

The program first prompts the user to enter a series of inputs. These can be an adjective, a preposition, a proper noun, etc. Once all the inputs are in place, they are placed in a premade story template using concatenation. In the end, the full story is printed out to read some misintended madness!

Source code – Github

14. What’s the word?

This name focuses on the user having to guess the randomly generated word. You can create a list from which the word would have to be guessed and also set a cap on the number of guesses allowed.

After this, you can create the rules yourself! When the user inputs the word, you can indicate whether the alphabet written appears in this particular position or not. You will need a function to check if the user is inputting alphabets or numbers and to display error messages appropriately.

Source code – Github

15. Rock, Paper, Scissors

If you are tired of having no playmate, then a 5-minute stint of rock, paper, scissors with the computer and designed by you, yourself will improve your mood.

We again use the random function here. You make a move first and then the program makes one. To indicate the move, you can either use a single alphabet or input an entire string. A function will have to be set up to check the validity of the move.

Using another function, the winner of that round is decided. You can then either give an option of playing again or decide a pre-determined number of moves in advance. A scorekeeping function will also have to be created which will return the winner at the end.

Source code – Github

16. Leap it!

In this python project, you input a year and check whether it is a leap year or not. For this, you’ll have to create a function that recognizes the pattern of leap years and can try fitting the inputted year into the pattern. In the end, you can print the result using a boolean expression.

This project requires a good command of Python operators and Python if-else statements. So, it is perfect for those who are academically strong in python and looking for hands-on experience in developing their Python project.

Source code – Github

17. Find out, Fibonacci!

You input a number and the function created checks whether the number belongs to the Fibonacci sequence or not. The underlying workings are similar to the above ‘Leap it!’ program.

One common theme in all the above projects is that they will help you to get your basics right. You will be the developer and the bug fixer. Not to mention, you’ll be closely working with creating and implementing a variety of functions along with working with variables, strings, integers, operators, etc. Just like 2 + 2 is the building block of your mathematics knowledge, so are these concepts, and learning about them in a fun way through building projects will help to understand and retain them more.

These are some of the most straightforward Python project ideas for you to work on. Once you finish these, let’s move to the next level.

Source code – Github

Read: Machine Learning Project Ideas For Beginners

Python Project Ideas: Intermediate Level

18. Calculator

Although there isn’t much use for a calculator, however, building your graphical UI calculator will make you familiar with a library like Tkinter in which you can create buttons to perform different operations and display results on a screen.

Source code – Github

19. Countdown Clock and Timer

It is another utility app in which the user can set a timer, and the app notifies you when the time is up.

This nifty app helps in furthering knowledge of python coding. It is an intermediary-level project in which the codes will take gather the input corresponding to the length of the countdown within seconds. After receiving the input, the countdown will be initiated and will appear on the screen in “minutes: seconds” format.

Source code – Github

20. Random Password Generator

This is one of the most popular coding project ideas in python. Online security is quintessential in this modern world where everything happens online. Passwords are the armors that protect our accounts from getting hacked or compromised. Having said that, creating a strong password and remembering it is a tedious task. You can build a program that intakes some words from the user and then generates a random password using those words. The user can remember the password with the help of the words he gave as input.

Source code – Github

21. Random Wikipedia Article

This is a complicated yet straightforward program. The program searches Wikipedia and fetches a random article. Then it asks the user if he wants to read that article or not. If the answer is yes, the material is shown; otherwise, another random report is presented. This is an apt project for those developers at the intermediary level looking to further their careers by developing creative and complex Python programs. 

Source code – Github

22. Reddit Bot

This is one of the excellent python project ideas for beginners. Reddit is a handy platform, and many people want to be online as much as they can. You can program a bot that monitors subreddits and reports whenever they find something useful. It will save Redditors a lot of time and provide helpful information with it.

Source code – Github

23. Python Command-Line Application

Python is known for building outstanding command-line applications. You can create your program, which can help you send emails to other people. The program will ask for your credentials and the content of the email, then send the data using your created command line.

Source code – Github

24. Alarm Clock

This is one of the interesting python project ideas. People all across the globe use alarm clock applications. It is quite a simple Command Line Interface (CLI) Python application for an intermediate-level developer. However, this project isn’t your run-of-the-mill alarm clock. In this application, you can input YouTube links in a text file and design the application to read the file. If you set a particular time in the alarm clock, it will pick a random YouTube link from the text file and play the YouTube video.

Source code – Github

25. Tic-Tac-Toe

We all have fond memories of playing Tic-Tac-Toe with our friends in school, don’t we? It is one of the most fun games you can play anywhere – all you need is a pen and paper! Usually, two players can play Tic-Tac-Toe at a time. The players crea

Source code – Githubte a 3×3 square grid. This is one of the coolest python project ideas. 

While the first player puts “X” in any one of the squares, and the second player will put an “O” in any square. This process will continue until all the squares are filled with each player putting X and O alternatively. The player who succeeds in creating a horizontal, vertical, or diagonal with three consecutive X or O on the grid wins.

You can use the Pygame library for building this project. Pygame is loaded with all the modules you need for computer graphics and sound.

Source code – Github

26. Steganography

Steganography is the art of hiding a secret message in another form of media, for example, hiding a coded message in an image or video. You can create a program that protects messages inside pictures for you. This coding project in Python can encode and decode images at a quick pace. It is apt for entry-level aspirants looking to enhance their coding skills. 

Source code – Github

27. Currency Converter

This is a simple GUI application that you can develop using Python. As you can guess by the name, you will build a currency converter that can convert currencies from one unit to another, for example, converting the Indian rupee into a pound or euro.

The design of this application will be straightforward – the main focus should be the primary function, that is, converting currency units from one to another. You can use Tkinter, the standard Python interface to the Tk GUI toolkit shipped along with Python.

Source code – Github

28. Post-it Notes

Post-it notes are an excellent way to note down trivial chores so that you don’t forget to do them. In this project, we’ll make a virtual version of the physical, adhesive post-it notes. The main goal of building this application is to allow users to carry their post-it notes wherever they go (since it is on a digital platform).

The application should have an option for account creation, different layouts for post-it notes, and a categorization feature to allow users to segment their notes. You can consider using Django for this project since it has an in-built user authentication feature.

Source code – Github

29. Site Connectivity Checker

The job of a site connectivity checker is to visit a URL and display the status of that URL, that is, whether or not it is a live URL. Usually, site connectivity checkers visit URLs at regular intervals and return the results each time. This project will work on the same lines – it will check the live status of URLs. Site connectivity checker is one of the interesting python projects for beginners.

