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An Expression on Data Science Project Ideas
Data Science is continuously thriving as a great career option for this generation. It is among the most promising & happening choices altogether. The market is boosting up with more demands for Data Scientists. It has been reported recently that the demand will increase further to many folds in the coming years. So, if you are a data science beginner, the best thing you can do is work on some real-time data science project ideas.
So, if you are an aspiring Data Scientist, it is highly recommended to practice skills to become an efficient professional for this field. After grabbing some very good theoretical knowledge on Data Science, if you are really looking ahead to explore what it seems like to be a professional, then now is the time to do some practical projects.
You must do some of the technical & real-time Data Science projects so that it helps you boost your career growth. The more you practice with Data Science projects, we assure you that you can keep up the pace towards becoming a sound Data Scientist professional.
Therefore, if you do some live Data Science Projects, it will enhance your knowledge, technical skills, and overall confidence. But most importantly, if you showcase even a few Data Science projects in your resume, then getting a good job is much easier for you. Why so? Because then the interviewer will know that you are really serious about a Data Science career.
Your real-time experience on Live Data Science Projects will let you hold a strong grip on Data Science trends & technologies. So, layout your hands on real-time Data Science projects & you will know how beneficial it will be for your speedy career growth. After all these discussions, we know that finding that perfect Data Science Project idea for your Data Science project concerns you even more than its actual implementation.
In this Data Science blog, we have listed out the names of a few Data Science Project ideas. And to answer your question – ‘What kind of Data Science project is good to start with?’, we have compiled a few good Data Science Project ideas for you to choose from.
Here are 50 Data Science Project ideas for you, and in the blog ahead, we are discussing a few of these projects in detail. So let’s begin!
- Analyzing the impact of climate change on global food supply
- Weather Prediction
- Keyword generation for google ads
- Traffic Signs Recognition
- Wine Quality Analysis
- Stock Market Prediction
- Fake News Detection
- Video Classification
- Human Action Recognition
- Medical Report Generation using CT Scans
- Email Classification
- Uber Data Analysis
- Sound Classification
- Credit Card Fraud Detection
- Sign Language Recognition
- Class of Flower Prediction
- Colour Detection
- Loan Prediction
- Road Traffic Prediction
- Income Classification
- Speech Emotion Recognition
- Celebrity Voice Prediction
- Store Sales Prediction
- Detecting Parkinson’s Disease
- Air Pollution Prediction
- Age and Gender Detection
- Optimizing Product Price
- IMDB Predictions
- Handwritten Digit Recognition
- Quora Insincere Questions Classification
- Driver Drowsiness Detection
- Web Traffic Time Series Forecasting
- Survival Prediction on the Titanic
- Time Series Modelling
- Image Caption Generator
- Insurance Purchase Prediction
- Crime Analysis
- Customer Segmentation
- Taxi Trip Time Prediction
- Job Recommendation System
- Boston Housing Predictions
- Sentiment Analysis
- Interest Level in Rental Properties
- Keyword generation for Google Ads
- Breast Cancer Classification
- Employee Computer Access Needs
- Tweets Classification
- Movie Recommendation System
- Product Price Suggestions
Latest Data Science Project Ideas
We have segmented all the Data Science Project Ideas as per the learner’s level. Therefore, you will get a list of a few amazing project briefs for beginner, intermediate & advanced Data Science project ideas.
1. Beginner Level | Data Science Project Ideas
This list of data science project ideas for students is suited for beginners, and those just starting out with Python or Data Science in general. These data science project ideas will get you going with all the practicalities you need to succeed in your career as a data science developer.
Further, if you’re looking for data science project ideas for final year, this list should get you going. So, without further ado, let’s jump straight into some data science project ideas that will strengthen your base and allow you to climb up the ladder.
1.1 Climate Change Impacts on the Global Food Supply
Frequent Climate change and irregularities are big challenging environmental issues. These irregularities in climate divisions are drastically affecting the human lives residing on the Earth. This Data Science Project concentrates on how the climate impact will highly affect global food production worldwide and how much quantification will impact climate change.
The main aim of development for this project is to calculate the potentialities on the staple crop productions due to climate change. Through this project, all the implications related to temperatures & precipitation change. It will then be taken into account how much carbon dioxide affects the growth of plants and the uncertainties happening in the climatic conditioning. Hence, this project will largely deal with Data Visualisations. It will also compare the production in various regions at different time zones.
1.2 Fake News Detection
You can drive your Data Science career with this amazing Data Science Project idea for beginners – Detection of Fake News using Python language. The act of wrong or misleading journalism on a digital platform or fake news can be detected by this project. Falsifications are spreading out via social media platforms and online channels & digital media to attain any political agenda.
