Are you approaching the final year of your data science course?
If so, it may be the case that a data analytics project is among the requirements for earning your degree.
However, choosing the right data analytics project can be challenging due to the complexity associated with such projects. Many of them involve a steep learning curve, which may not be ideal if you don’t have too much time to spare.
In addition to that, some of these projects require data science tools with costly subscription plans.
It is for these reasons that I will be recommending proven project ideas, some of which I have tried out over the years to enhance my professional portfolio.
In this article, I’ll be taking you through some data analytics project ideas for final year students, so you can find one that meets your goals in terms of both budget and simplicity.
Let’s get started.
1. Telecommunications Churn Prediction
Customer churn is a huge problem in the telecommunications industry.
A study by the University of Zambia established that churn rates reach as high as 67% annually for telecom providers.
Among the leading factors was dissatisfaction with various services. It is for this reason that a telecommunications churn prediction system is among the most interesting data analytics project topics.
Binary classification can help with customer segmentation if you’re working with large telecommunications datasets, slotting your users into groups depending on a classification rule and in line with certain attributes.
Via a logistic regression model and a telecommunication data set, you can predict how many customers are likely to opt-out of a service. This project enables you to identify at-risk customers from various customer points, most notably a CRM system.
For a head start, these machine learning courses offer excellent ways to implement these data analytics project ideas for students. Using machine learning and python, you’ll learn how to predict customer churn and economic trends.
2. Fake News Detection Software
Do you encounter fake news often?
According to a Statista survey, over 52% of Americans feel many online news websites regularly push out fake news. Fake news entails articles with inaccurate facts and figures, and those deliberately created to mislead the audience.
It consequently becomes difficult to trust any information you find online. That’s why your data analytics final year project ideas could include a fake news detection system.
Using a K-Nearest Neighbour classifier, which is ideal in this case because the outcome of the algorithm doesn’t necessarily depend on one variable, you can lay the groundwork for your model. As an example, here’s a sample fake news detection model by IEEE.
This algorithm can then be trained by data scraping information in the world wide web to build a database against which you can verify suspicious articles, thereby classifying them as either fake or trustworthy. The classification process could be based on the source of the article and the length of the article, among other parameters.
3. Movie Recommendation System
Choosing the right film on a streaming platform can be challenging, because of the sheer volume of options at your disposal.
Statista reports that 2,734 movies were released between 2017 and 2020 in North America alone. This attests to how endless the choices are, which easily leads to you finding a movie outside your taste preferences, and consequently leaving a bad review on the platform and opting for another service altogether.
To solve selection issues, one of the big data analytics project ideas you could try out is a movie recommendation system.
We’ll focus on two techniques, namely:
- User-based filtering
- Collaborative filtering
User-based filtering entails building an algorithm to recommend new movies to your users, depending on past data about similar items. In other words, your system would recommend similar genre movies to viewers.
Alternatively, you could go with an item-based collaborative filtering algorithm, which reverses this process. Using datasets about user ratings, your system would recommend movies according to past preferences of users with similar review habits. These data science courses will help you get started on your movie recommendation system.
Some of the courses will show you how to build the project from scratch, and even offer data sets you could use for your movie recommender.
4. AI-Powered Analytics Chatbot
Modern customer service offers excellent data analysis project ideas.
If you’ve ever made an inquiry to a business after-hours on the verge of a public holiday, then you know the pain of having to wait days before getting a response to your urgent request. A Statista survey finds that 12% of poor customer service is down to a lack of speed.
By building your own chatbot, you can improve customer satisfaction for business owners. To create a bot that can handle unstructured data, you could use the Seq2seq approach for your natural language processing. This algorithm implores a recurrent neural network to inform the next step based on the context of the first.
Using SQL language, you can connect your bot to question-answer pairings to offer appropriate responses when prompted.
These artificial intelligence courses can help you build a chatbot quickly and easily. If you aren’t too keen on the coding work involved in creating such a conversational AI, some of these courses include no-coding data analytics project ideas for beginners.
5. Stock Market Prediction Application
The stock market is a very volatile field.
Stock prices change every day, and it’s easy for you to bank on a stock that’s doing well one day, only to see it drastically plummet the very next day. Consequently, traders are always looking for a better way to anticipate trends and inform investment decisions.
An AI-powered stock market prediction app is one of the best data analytics project ideas for students, as it is very applicable in this trillion-dollar industry.
Basically, you’ll be building a program around an LSTM neural network using various data points from stock market websites to power your model. Afterward, you can take real-world datasets about specific stock exchanges, which you can easily find online, and run them through your program to generate trading predictions.
Try out these amazing TensorFlow courses to start building your reliable stock market app today, and get other valuable data analysis project ideas for students. You’ll learn how to build a simple stock market app for day trading based on daily volume exchanges, among other key factors.
6. Credit Card Fraud Detection
Have you ever experienced credit card fraud?