You must design the code for this application from scratch. As for your connections, you can either opt for TCP or ICMP. You can use click, docopt, or argparse frameworks for adding commands that will enable users to add and delete URLs from the list of URLs they want to check. 

Source code – Github

30. Directory Tree Generator

A Directory Tree Generator lets you visualize the relationship between files and directories, thereby making it easier to understand the positioning of files and directories. For this project, you can use os library to list the files and directories within a specific directory. Again, docopt or argparse frameworks are excellent tools for the project. 

Read: Python Developer Salary in India

These are some intermediate Python project ideas on which you can work. If you still like to test your knowledge and take on some tough projects

Source code – Github

Python Project Ideas: Advanced Level

31. Speed Typing Test

Let’s start advanced python project ideas for beginners. Do you remember the old typing test game which was used in Windows XP and before? You can create a similar program that tests your typing speed. First, you need to create a UI using a library like Tkinter. Then create a fun typing test that displays the user speed, accuracy, and words per minute in the end. You can also find source code for the program online.

Source code – Github

32. Content Aggregator

The internet is filled with websites, articles, and information. When we want to find something, it is tough to go through each of them. For this use, you can create a content aggregator that automatically searches popular websites and looks for relevant content and then complies with all the content and lets the user choose which content they want. It is very much like Google but unbiased. And this is the perfect idea for your next python project!

Source code – Github

33. Bulk File Rename/ Image Resize Application

This is an advanced project which needs you to be well-versed in Machine Learning. We will begin by teaching the program on how to pre-process data, then perform a few resize and rename images tasks. As the program starts learning, it can handle bulk functions at once.

Source code – Github

34. Python File Explorer

This is a significant project as it will test your knowledge of the various concepts of Python. You need to build an app that anyone uses to explore the files in their system. You can also add features like searching and copy-paste. Tkinter is a commendable choice for this project as it makes the development of GUI applications fast and easy.

To create the Python File Explorer using Tkinter, you have to import the file dialog module from Tkinter. This module is designed for opening files and directories and saving them.

Source code – Github

35. Plagiarism Checker

Content writing is one of the most prolific online businesses. The market lacks a free tool that can be used to check for plagiarism in documents. You can use a natural language processing library along with the Google search API to create a program that searches the first few pages of Google and checks for plagiarism.

Source code – Github

36. Web Crawler

A web crawler is an automated program script that surfs the internet and stores the content of a particular webpage. A web crawler is one of the most useful python projects to find up-to-date information. You will need to use a multi-thread concept for such a program. You can use Python’s request module to make the crawler bot, or you can use Scrapy. It is Python’s open-source web crawling framework explicitly designed for web scraping and extracting data by using APIs.

Source code – Github

37. Music Player

Everyone likes listening to music; you can also create your music player app. Other than playing music, your program can explore your file directories and search for music. This is one of the creative python projects you might face is creating an interactive interface that can be used by regular users.

The app will have a neat interface that will allow users to browse through tracks, increase/decrease volume, and display the name of the song, artist, or album. This project will mainly involve the basics of Python programming, database management, algorithm construction, and data processing

Source code – Github

38. Price Comparison Extension

This can be an interesting and useful python project idea. Just like Trivago, you can create a program that searches a few notable websites for the price of a product and then show you the best deal. It is a convenient program, as many businesses started on this small program. You can use this extension for groceries, stationery, etc.

Source code – Github

39. Expense Tracker

As you can guess by the name, an expense tracker is a software application that lets you keep track of your expenses, and even analyze the expenses. In this python project, you will build a simple expense tracker that can keep track of the user’s expenses.

Expense tracker is one of the trending python projects which should also be able to perform statistical analysis to give accurate insights to users on their expenses so that they can plan their expenses better. You can use PySimpleGUI to create the interface for this application, and even Python libraries like Pandas and Matplotlib can be handy tools for the project.

Source code – Github

40. Regex Query Tool

Regular search tools often fail to produce the desired results for specific queries. In such events, what you need is a Regex Query Tool. In simple words, a regex is a set of strings, which means that when you enter a query in this tool, it will check the validity of your query.

If the regex can match patterns in the text query entered by the user, it notifies the user by highlighting all the matching patterns. A Regex Query Tool is one of the trending python projects which allows users to quickly check the validity of their regex strings on the Web, thereby making the search process much easier. Python’s re library is the perfect tool for running the query strings on the user-inputted text.

Source code – Github

41. Instagram Photo Downloader

This would be an app that automatically downloads all the Instagram images of your friends. As Instagram is growing everyday, this is one of the useful python projects and it is quite similar to the above command line app as this app will use your credentials to open your account and then look for your friend’s ID and download their photos. This app would be handy when people want to delete pages and save just the images.

Source code – Github

42. Quiz Application

This is one of the interesting python project ideas to create. This is a standard quiz application that presents a set of carefully curated questions to the users (a questionnaire), allows them to answer the same, and displays the correct answer if they are wrong. Each test will display the final score of the user. The application will have an account creation option, wherein some users can be appointed as Admins.

These Admins can create tests for other users. In this way, the tests and quizzes continue to be updated. This application requires a database to store all the questions, answers, and scores of the users. You can also include additional features like timers for tests.

Source code – Github

Also read: Python Interview Questions & Answers

Bonus Python Project Ideas You Shouldn’t Miss Out [With Python Libraries]

#1 Sentiment Analysis

One of the most popular mini project in python now under development in multiple disciplines is sentiment analysis. It leverages computational linguistics, text analysis, biometrics, and natural language processing to identify, extract, and research affective states systematically. From review and poll systems to eCommerce, this project idea is applicable on a range of contexts. 

Most Implemented Libraries

  • NLTK

The NLTK in Python aims to provide a wholesome solution for natural language analyzing issues. This library aids with all aspects, from splitting paragraphs, word statements, and highlighting parts to identifying speech. This lets the machine understand what exactly the text is regarding. 

  • Scikit-learn

This is one of the most uncommon machine learning libraries that helps in featuring several clustering algorithms, classifications, and regression. It often involves random forests, DBSCAN, k-means, and vector machines. This library is also created for inter-operating with the final year project of Python Projects libraries such as Pandas and Numpy.

Libraries Used For Sentiment Analysis
NLTK

The goal of the Python NLTK module is to offer a thorough resolution to a Natural Language Processing issue. 

NLTK assists in separating sentences from paragraphs, breaking down words, identifying the words’ parts of speech, emphasizing the main ideas, and finally enabling the computer to comprehend the text as a whole. 

Scikit-Learn

Random forests, support vector machines, DBSCAN, gradient boosting, and k-means are just a few of the classification, regression, and clustering algorithms included in Scikit-learn, a machine learning package. 