With this data science project idea, you can use Python language to develop a specific model that can precisely detect whether the news is real journalism or false information.. For this, you need to build a ‘TfidfVectorizer’ classifier and then use a ‘PassiveAggressiveClassifier’ to classify the news into either a “Real” and “Fake” segmentations. There will be a dataset of the shape of 7796×4 dimensions and execute all these in the ‘JupyterLab’.
The main idea of this Data Science project is to develop a real-time machine learning model that can correctly detect social media news authenticity. ‘TF’, commonly known as ‘Term Frequency’, is the total number of times any word will appear in a single document. Whereas, ‘IDF’ or ‘Inverse Document Frequency’ is a calculative measure of the value of a word & it is based on the reputational frequency of its occurrence appearing in the various documents.
The theory is on the ‘Common words’, if these common words happen to appear in multiple documents with a high frequency then they are considered as less important words. So, what ‘TFIDFVectorizer’ does is to analyze the collection of these documents and then accordingly create a ‘TF-IDF’ matrix to it.
Along with this, a ‘PassiveAggressive’ classifier will remain ‘passive’ in case the ‘classification outcome’ is correct; but on the other hand, it will change aggressively if the ‘classification outcome’ is incorrect. So, you can create a machine learning model to detect social media news to be genuine or fake news using this Data Science Project idea.
1.3 Human Action Recognition
This is a Data Science project on the human action recognition model. It will look at the short videos made on human beings where they are performing specific actions. This model tries to do a classification that is based on actions performed. In this Data science project, you need to use a complex neural network. This neural network is then trained on a specific dataset that contains these short videos. Then there is an accelerometer data that is associated with the dataset. The accelerometer data conversion is done first along with a ‘time-sliced’ representation. Thereafter, you have to use the ‘Keras’ library so that you can do training, validation, and testing of the network based on these datasets.
1.4 Forest Fire Prediction
One of the alarming & common disasters happening in today’s world is forest fires. These disasters are highly damaging to the ecosystem. To deal with such a disaster, a lot of money on infrastructure & controlling and handling is required. We can build a Data Science project using ‘k-means clustering’- it can identify any forest fires hotspots along with the severity of the fire at that particular spot.
It can be alternatively used for better resource allocation with the faster response time. Hence, using the meteorological data such as those seasons around which these kinds of fires tragedies are more likely to happen and various weather conditions that worsen them may increase these results’ accuracy levels.
1.5 Road Lane Line Detection
Another Data Science project ideas for beginners include a Live Lane-Line Detection Systems built-in Python language. In this project, a human driver receives guidance on lane detections through lines drawn on the road.
Not only this, it further refers to which direction the driver should steer their vehicle. This Data Science Project application is vital for the development of driverless cars. Hence, you can also develop an application with the powerful capability to identify a track line through the input images or via a continuous video frame.
2. Data Science Projects Ideas |Intermediate Level
2.1 Recognition of Speech Emotion
One of the popular Data Science project ideas is recognition of the speech emotion. If you want to learn the usage of different libraries, this project is perfect for you. You must have seen a lot of editor tools that can tell us how our speech emotion is appearing. This program model can be built as a Data Science project.
In this Data Science project, we will use ‘librosa’ that will perform a ‘Speech Emotion Recognition’ for us. The SER process is a trial process that can recognize human emotion. It can also recognise the speech from the affective states. As we use a combination of a tone and a pitch for expressing emotions through our voice.
The Speech Emotion Recognition model is absolutely possible. However, it can be a challenging project to perform as human emotions are very subjective. The annotation of the human audio is also quite challenging. So, here you will use the mfcc, mel & the chroma features. With this, you will also use the dataset known as ‘RAVDESS’ for the emotion recognition process. In this Data Science project, you will also learn how to develop an ‘MLPClassifier’ for this model.
2.2 Gender and Age Detection with Data Science
So, one of the impressive project ideas on Data Science is the ‘Gender and Age Detection with OpenCV’. With this kind of real-time project, you can easily grab your recruiter’s attention in a Data Science interview.
Talking about the project, the ‘Gender and Age Detection’ is a machine learning project based on computer visioning. Through this Data Science Project, you can learn the practical application of CNN i.e, the convolutional neural networks. Down the line, you will also use models that are trained by ‘Tal Hassner’ and ‘Gil Levi’ for ‘Adience’ dataset.
Along with this, you will also use some files such as – .pb, .prototxt, .pbtxt, & .caffemodel files. Heard about these terms? Read about these files? Understand models too? But do you know how to implement them? Well, you can learn it if you opt to develop a Data Science Project on it.
It’s a very practical project as you will create a model that can detect any human being’s age & gender through analyses of single face detection via an image. So, with this gender classification in a man or a woman can be classified. Also, the age can be classified among the ranges of 0-2/ 4-6/ 8- 2/ 15-20/ 25-32/ 38-43/ 48-53/ 60-100.
