Want to become a data scientist but don’t know Python? Don’t worry; we’ve got your back. With our free online Python course for beginners, you can learn Python online free and kickstart your data science journey. You don’t have to spend a dime to enroll in this program. The only investment you’d have to make is 30 minutes a day for a few weeks, and by the end, you’d know how to use Python for data science.
To enroll in our Python course free, head to our upStart page, select the “Python for Data Science” course, and register. This article will discuss why you should study Python for data science, our course contents, and what its advantages are. Let’s get started.
Table of Contents
Why Learn Python for Data Science?
Python is among the most popular programming languages on the planet. According to a survey from RedMonk, a prominent analyst firm, Python ranked 2nd in their ranking of programming languages by popularity.
In data science, Python has many applications. It has multiple libraries that simplify various data operations. For example, Pandas is a Python library for data analysis and manipulation. It offers numerous functions to manipulate vast quantities of structured data.
This way, it makes data analysis much more straightforward. Another primary Python library in data science is matplotlib, which helps you with data visualization. Python is one of the core skills of data science professionals. Learning it will undoubtedly help you in entering this field.
Why Choose Python for Data Science from upGrad?
There are many advantages to joining our Python free courses. Here are some of them:
1 to 1 Industry Mentorship
You’ll learn exclusively from a leading industry expert. They will guide you through the course, and you can ask them questions when required.
Cutting Edge Content
upGrad’s professionally created content ensures that you get the best online learning experience.
Weekly Live Lectures
You’ll get exclusive live lectures every week during the course. They will help you remove any doubts and streamline your learning experience.
After you complete our Python online course free, you’ll receive a certificate for completion. The certificate would enhance your CV substantially.
Apart from these benefits, the biggest one is that you can join the course for free. It doesn’t require any monetary investment. Let’s now discuss what the course is about and what it will teach you:
What Will You Learn?
Learning Python is crucial for becoming a data scientist. It has many applications in this field, and without it, you can’t perform many vital operations related to data science. Because Python is a programming language, many students and professionals hesitate to study it.
They read about Python’s various applications in data science, artificial intelligence, and machine learning and think it’s a highly complicated subject. However, Python is an elementary programming language that you can learn quickly.
Our free Python online course for beginners covers this prominent programming language’s basics and helps you understand its fundamental uses in data science. Our Python course free lasts for four weeks and has four sections, namely:
- Intro to Python
- Programming using Python
- Python Libraries
These sections allow you to learn Python in a stepwise manner. Let’s discuss each one of these sections in detail:
Intro to Python
In the first module of our Python online course free, you’ll get a stepwise tutorial to begin learning Python. It will familiarize you with Python’s fundamentals, what it is, and how you can learn this programming language.
Apart from the basics, this section will explain the various jargons present in data science to you. You’ll get to know the meaning behind many technical terms data scientists usually use, including EDA, NLP, Deep Learning, Predictive Analytics, etc. Understanding what Python is will give you the foundation you need to study its more advanced concepts later on.
When you’d know the meaning behind data science jargon, you would understand how straightforward this subject is. It’s an excellent method to get rid of your hesitation in learning data science. By the end of this module, you would be able to use data science jargon casually like another data professional.
Programming using Python
This section of our course will teach you Python’s basics from a coding perspective, including strings, lists, and data structures. Data structures are one of the essential concepts you can study in data science.
They help in organizing data so you can access it and perform operations on it quickly. Understanding data structures is vital to becoming a proficient data scientist. Many recruiters ask the candidates about data structures and their applications in technical interviews.
This module focuses on programming with Python in data science. So, it covers the basic concepts of many data structures, such as lists.
When you’re familiar with the basics, you can easily use them later in more advanced applications. For example, lists are among the most versatile data structures. They allow the storage of heterogeneous items (items of different data types) such as strings, integers, and even other lists.
Another prominent property that makes lists a preferred choice is they are mutable. This allows you to change their elements even after you create the list. This module of our Python free courses will cover many topics like this.
Python is popular among data scientists for many reasons. One of those reasons is its large number of libraries. There are more than 1,37,000 Python libraries. This number should give you an idea of how valuable these libraries are.
These libraries simplify specific processes and make it easier for developers to perform related functions. In this section of our free online Python course for beginners, you’ll learn about multiple Python libraries data scientists use, such as NumPy, matplotlib, and Pandas.
A Python library contains reusable code that helps you perform specific tasks with less effort. Unlike C or C++, its libraries don’t focus on a context. They are collections of modules. You can import a module from another program to use its functionality. Every Python library simplifies certain functions.
For example, with NumPy, you can perform mathematical operations in Python smoothly. It has many high-level mathematical functions and support for multi-dimensional matrices and arrays. Understanding these libraries will help you in performing operations on data.
In the final section of our Python online course free, you’ll learn how to perform EDA through this programming language. EDA stands for Exploratory Data Analysis and focuses on understanding the data so you can derive valuable insights from the same.
EDA is a vital aspect of data analysis because it helps you discover many things in your data. For example, you can detect outliers by performing exploratory data analysis. Outliers are essential to detect for data cleaning.
Learning EDA will help you in understanding proper data arrangements too. It helps you discover hidden values, normalize the numerical variables, remove duplicates, and derive insights easily.
Must Read: Python Project Ideas & Topics for Beginners
How to Start
To join our Python online course free, you only have to follow these steps:
- Head to our upStart page
- Select the “Python for Data Science” course
- Click on Register
- Complete the registration process
That’s it. You can learn Python online free through our newly-launched upStart program and kickstart your data science journey. You’d only have to invest 30 minutes a day for a few weeks. This program requires no monetary investment.
If you have any questions or suggestions regarding this topic, please let us know in the comments below. We’d love to hear from you.
If you are curious to learn about Python, data science, check out IIIT-B & upGrad’s Executive PG Programme 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.