Also, it is made to work with Pandas and NumPy – two popular Python libraries.

#2 Customer Segmentation

Customer segmentation is the practice of grouping customers based on shared traits or characteristics so that businesses may effectively and correctly cater to each group. 

Most Implemented Libraries

  • Numpy

Numpy is one of the unique libraries that provide support for matrices, multi-facet arrays, and large arrays. It comes with a collection of mathematical functionalities for operating the arrays. 

  • Matplotlib

Matplotib is a prevalent Python library that is utilized for plotting graphs and charts from derived information and data.

Libraries Used For Customer Segmentation
NumPy

NumPy, a popular Python package, offers support for huge, multidimensional arrays and matrices. 

It also helps you with a sizable number of sophisticated mathematical operations that may be performed on these arrays. 

Pandas

Pandas, one of the cutting-edge Python libraries, is widely used for analyzing and manipulating data. 

For modifying numerical tables and time series, it provides data structures and operations. 

Scikit-Learn

Scikit-Learn, a popular ML package, comes with clustering, regression, and classification algorithms like support vector machines, gradient boosting, random forests, k-means, and DBSCAN. 

It is made to work together with Python libraries like NumPy and Pandas.

Matplotlib A Python module called Matplotlib is used to create graphs and charts from the obtained data. 

#3 Object Detection

We can recognize and find items in an image or video using the computer vision technique known as object detection, which is also a well-liked Python project idea. This method can be used to count objects in a scene, locate and track them precisely, and accurately identify them, among other things. 

Most Implemented Libraries

  • TensorFlow

This is a prevalent Python library that is often utilized for deep learning in Python Projects. The Tensor flow usually emphasizes the interface and training of neural networks and deep learning. One can perform multiple tasks at the same time with the help of this library. 

  • OpenCV

The Open CV is a unique yet popular library that has an open-source interface. It is generally used for computer vision and machine learning. It offers a common platform for software related to computer vision and accelerates machine perception. It usually speeds up the perceptions of commercial products. 

  • Keras

Keras is also a popular library with an open-source interface that is implemented in imitated neural networks. It supports various deep learning and machine learning libraries. However, with the arrival of the 2.4 version, it only supports the TensorFlow interface. 

Libraries Used For Object Detection
TensorFlow

TensorFlow is a well-known Python deep learning library, is applicable on a range of tasks. 

However, it primarily focuses on deep learning and neural network inference and training. 

OpenCV

OpenCV (Open Source Computer Vision Library) is a free Python library for computer vision and machine learning. 

Machine perception in commercial products is accelerated and a common framework for computer vision applications is provided. 

Keras

An open-source toolkit called Keras offers a Python interface for convolutional neural networks. 

Before version 2.4, Keras supported a variety of machine learning and deep learning libraries, but now it solely serves as an interface for the TensorFlow library. 

#4 Twitter Bot

Through the Twitter API, a Twitter bot can operate and administer a Twitter account. The bot is capable of carrying out any task on its own, including tweeting, retweeting, liking, following, and unfollowing, among others. 

Most Implemented Library

  • Tweepy

Tweepy is one of the popular Python libraries that help you access the Twitter API. The library allows Python to interact with the platform of Twitter and implement the API efficiently. 

Libraries Used For Twitter Bot
Tweepy

The Python package Tweepy provides access to the Twitter API. 

This module makes it possible for Python to interact with and utilise the Twitter platform’s API. 

Tkinter

The most popular technique for creating a GUI (Graphical User Interface) is Tkinter. 

It is a typical interface for the Python-supplied Tk GUI toolkit. The quickest and simplest method for making GUI apps is Tkinter. 

#5 Currency Converter

Currency converter is one of the dynamic schemes among Python projects that include creating applications and software with a simplified interface. These applications help in transforming a single currency into a different type of currency for determining the corresponding value. 

Libraries implemented

  • Request

The request model lets the users fetch HTTP requests with the use of Python. The request of HTTP then sends back a reply object with all of the data responses, such as status, content, and encoding. 

  • Forex

Forex is free of charge foreign exchange percentage and conversion of currency in Python library. It comes with multiple features such as Bitcoin pricing, a list of currency percentages, Bitcoin conversion, and more.  

  • Tkinter

Tkinter is a prevalently used strategy when it comes to generating graphical user interfaces. It is one of the standard interfaces when it comes to a toolkit of TK GUI and is usually provided with Python projects. It is one of the quickest and most convenient applications of GUI.

#6 Web-Crawler

Web crawler is often known as the short form of crawler in today’s tech industry. It is basically a web bot that methodically searches the WWW to accomplish web indexing. Internet search engines and other web pages utilize web crawling or relevant ways to upgrade their content. Crawler is one of the unique schemes among Python begineer projects that can copy pages in order to conduct processing with the help of search engines. This lets users browse more content freely as the downloaded pages are indexed.

Most Implemented Libraries

  • Scrapy

Scrapy is a framework implemented by Python projects. This framework can be implemented for extracting data by utilizing API or a generic purpose crawler.

  • Beautiful Soup

This is another Python package due to parsing the XML and HTML documents. It generates a parse tree for parsing pages that can take out data from the HTML that is effective for internet scraping.  

#7 Calculator

The calculator is one of the apt Python Projects for beginners to get their hands dirty and doing python simple projects.

Most Implemented Library

  • Math

Python Projects come with an in-built model that you can utilize for mathematical activities. The mathematics models have a set of constants and methodologies. 

#8 Currency Converter

The currency converter is another one of the Python Project ideas that involves developing simple software or an application that converts one currency into another to check its corresponding value.

Most Implemented Libraries

  • Requests

It offers a simple interface that makes functioning with HTTP quite simple. It simplifies the procedure of receiving and sending data from sites by offering an equal interface for both POST and GET strategies. 

  • Forex

As explained above, Forex is a powerful tool when it comes to the library of Python projects. It mostly deals with the conversion of BitCoins. 

#9 Rock Paper Scissors

The Rock Paper Scissors is a traditional game and simultaneously one of the entertaining Python Projects for beginners. It is an excellent medium to hone your practical skills in Python.

Most Implemented Library

  • Pygame

Pygame is usually a cross-interfaced set among the Python modules that are specially created for coding games. 

#10 Tic Tac Toe

This is one of the last ideas of Python Projects that have left a massive impact on the processing of computer language. One can use it by executing mathematical functionalities offered by Python. His project is enriched with Python basics and fundamentals.  

Most Implemented Library

  • Numpy

This popular library encapsulates the n-dimensional arrays when it comes to homogeneous data categories with several operations that are being performed. 

#11 Dice Rolling Simulator

This is one of the simplified but efficient Python projects that is showcased in a portfolio or resume. This can create the knowing credibility of the fundamental concept of Python. 

Most Implemented Library

  • Random

Random is a pre-determined model that is utilized for creating and functioning with the random values. The random values offer several tactics that can be utilized for generating and manipulating the random variables.

Which Project Platform Should You Choose?

You may wonder which project platform should you select for your python projects. It is essential to develop your software projects on a specific platform so that others (particularly those lacking technical expertise) can also use your product. There are three main platforms that developers use to build python projects – Web, desktop, and command-line.

Web

Web applications are software projects that can run on the Web. Anyone with a working internet connection can access web applications on any device – you don’t need to download them separately. Thus, if you want to make a software product for public use, the Web is the ideal platform for such applications. 

Web applications are elaborate projects having both back-end and front-end. While the back end refers to the business logic of your application that manipulates and stores the data, the front end refers to the user interface of your application – the part that users can see and interact with. Keeping the back end as the focus of your web application, you must also learn the basics of front-end development with tools like JavaScript, HTML, and CSS. 

However, if you work with Python, it can take care of all your back-end and front-end development needs. Python has an exclusive library that eliminates the need for using JavaScript, HTML, and CSS – Anvil. Apart from this, there are many other Python-based web frameworks like Django, Flask, Web2Py, CherryPy, and Pylons, to name a few. 

Desktop GUI

Since desktop applications are widely used by people across the globe, building a desktop application is a great project idea for both freshers and intermediate-level Python developers. The best part about developing desktop GUIs (Graphical User Interfaces) is that you need not learn any front-end technology. Python is all you will need for creating desktop applications.

Python comes with several frameworks for building desktop applications. While PySimpleGUI is a user-friendly Python framework, PyQt5 is one of the advanced Python-based GUI frameworks. 

Once you develop a desktop GUI, you can even make it compatible with all three major operating systems (Linux, Windows, or macOS) by compiling it into executable code for the OS you wish to run it on. 

Command-Line

Command-Line Applications are those applications/programs where user interaction is entirely dependent on the terminal and shell. These applications function in a console window. As such, they are devoid of any form of graphics and visual interface for the users to see. Thus, to use command-line applications, you have to enter specific commands – while users can enter their input (commands) using ASCII characters, the app will also provide the output through ASCII. This is one of the most popular python projects in recent times. 

Naturally, command-line applications demand a certain level of technical know-how of commands. Although they aren’t as user-friendly as web or desktop applications, common-line applications are robust and powerful. Python has a range of useful command-line frameworks, including click, docopt, Plac, Cliff, and Python Fire.

Choose the Right Program

If you are looking forward to building a career in data science, picking the right program is imperative. Being a part of data science courses that can arm you with scholastic and practical expertise is paramount. State-of-the-art language program courses will help you attain exposure to real-world cases and studies, providing pragmatic knowledge and acumen. Python programs deliver the ultimate insight to generate insightful reports, analyze data, and reach data-driven business decisions. 

Python Project Ideas: Conclusion

In this article, we have covered 42Python project ideas. We started with some beginner projects which you can solve with ease. Once you finish with these simple python projects, I suggest you go back, learn a few more concepts and then try the intermediate projects. When you feel confident, you can then tackle advanced projects. If you wish to improve your python skills, you need to get your hands on these Python project ideas. Now go ahead and put to test all the knowledge that you’ve gathered through our python project ideas guide to building your very own python project!

I hope you will learn a lot while working on these python projects. If you are curious about learning data science to be in the front of fast-paced technological advancements, check out upGrad & IIM-K’s Professional Certificate Program in Data Science for Business Decision Making and upskill yourself for the future.

Check out our other data science courses at upGrad.com

Frequently Asked Questions (FAQs)

1. What are some Machine Learning project ideas for beginners?

Below are some interesting Ml projects that use Python as the main programming language: Some of the tweets can be a bit offensive for a respective audience and the Tweets Sorting Tool can be used to avoid them. This machine learning project filters the tweets based on some keywords. Working on the neural network is one of the best domains to test your machine learning concepts. Handwritten characters classifier works on neural networks to identify handwritten English alphabets from A-Z. The Sentiment Analysis Model is used to detect and identify a person’s feelings and sentiments behind a post or picture posted on social media.

2. What are the major components of a Python project?

The following components highlight the most general architecture of a Python project. The problem statement is the fundamental component on which the whole project is based. It defines the problem that your model is going to solve and discusses the approach that your project will follow. The dataset is a very crucial component of your project and should be chosen carefully. Only large enough datasets from trusted sources should be used for the project. The algorithm you are using to analyze your data and predict the results. Popular algorithmic techniques include Regression Algorithms, Regression Trees, Naive Bayes Algorithm, and Vector Quantization.

3. Which Python libraries are prerequisites to getting started with the project development?

Python has a wide range of rich libraries and modules that makes it one of the best and most versatile languages for development purposes. The following are some of the most popular Python libraries - TensorFlow is a boon to Machine Learning engineers. This library is developed by Google and can be considered a computational library. If you are working with complex data then you must have Scikit-Learn in your arsenal. This library provides a cross-validation feature which allows various methods to check the accuracy of your model. Numpy is again a machine learning library used by other Python libraries like TensorFlow to perform internal operations. Keras is another popular Python library that provides a convenient mechanism for neural networks.

Did you find this article helpful?

Rohit Sharma

Rohit Sharma is the Program Director for the UpGrad-IIIT Bangalore, PG Diploma Data Analytics Program.

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I can’t say for sure that the pizza was what persuaded him to take the company’s offer, but a little old-fashioned wooing never hurts. Button up the process – Just as it helps to have an expedited process, it also works to your benefit is the process is as smooth and trouble-free as you can make it. This means hassle-free travel arrangements, on-time interviews, and quick feedback. Network – make sure that you know the best of the talent available in the market at all levels and keep in touch with them thru porfessional social sites on subtle basis as this will come handy in picking the right candidate on selective basis Redesigned Interview Process In the old days one would screen resumes and then schedule lots of 1:1’s. Typically people would ask questions aimed at assessing a candidate’s proficiency with stats, technicality, and ability to solve problems. But there were three problems with this – the interviews weren’t coordinated well enough to get a holistic view of the candidate, we were never really sure if their answers would translate to effective performance on the job, and from the perspective of the candidate it was a pretty lengthy interrogation. So, a new interview process need to be designed that is much more effective and transparent – we want to give the candidate a sense for what a day in the life of a member on the team is like, and get a read on what it would be like to work with a company. In total it takes about two days to make a decision, and there be no false positives (possibly some false negatives though), and the feedback from both the candidates and the team members has been positive. There are four steps to the process: Resume/phone screens – look for people who have experience using data to drive decisions, and some knowledge of what your company is all about. On both counts you’ll get a much deeper read later in the process; you just want to make sure that moving forward is a good use of either of both of your time. Basic data challenge – The goal here is to validate the candidate’s ability to work with data, as described in their resume. So send a few data sets to them and ask a basic question; the exercise should be easy for anyone who has experience. In-house data challenge – This is should be the meat of the interview process. Try to be as transparent about it as possible – they’ll get to see what it’s like working with you and vice versa. So have the candidate sit with the team, give them access to your data, and a broad question. They then have the day to attack the problem however they’re inclined, with the support of the people around them. Do encourage questions, have lunch with them to ease the tension, and check-in periodically to make sure they aren’t stuck on something trivial. At the end of the day, we gather a small team together and have them present their methodology and findings to you. Here, look for things like an eye for detail (did they investigate the data they’re relying upon for analysis), rigor (did they build a model and if so, are the results sound), action-oriented (what would we do with what you found), and communication skills. Read between the resume lines Intellectual curiosity is what you should discover from the project plans. It’s what gives the candidate the ability to find loopholes or outliers in data that helps crack the code to find the answers to issues like how a fraudster taps into your system or what consumer shopping behaviors should be considered when creating a new product marketing strategy. Data scientists find the opportunities that you didn’t even know were in the realm of existence for your company. They also find the needle in the haystack that is causing a kink in your business – but on an entirely monumental scale. In many instances, these are very complex algorithms and very technical findings. However, a data scientist is only as good as the person he must relay his findings to. Others within the business need to be able to understand this information and apply these insights appropriately. Explore our Popular Data Science Courses Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Courses Good data scientists can make analogies and metaphors to explain the data but not every concept can be boiled down in layman’s terms. A space rocket is not an automobile and, in the brave new world, everyone must make this paradigm shift. Top Data Science Skills You Should Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Online Certification Inferential Statistics Online Certification 2 Hypothesis Testing Online Certification Logistic Regression Online Certification 3 Linear Regression Certification Linear Algebra for Analysis Online Certification upGrad’s Exclusive Data Science Webinar for you – Watch our Webinar on The Future of Consumer Data in an Open Data Economy document.createElement('video'); https://cdn.upgrad.com/blog/sashi-edupuganti.mp4 Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Our learners also read: Free Python Course with Certification And lastly, the data scientist you’re looking for needs to have strong business acumen. Do they know your business? Do they know what problems you’re trying to solve? And do they find opportunities that you never would have guessed or spotted?
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by upGrad

14 May'16
UpGrad partners with Analytics Vidhya

5.67K+

UpGrad partners with Analytics Vidhya

We are happy to announce our partnership with Analytics Vidhya, a pioneer in the Data Science community. Analytics Vidhya is well known for its impressive knowledge base, be it the hackathons they organize or tools and frameworks that they help demystify. In their own words, “Analytics Vidhya is a passionate community for Analytics/Data Science professionals, and aims at bringing together influencers and learners to augment knowledge”. Explore our Popular Data Science Degrees Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Degrees We are joining hands to provide candidates of our PG Diploma in Data Analytics, an added exposure to UpGrad Industry Projects. While the program already covers multiple case studies and projects in the core curriculum, these projects with Analytics Vidhya will be optional for students to help them further hone their skills on data-driven problem-solving techniques. To further facilitate the learning, Analytics Vidhya will also be providing mentoring sessions to help our students with the approach to these projects. Our learners also read: Free Online Python Course for Beginners Top Essential Data Science Skills to Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Certifications Inferential Statistics Certifications 2 Hypothesis Testing Certifications Logistic Regression Certifications 3 Linear Regression Certifications Linear Algebra for Analysis Certifications This collaboration brings great value to the program by allowing our students to add another dimension to their resume which goes beyond the capstone projects and case studies that are already a part of the program. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? Through this, we hope our students would be equipped to showcase their ability to dissect any problem statement and interpret what the model results mean for business decision making. This also helps us to differentiate UpGrad-IIITB students in the eyes of the recruiters. upGrad’s Exclusive Data Science Webinar for you – Transformation & Opportunities in Analytics & Insights document.createElement('video'); https://cdn.upgrad.com/blog/jai-kapoor.mp4 Check out our data science training to upskill yourself
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by Omkar Pradhan