But due to various factors such as makeup, or brighter dim lighting, or an unusual facial expression, the recognition of the gender and the age from a single source can become challenging. Therefore, in this Data Science project, you will use a classification model instead of a regression model. A lot of practical & technical learning can be grabbed to upscale your technical skills with these kinds of projects. So, take up the challenge & work hard towards it to make an impressive Data Science Resume.
2.3 Driver Drowsiness Detection in Python
An excellent Data Science project idea for intermediate levels is the ‘Keras & OpenCV Drowsiness Detection System’. Driving overnight is not only tough but a risky job too. We have heard of a lot of cases where accidents happen because the driver fell asleep while driving.
Thus, this project can help prevent numerous road accidents that happen due to such cases. This project’s main aim is to recognize whenever the driver may get drowsy & fall asleep while driving. This project uses Python language where you can build a model that can timely detect the sleepy driver behavior and raises an alert alarm through a high beeping alarm.
In this project, you can implement a ‘deep learning model’ & with its use, you can do a classification among images where a human eye is open or close. Not just this, in this model another formula line is to calculate the score.
This score is based on the time period of how long the eyes remain closed. The score is maintained throughout the driving session. If that score increases & crosses a specified threshold, this model will throw workflow automation through which the alarm will start buzzing heavily.
So, with these kinds of Data Science projects implementations, you will learn all the basics of Data Science projects. You will implement it using ‘Keras’ and ‘OpenCV’. So, why are these used? Well, you are using ‘OpenCV’ to detect face & eye movements. Whereas, with ‘Keras’, you can classify the eye’s state whether it is open or close while using techniques of the Deep neural network.
Chatbots are increasingly becoming popular these days. So, for a Data Science project, it is a high on-demand requirement by almost all organizations. It is an essential segment of the business nowadays. These days, chatbots are playing a very crucial role in businesses. They are helping business lines to save an enormous amount of time on their human resources. It is used to provide an improved and personalized business service simultaneously.
There are many businesses who are offering services to their customers. To provide customer service on a large scale, it requires a lot of human resources, ample time, and many efforts to handle each customer on time. On the other hand, these chatbots can provide automation for customer interaction services simply by answering a set of frequent questions commonly inquired by the customers.
There are 2 types of chatbots available in today’s time: Domain-specific chatbot and Open-domain chatbot. The domain-specific chatbot is most often used for a particular problem solution. These are customized in a very strategic & smart manner so that they work strategically & effectively in relation to domain specifications. The second one, ‘Open-domain’ chatbots, needs a lot of training materials that are too continuously because, as per the name, it is developed to answer any kind of question.
Technically speaking, the chatbots are trained using the ‘Deep Learning’ techniques. They need a dataset with vocabulary listing, lists consisting of a common sentence, an intent which is behind them, and then the appropriate responses. This is one of the trending data science project ideas.
The ‘Recurring Neural Networks’ (The RNN’s) are the common methodologies to train chatbots. These bots contain encoders that can update the states as per the input sentences alongside intent. It then passes the specified state to the Chatbot.
Thereafter, the chatbot uses the decoder to search an appropriate & subsequent response according to inputted words & also besides the intent. With this Data Science project, you can easily learn Python language implementation as the complete project is itself made in Python. You can upscale your Python technical skills to a certain extent.
2.5 Handwritten Digit & Character Recognition Project
With this Data Science Project idea on ‘Handwritten Digit & Character Recognition with the help of CNN, you will practically learn Deep Learning concepts. So, if you are a budding Data Scientist or an enthusiast of machine learning then this is the perfect Data Science project idea for you. For this project development, you will use the ‘MNIST dataset’ of hand-written digits. This is a great project to get hands-on experience with Data Science as you will learn amazing ways that are involved in the process of project building.
As discussed, this project is implemented through the ‘Convolutional Neural Networks’. After this, for a real-time prediction, you will build a creative graphical- based user interface for drawing digits on the canvas, and thereafter you will build a model that will be used for the prediction of the digits.
The project’s focus is on developing the computer’s ability & to empower the computer system so that it can recognize characters in hand-written formats by humans. It will then evaluate it further to understand it with reasonable accuracy. With this project implementation, you can learn the practical implementation of the ‘Keras’ and also ‘Tkinter’ libraries.
These are some intermediate data science project ideas on which you can work. If you still like to test your knowledge and take on some tough projects
3. Advance Level Data Science Projects Ideas
3.1 Credit Card Fraud Detection Project
After implementing easy projects, you can now move to some advanced Data Science project ideas to learn more concepts. One such idea is Credit card Fraud Detection. With this project, you will learn how to use the R with different algorithms such as Decision Tree, Artificial Neural Networks, Logistic Regression, and the Gradient Boosting Classifier.