There were over 459,297 cases of credit fraud in 2020, with the resulting losses reaching more than $28.65 billion worldwide according to The Nelson Report. With businesses of all kinds affected, prioritizing data analytics project topics to solve this could be highly rewarding.
If you take up a credit card fraud detection system, you’ll be able to enhance your portfolio to work for financial institutions.
The first step entails building a training database for your machine learning algorithm, involving information on fraud risk scores from sources like MicroBilt. Using this data, the model can predict the likelihood of a fraudulent transaction. In addition, your algorithm could work on conditional settings e.g. SSN matches, for instance, to verify transactions.
Here are some business analytics courses to enact these data analysis project ideas for students. One of them covers how you can analyze credit transactions to not only detect fraud but also use predictive analytics to anticipate buying patterns.
7. Weather Prediction App
The weather impacts every sphere of our lives today.
With inaccurate weather forecasts, farmers wouldn’t know how to adjust their farming techniques. What’s more, air traffic control teams would miss hazardous conditions, leading to unplanned redirects and even accidents.
A weather prediction app can help you solve problems for the transport, agricultural and military sectors. That is why it’s among the most in-demand data analytics project ideas.
First, you’ll need to find a reliable data source for your model. Some great and free options include OpenWeatherMap API, which collects meteorological data from more than 400,000 weather stations worldwide.
Panda is an excellent python library option that you could use for data processing and interacting with your database. Geolocation features can further help you provide app users with specific location-based information. If you’d like to get a move on your weather prediction mobile app, these Android app development courses will show you the ropes.
The classes mostly focus on Kotlin, which enables you to set up an application development environment with little to no coding background.
8. Sentiment Analyzer Project
Sentiment analysis offers a solid way for businesses to gauge brand perception.
This is becoming increasingly important given that customer experience (CX) is where most business competition is today. Findings from Gartner’s customer experience survey further establish this, given that 66% of marketers today believe CX is a huge differentiating factor.
A sentiment analyzer is among excellent data analytics final year project ideas, as you can appeal to many businesses that prioritize the customer experience.
You can build a rule-based system that uses natural language processing techniques like parts-of-speech tagging and tokenization to identify negative words in textual data. Alternatively, you can save yourself the work of crafting rules by using machine learning classifiers, which work on text feature extraction to identify tone.
To get a clearer idea of how to make it all work, these deep learning tutorials can surely prove useful.
They cover key concepts on recursive neural networks, which offer a great building block for your sentiment analysis model.
9. Flight Delay Prediction Model
Flight delays impact everyone involved in the industry.
The US Department of Transportation estimates that close to 16% of flights have been delayed so far in 2021. For passengers, it means not getting to appointments on time. The consequences for airlines, on the other hand, are tainted brand reputation and churn while air traffic controllers have to rework complex data systems to fit new schedules.
An online analytical processing (OLAP) cube is an excellent option to base your flight delay production model on and solve these challenges.
OLAP enables you to consider multiple data sources and clean the data in a single warehouse.
Speaking of which, Apache Spark is an excellent option for data cleaning in this case and you could use readily available Amadeus flight status datasets as your source. You can then build a qualitative prediction model on AWS SageMaker, for example.
To get a better understanding of Sagemaker, these AWS courses can be of huge assistance. Amazon Web Services supports many top educational and government agencies today, and these classes include many data analytics project ideas for beginners to improve your job market appeal.
10. Market Basket Analysis
For a retailer, convincing your customer to make an additional purchase is far from easy.
A lot of variables factor into the equation, from preferences to time of day. Without proper data analytics, it’s hard to recommend a product that appeals to your market. In fact, it is the case today that 51% of customers who receive product recommendations end up not buying suggested items.
A market basket analysis is among excellent data analysis project ideas to resolve this by personalizing recommendations to ignite sales.
This market basket analysis project is basically a product recommendation system that provides buyers with additional sales offers they’re likely to act on. It works on historical purchase data about previous buyers, then recommends items to your new buyer based on similar patterns, mostly using If-Then, probabilistic scenario rules.
For instance, if most of your customers buy product A then B, any time a purchase occurs for A, your conditional algorithm automatically recommends B.
To get a head start on this project, check out these SQL courses on Udemy. You’ll get to learn marketing analytics, involving product abandonment so you can better create an effective product recommendation system.
Are you ready to start your data analytics project?
A lack of clarity is typically the enemy when pondering the way forward for your project.
If you have little idea about your end product, you may find yourself starting on a project and abandoning it midway when it becomes unattainable. With these proven data analytics project ideas for final year students, you can make a successful project to impress your examiners and even prospective employers.
To build up underlying knowledge to power through your data analytics project, consider these incredible algorithm and data structure courses on Coursera.
These classes contain easy approaches to analyzing and developing various algorithms. They also offer valuable pointers on what and how to use various algorithm-building resources.