09 Oct'16
Data Analytics Student Speak: Story of Thulasiram

5.68K+

Data Analytics Student Speak: Story of Thulasiram

When Thulasiram enrolled in the UpGrad Data Analytics program, in its first cohort, he was not very different for us, from the rest of our students in this. While we still do not and should not treat learners differently, being in the business of education – we definitely see this particular student in a different light. His sheer resilience and passion for learning shaped his success story at UpGrad. Humble beginnings Born in the small town of Chittoor, Andhra Pradesh, Thulasiram does not remember much of his childhood given that he enlisted in the Navy at a very young age of about 15 years. Right out of 10th standard, he trained for four years, acquiring a diploma in mechanical engineering. Thulasiram came from humble means. His father was the manager of a small general store and his mother a housewife. It’s difficult to dream big when leading a sheltered life with not many avenues for exposure to unconventional and exciting opportunities. But you can’t take learning out of the learner. “One thing I remember about school is our Math teacher,” reminisces Thulasiram, “He used to give us lot of puzzles to solve. I still remember one puzzle. If you take a chessboard and assume that all pawns are queens; you have to arrange them in such a way that none of the eight pawns should die. Every queen, should not affect another queen. It was a challenging task, but ultimately we did it, we solved it.” Navy & MBA At 35 years of age, Thulasiram has been in the navy for 19 years. Presently, he is an instructor at the Naval Institute of Aeronautical Technology. “I am from the navy and a lot of people don’t know that there is an aviation wing too. So, it’s like a dream; when you are a small child, you never dream of touching an aircraft, let alone maintaining it. I am very proud of doing this,” says Thulasiram on taking the initiative to upskill himself and becoming a naval-aeronautics instructor. When the system doesn’t push you, you have to take the initiative yourself. Thulasiram imbibed this attitude. He went on to enroll in an MBA program and believes that the program drastically helped improve his communication skills and plan his work better. How Can You Transition to Data Analytics? Data Analytics Like most of us, Thulasiram began hearing about the hugely popular and rapidly growing domain of data analytics all around him. Already equipped with the DNA of an avid learner and keen to pick up yet another skill, Thulasiram began researching the subject. He soon realised that this was going to be a task more rigorous and challenging than any he had faced so far. It seemed you had to be a computer God, equipped with analytical, mathematical, statistical and programming skills as prerequisites – a list that could deter even the most motivated individuals. This is where Thulsiram’s determination set him apart from most others. Despite his friends, colleagues and others that he ran the idea by, expressing apprehension and deterring him from undertaking such a program purely with his interests in mind – time was taken, difficulty level, etc. – Thulasiram, true to the spirit, decided to pursue it anyway. Referring to the crucial moment when he made the decision, he says, If it is easy, everybody will do it. So, there is no fun in doing something which everybody can do. I thought, let’s go for it. Let me push myself — challenge myself. Maybe, it will be a good challenge. Let’s go ahead and see whether I will be able to do it or not. UpGrad Having made up his mind, Thulasiram got straight down to work. After some online research, he decided that UpGrad’s Data Analytics program, offered in collaboration with IIIT-Bangalore that awarded a PG Diploma on successful completion, was the way to go. The experience, he says, has been nothing short of phenomenal. It is thrilling to pick up complex concepts like machine learning, programming, or statistics within a matter of three to four months – a feat he deems nearly impossible had the source or provider been one other than UpGrad. Our learners also read: Top Python Free Courses Favorite Elements Ask him what are the top two attractions for him in this program and, surprising us, he says deadlines! Deadlines and assignments. He feels that deadlines add the right amount of pressure he needs to push himself forward and manage time well. As far as assignments are concerned, Thulasiram’s views resonate with our own – that real-life case studies and application-based learning goes a long way. Working on such cases and seeing results is far superior to only theoretical learning. He adds, “flexibility is required because mostly only working professionals will be opting for this course. You can’t say that today you are free, because tomorrow some project may be landing in your hands. So, if there is no flexibility, it will be very difficult. With flexibility, we can plan things and maybe accordingly adjust work and family and studies,” giving the UpGrad mode of learning, yet another thumbs-up. Amongst many other great things he had to say, Thulasiram was surprised at the number of live sessions conducted with industry professionals/mentors every week. Along with the rest of his class, he particularly liked the one conducted by Mr. Anand from Gramener. Top Data Science Skills to Learn to upskill SL. No Top Data Science Skills to Learn 1 Data Analysis Online Courses Inferential Statistics Online Courses 2 Hypothesis Testing Online Courses Logistic Regression Online Courses 3 Linear Regression Courses Linear Algebra for Analysis Online Courses What Kind of Salaries do Data Scientists and Analysts Demand? Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? upGrad’s Exclusive Data Science Webinar for you – ODE Thought Leadership Presentation document.createElement('video'); https://cdn.upgrad.com/blog/ppt-by-ode-infinity.mp4 Explore our Popular Data Science Courses Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Courses “Have learned most here, only want to learn..” Interested only in learning, Thulasiram made this observation about the program – compared to his MBA or any other stage of life. He signs off calling it a game-changer and giving a strong recommendation to UpGrad’s Data Analytics program. We are truly grateful to Thulasiram and our entire student community who give us the zeal to move forward every day, with testimonials like these, and make the learning experience more authentic, engaging, and truly rewarding for each one of them. If you are curious to learn about data analytics, data science, check out IIIT-B & upGrad’s PG Diploma in Data Science which is created for working professionals and offers 10+ case studies & projects, practical hands-on workshops, mentorship with industry experts, 1-on-1 with industry mentors, 400+ hours of learning and job assistance with top firms.
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by Apoorva Shankar

07 Dec'16
Decoding Easy vs. Not-So-Easy Data Analytics

5.12K+

Decoding Easy vs. Not-So-Easy Data Analytics

Authored by Professor S. Sadagopan, Director – IIIT Bangalore. Prof. Sadagopan is one of the most experienced academicians on the expert panel of UpGrad & IIIT-B PG Diploma Program in Data Analytics. As a budding analytics professional confounded by jargon, hype and overwhelming marketing messages that talk of millions of upcoming jobs that are paid in millions of Rupees, you ought to get clarity about the “real” value of a data analytics education. Here are some tidbits – that should hopefully help in reducing your confusion. Some smart people can use “analytical thinking” to come up with “amazing numbers”; they are very useful but being “intuitive”, they cannot be “taught.” For example: Easy Analytics Pre-configuring ATMs with Data Insights  “We have the fastest ATM on this planet” Claimed a respected Bank. Did they get a new ATM made especially for them? No way. Some smart employee with an analytical mindset found that 90% of the time that users go to an ATM to withdraw cash, they use a fixed amount, say Rs 5,000. So, the Bank re-configured the standard screen options – Balance Inquiry, Withdrawal, Print Statement etc. – to include another option. Withdraw XYZ amount, based on individual customer’s past actions. This ended up saving one step of ATM operation. Instead of selecting the withdrawal option and then entering the amount to be withdrawn, you could now save some time – making the process more convenient and intuitive. A smart move indeed, however, this is something known as “Easy Analytics” that others can also copy. In fact, others DID copy, within three months! A Start-Up’s Guide to Data Analytics Hidden Data in the Weather In the sample data-sets that used to accompany a spreadsheet product in the 90’s, there used to be data on the area and population of every State in the United States. There was also an exercise to teach the formula part of the spreadsheet to compute the population density (population per sq. km). New Jersey, with a population of 467 per sq. km, is the State with the highest density. While teaching a class of MBA students in New Jersey, I met an Indian student who figured out that in terms of population density, New Jersey is more crowded than India with 446 people per sq. km!  An interesting observation, although comparing a State with a Country is a bit misleading. Once again, an Easy Analytics exercise leading to a “nice” observation! Some simple data analytics exercises can be routinely done, and are made relatively easier, thanks to amazing tools: B-School Buying Behavior Decoded In a B-School in India that has a store on campus, (campus is located far from the city center) some smart students put several years of sales data of their campus store. They were excited by the phenomenal computer power and near, idiot-proof analytics software. The real surprise, however, was that eight items accounted for 85% of their annual sales. More importantly, these eight items were consumed in just six days of the year! Everyone knew that a handful of items were the only fast-moving items, but they did not know the extent (85%) or the intensity (consumption in just six days) of this. It turns out that in the first 3 days of the semester the students would stock the items for the full semester! The B-School found it sensible to request a nearby store to prop up a temporary stall for just two weeks at the beginning of the semesters and close down the Campus Store. This saved useful space and costs without causing major inconvenience to the students. A good example of Easy Analytics done with the help of a powerful tool. Top 4 Data Analytics Skills You Need to Become an Expert! The “Not So Easy” Analytics needs deep analytical understanding, tools, an ‘analytical mindset’ and some hard work. Here are two examples, one taken from way back in the 70’s and the other occurring very recently: Not-So-Easy Analytics To Fly or Not to Fly, That is the Question Long ago, the American Airlines perfected planned overbooking of airline seats, thanks to SABRE Airline Reservation system that managed every airline seat. Armed with detailed past data of ‘empty seats’ and ‘no show’ in every segment of every flight for every day through the year, and modeling airline seats as perishable commodities, the American Airlines was able to improve yield, i.e., utilization of airplane capacity. They did this through planned overbooking – selling more tickets than the number of seats, based on projected cancellations. Explore our Popular Data Science Online Certifications Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Online Certifications If indeed more passengers showed up than the actual number of seats, American Airlines would request anyone volunteering to forego travel in the specific flight, with the offer to fly them by the next flight (often free) and taking care of hotel accommodation if needed. Sometimes, they would even offer cash incentives to the volunteer to opt-out. Using sophisticated Statistical and Operational Research modeling, American Airlines would ensure that the flights went full and the actual incidents of more passengers than the full capacity, was near zero. In fact, many students would look forward to such incidents so that they could get incentives, (in fact, I would have to include myself in this list) but rarely were they rewarded!) upGrad’s Exclusive Data Science Webinar for you – Transformation & Opportunities in Analytics & Insights document.createElement('video'); https://cdn.upgrad.com/blog/jai-kapoor.mp4 What American Airlines started as an experiment has become the standard industry practice over the years. Until recently, a team of well-trained (often Ph.D. degree holders) analysts armed with access to enormous computing power, was needed for such an analytics exercise to be sustained. Now, new generation software such as the R Programming language and powerful desktop computers with significant visualization/graphics power is changing the world of data analytics really fast. Anyone who is well-trained (not necessarily requiring a Ph.D. anymore) can become a first-rate analytics professional. Top Data Science Skills You Should Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Online Certification Inferential Statistics Online Certification 2 Hypothesis Testing Online Certification Logistic Regression Online Certification 3 Linear Regression Certification Linear Algebra for Analysis Online Certification Unleashing the Power of Data Analytics Our learners also read: Free Python Course with Certification Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences?   Cab Out of the Bag Uber is yet another example displaying how the power of data analytics can disrupt a well-established industry. Taxi-for-sure in Bangalore and Ola Cabs are similar to Uber. Together, these Taxi-App companies (using a Mobile App to hail a taxi, the status monitor the taxi, use and pay for the taxi) are trying to convince the world to move from car ownership to on-demand car usage. A simple but deep analytics exercise in the year 2008 gave such confidence to Uber that it began talking of reducing car sales by 25% by the year 2025! After building the Uber App for iPhone, the Uber founder enrolled few hundreds of taxi customers in San Francisco and few hundreds of taxi drivers in that area as well. All that the enrolled drivers had to do was to touch the Uber App whenever they were ready for a customer. Similarly, the enrolled taxi customers were requested to touch the Uber App whenever they were looking for a taxi. Thanks to the internet-connected phone (connectivity), Mobile App (user interface), GPS (taxi and end-user location) and GIS (location details), Uber could try connecting the taxi drivers and the taxi users. The real insight was that nearly 90% of the time, taxi drivers found a customer, less than 100 meters away! In the same way, nearly 90% of the time, taxi users were connected with their potential drivers in no time, not too far away. Unfortunately, till the Uber App came into existence, riders and taxi drivers had no way of knowing this information. More importantly, they both had no way of reaching each other! Once they had this information and access, a new way of taxi-hailing could be established. With back-end software to schedule taxis, payment gateway and a mobile payment mechanism, a far more superior taxi service could be established. Of course, near home, we had even better options like Taxi-for-sure trying to extend this experience even to auto rickshaws. The rest, as they say, is “history in the making!” Deep dive courses in data analytics will help prepare you for such high impact applications. It is not easy, but do remember former US President Kennedy’s words “we chose to go to the Moon not because it is easy, but because it is hard!” Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.  
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by Prof. S. Sadagopan

14 Dec'16
Launching UpGrad’s Data Analytics Roadshow – Are You Game?

5.14K+

Launching UpGrad’s Data Analytics Roadshow – Are You Game?

We, at UpGrad, are excited to announce a brand new partnership with various thought leaders in the Data Analytics industry – IIIT Bangalore, Genpact, Analytics Vidhya and Gramener – to bring to you a one-of-a-kind Analytics Roadshow! As part of this roadshow, we will be conducting several back-to-back events that focus on different aspects of analytics, creating interaction points across India, to do our bit for a future ready and analytical, young workforce.  Also Read: Analytics Vidhya article on the UpGrad Data Analytics Roadshow Here is the line-up for the roadshow, to give you a better sense of what to expect: 9 webinars – These webinars (remote) will be conducted by industry experts and are aimed at increasing analytics awareness, providing a way for aspirants to interact with industry practitioners and getting their tough questions answered. 11 workshops – The workshops will be in-person events to take these interactions to the next level. These would be spread across 6 cities – Delhi, Bengaluru, Hyderabad, Chennai, Mumbai and Pune. So, if you are in any of these cities, we are looking forward to interact with you. Featured Data Science program for you: Master of Science in Data Science from from IIIT-B 2 Conclaves – These conclaves are larger events with a pre-defined agendas and time for networking. The first conclave is happening on the 17th of December in Bengaluru.  Explore our Popular Data Science Online Certifications Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Online Certifications Hackathon – Time to pull up your sleeves and showcase your nifty skills. We will be announcing the format of the event shortly. “We find that the IT in­dustry is ab­sorb­ing al­most half of all of the ana­lyt­ics jobs. Banking is the second largest, but trails at al­most one fourth of IT’s re­cruit­ing volume. It is in­ter­est­ing that data rich in­dus­tries like Retail, Energy and Insurance are trail­ing near the bot­tom, lower than even con­struc­tion or me­dia, who handle less data. Perhaps these are ripe for dis­rup­tion through ana­lyt­ics?” Our learners also read: Learn Python Online for Free Mr. S. Anand, CEO of Gramener, wonders aloud. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences? upGrad’s Exclusive Data Science Webinar for you – Watch our Webinar on The Future of Consumer Data in an Open Data Economy document.createElement('video'); https://cdn.upgrad.com/blog/sashi-edupuganti.mp4   Top Data Science Skills You Should Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Online Certification Inferential Statistics Online Certification 2 Hypothesis Testing Online Certification Logistic Regression Online Certification 3 Linear Regression Certification Linear Algebra for Analysis Online Certification Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career.
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by Apoorva Shankar

15 Dec'16
What’s Cooking in Data Analytics? Team Data at UpGrad Speaks Up!

5.22K+

What’s Cooking in Data Analytics? Team Data at UpGrad Speaks Up!

Team Data Analytics is creating the most immersive learning experience for working professionals at UpGrad. Data Insider recently checked in to me to get my insights on the data analytics industry; including trends to watch out for and must-have skill sets for today’s developers. Here’s how it went: How competitive is the data analytics industry today? What is the demand for these types of professionals? Let’s talk some numbers, a widely-quoted McKinsey report states that the United States will face an acute shortage of around 1.5 million data professionals by 2018. In India, which is emerging as the global analytics hub, the shortage of such professionals could go up to as high as 200,000. In India alone, the number of analytics jobs saw a 120 percent rise from June 2015 to June 2016. So, we clearly have a challenge set out for us. Naturally, because of acute talent shortage, talented professionals are high in demand. Decoding Easy vs. Not-So-Easy Analytics What trends are you following in the data analytics industry today? Why are you interested in them? There are three key trends that we should watch out for: Personalization I think the usage of data to create personalized systems is a key trend being adopted extremely fast, across the board. Most of the internet services are removing the anonymity of online users and moving towards differentiated treatment. For example, words recommendations when you are typing your messages or destinations recommendations when you are using Uber. Our learners also read: Learn Python Online for Free End of Moore’s Law Another interesting trend to watch out for is how companies are getting more and more creative as we reach the end of Moore’s Law. Moore’s Law essentially states that every two years we will be able to fit double the number of transistors that could be fit on a chip, two years ago. Because of this law, we have unleashed the power of storing and processing huge amounts of data, responsible for the entire data revolution. But what will happen next? IoT Another trend to watch out for, for the sheer possibilities it brings. It’s the emergence of smart systems which is made possible by the coming together of cloud, big data, and IoT (internet of things). Explore our Popular Data Science Courses Executive Post Graduate Programme in Data Science from IIITB Professional Certificate Program in Data Science for Business Decision Making Master of Science in Data Science from University of Arizona Advanced Certificate Programme in Data Science from IIITB Professional Certificate Program in Data Science and Business Analytics from University of Maryland Data Science Courses What skill sets are critical for data engineers today? What do they need to know to stay competitive? A good data scientist sits at a rare overlap of three areas: Domain Knowledge This helps understand and appreciate the nuances of a business problem. For e.g, an e-commerce company would want to recommend complementary products to its buyers. Statistical Knowledge Statistical and mathematical knowledge help to inform data-driven decision making. For instance, one can use market basket analysis to come up with complementary products for a particular buy. Technical Knowledge This helps perform complex analysis at scale; such as creating a recommendation system that shows that a buyer might prefer to also buy a pen while buying a notebook. How Can You Transition to Data Analytics? Outside of their technical expertise, what other skills should those in data analytics and business intelligence be sure to develop? Ultimately, data scientists are problem solvers. And every problem has a specific context, content and story behind it. This is where it becomes extremely important to tie all these factors together – into a common narrative. Essentially all data professionals need to be great storytellers. In this respect, one of the key skills for analysts to sharpen would be, breaking down the complexities of analytics for others working with them. They can appreciate the actual insights derived – and work toward a common business goal. In addition, what is as crucial is getting into a habit of constantly learning. Even if it means waking up every morning and reading what’s relevant and current in your domain. Top Essential Data Science Skills to Learn SL. No Top Data Science Skills to Learn 1 Data Analysis Certifications Inferential Statistics Certifications 2 Hypothesis Testing Certifications Logistic Regression Certifications 3 Linear Regression Certifications Linear Algebra for Analysis Certifications What should these professionals be doing to stay ahead of trends and innovations in the field? Professionals these days need to continuously upskill themselves and be willing to unlearn and relearn. The world of work and the industrial landscape of technology-heavy fields such as data analytics is changing every year. The only way to stay ahead, or even at par with these trends, is to invest in learning, taking up exciting industry-relevant projects, participating in competitions like Kaggle, etc. How important is mentorship in the data industry? Who can professionals look toward to help further their careers and their skills? Extremely important. Considering how fast this domain has emerged, academia and universities, in general, have not had the chance to keep up equally fast. Hence, the only way to stay industry-relevant with respect to this domain is to have industry-specific learning. This can only be done in two ways – through real-life case studies and mentors who are working/senior professionals and hail from the data analytics industry. In fact, at UpGrad, there is a lot of stress on industry mentorship for aspiring data specialists. This is in addition to a whole host of case studies and industry-relevant projects. Get data science certification from the World’s top Universities. Learn Executive PG Programs, Advanced Certificate Programs, or Masters Programs to fast-track your career. Read our popular Data Science Articles Data Science Career Path: A Comprehensive Career Guide Data Science Career Growth: The Future of Work is here Why is Data Science Important? 8 Ways Data Science Brings Value to the Business Relevance of Data Science for Managers The Ultimate Data Science Cheat Sheet Every Data Scientists Should Have Top 6 Reasons Why You Should Become a Data Scientist A Day in the Life of Data Scientist: What do they do? Myth Busted: Data Science doesn’t need Coding Business Intelligence vs Data Science: What are the differences?   Where are the best places for data professionals to find mentors? upGrad’s Exclusive Data Science Webinar for you – Transformation & Opportunities in Analytics & Insights document.createElement('video'); https://cdn.upgrad.com/blog/jai-kapoor.mp4 While it’s important for budding or aspiring data professionals to tap into their networks to find the right mentors, it is admittedly tough to do so. There are two main reasons that can be blamed for this. First, due to the nascent stage, the industry is at, it is extremely difficult to find someone with the requisite skill sets to be a mentor. Even if you find someone with considerable experience in the field, not everybody has the time and inclination to be an effective mentor. Hence most people don’t know where to go to be mentored. That’s where platforms like UpGrad come in, which provide you with a rich, industry-relevant learning experience. Nowhere else are you likely to chance upon such a wide range of industry tie-ups or associations for mentorship from very senior and reputed professionals. How Can You Transition to Data Analytics? What resources should those in the data analytics industry be using to ensure they’re educated and up-to-date on developments, trends, and skills? There are many. For starters, here are some good and pretty interesting blogs and resources that would serve aspiring/current data analysts well to keep up with Podcasts like Data Skeptic, Freakonomics, Talking Machines, and much more.   This interview was originally published on Data Insider.  
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by Rohit Sharma

23 Dec'16