You can also learn to use the ‘Card Transactions’ datasets to classify the credit card transaction as a fraudulent activity or a genuine transaction. You will also learn to fit all the different types of models along with the plot performance curve for all of them. This is one of the best data science project ideas one can find.
3.2 Customer Segmentations
This is one of the most popular Data Science projects in the field of Data Science. Digital Marketing is an up & advanced way to target an audience for the companies through their online marketing activities for marketing purposes nowadays. So before running a marketing campaign, different customer segmentation is first done.
Customer Segmentation is among very popular applications of indeed unsupervised learning. Hereby, using clustering methods, companies can now easily identify the customers’ various segments for targeting the potential user-base. There are divisions made on customers & groups are formed according to the common characteristics such as gender, interest areas, age, and habits.
Based on these details they can effectively market each customer group. The project uses the ‘K-means clustering’ and you will learn how to perform visualizations on distributions such as gender and age. Customers annual incomes & average score values can also be analysed.
3.3 Traffic Signs Recognition
This project aims to develop a model to achieve high accuracy in self-driving car technologies using CNN techniques. Traffic signs and traffic rules are of utmost importance for every driver and it must be followed to avoid accidents. To follow these rules, the user must understand how the traffic signals appear to be.
It’s a general rule that to obtain a driving license, an individual has to learn all the driving signals. But for autonomous vehicles, there are programs developed such as the ‘Traffic signs recognition’ using CNN, where you can learn how to program a model that can precisely identify various kinds of traffic signals by the input of an image.
There is a dataset called the ‘German Traffic signs recognition benchmark’. It is commonly known as the GTSRB that is used in the development of a Deep Neural Network for recognizing the class of all the traffic signs belonging to which class type. You will also learn practical knowledge of building a GUI for application interaction.
In this article, we have covered top data science project ideas. We started with some beginner projects which you can solve with ease. Once you finish with these simple data science 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 the advanced projects. If you wish to improve your data science skills, you need to get your hands on these data science project ideas. Now go ahead and put to test all the knowledge that you’ve gathered through our data science project ideas guide to build your very own data science project!
We wish that you will drastically improve all the skills of Data Science with the project ideas we presented to you here in this blog. But in case you are new to the Data Science field & would love to learn the Data Science & build similar models for the technological advancements, we recommend you to check out the online course on upGrad & IIIT-B’s PG Diploma programs to learn & upskill in the Data Science world with experienced & expert professionals.
With the right set of knowledge, guidance & tools, you can learn any Data Science project. No level is difficult for learners. That’s why all these live projects are a perfect way to enhance one’s skills and fast progress in attaining mastery. At upGrad, we offer 3 Data Science Online Certification:
1. Executive PG Programme in Data Science (12 months)
From IIIT Bangalore
2. Master of Science in Data Science (18 months)
From Liverpool John Moores University
3. Advanced Certificate Programme in Data Science (7 months)
From IIIT Bangalore
Try these Data science online certifications by upGrad as we are sure that they will help you in your Data Science career path. Therefore, don’t delay! Start your practice now!
The following points should be kept in mind before starting any Data Science project: The following components highlight the most general architecture of a Data Science project: The following are the essential skills and tools any Data Science enthusiast should master:
How to make a good Data Science project?
Choose the programming language that you are comfortable with. However, the language chosen should be one of the in-demand languages such as Python, R, and Scala.
Use datasets from trusted sources. You can use Kaggle datasets. Moreover, make sure that the dataset you are using does not contain errors.
Find errors or outliers in your dataset and rectify them before training your model. You can use visualization tools to find the errors in your dataset.
Describe the major components that a Data Science project should have?
Problem Statement: This 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.
Dataset: This is a very crucial component for your project and should be chosen carefully. Only large enough datasets from trusted sources should be used for the project.
Algorithm: This includes 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.
Training Models: This involves training your model against various inputs and predicting the output. This component decides the accuracy of your project. Using proper training techniques can produce better outcomes.
What are the skills required to be a Data Scientist?
1. Statistical Skills including Probability
2. Analytical Skills to analyze and test the data.
3. Programming languages such as Python, R, Scala, and JAVA.
4.Data Visualization Tools such as Power BI, Tableau
5. Algorithms including Regression, Decision Trees, Bayes Algorithm
6. Calculus and Algebra.
7. Communication and Presentation Skills
8. Databases such as SQL
9. Cloud Computing to manage the resources
Apart from these technical skills, a professional Data Scientist should also have some soft skills to provide value to the company and improve interpersonal relationships. These skills include critical and curious thinking, business orientation, smart communication skills, problem-solving, team management, and creativity.
The following points should be kept in mind before starting any Data Science project:
The following components highlight the most general architecture of a Data Science project:
The following are the essential skills and tools any Data Science enthusiast should master: