Top 12 Data Science Projects For Final Year 2024

Data Science Projects For Final Year

Welcome to the Top 12 final-year data science project for 2024. We will look into the world of data, aiming to extract valuable insights and solutions. Focused on a real-world challenge, we employ cutting-edge techniques to unravel patterns and trends. Join us on this journey where data transforms into knowledge, paving the way for informed decision-making.

What is Data Science?

Data Science is a discipline that consists of domain expertise, programming skills, and knowledge of mathematics and statistics to get meaningful insights from data. These top 12 Data Science Projects are developed from insights based on numbers, statistics, and trends from data that will be used to make decisions for achieving a business goal.

What are the Top 12 Data Science Projects?

1. Student Placement Prediction using Machine Learning

The main goal of the project is to check the previous year’s student’s historical data and also to predict the placement possibilities of the current students. This project helps to increase the placement percentage of the institutions with the help of Machine Learning Algorithms.

2. Text Summarization using NLP | Machine Learning

The main purpose of this project is to know the concepts of natural language processing (NLP) and then to make a tool for text summarization. The manual work has been removed as the issues related to automatic summarization are rising. This project will focus on creating a tool that will summarize the document automatically.

3. Heart Disease Deduction using Big Data using ML

This project will allow us to make a model for getting the correct prediction of heart disease problems regarding healthcare applications. Through this, it will be more easy to outline the health care big data. Hence, it will reduce the consumption time along with the efficiency of data on heart disease. Due to this, it will show good performance in heart disease prediction.

4. Diabetics Prediction using Machine Learning

We’re using a special dataset about people’s health to figure out who might get diabetes soon. We’re using a computer program called Python along with some smart tools like machine learning and pandas to help us. First, we check the data to see how age, gender, and symptoms connect to diabetes.

Then, we clean up the data to make sure it’s good and ready. Next, we pick out the important things that help us predict diabetes. After that, we teach our computer model using some data, and we test how good it is.

We make cool graphs to show the patterns in the data that are linked to diabetes. Our main goal is to predict who might get diabetes in the next five years, so we can help them stay healthy and avoid problems. It’s like giving doctors a heads-up to keep everyone safe and well.

5. Employee Attrition with the Machine Learning

Several employees will work in the company. Many factors will affect the employee number in a company. Another important factor that we have to consider is the need to have potential employees in an organization.

6. Smart Farming Using Machine Learning Algorithms

For this project, we need to make a Machine Learning Model for Smart Farming. Additionally, we can do Smart Farming Prediction and this suggestion can be done with the help of Space Vector Modulation Classification and Neural Network Algorithm.

7. Churn Modelling Analysis with Deep Learning | Machine learning

Churn Analysis is considered the most used analysis in the Subscription Oriented Industries order to check customer behaviors to predict the customers who thought of leaving the service agreement from the company.

Therefore, the proposed model’s first classes will churn the customer data with the help of classification algorithms. The Random Forest and Decision Tree algorithm will do good performance with 90.44 % correctly classified instances.

8. Bitcoin Price Prediction Using Machine Learning

The main goal of the project is to know the bitcoin with the Machine Learning Algorithms. We know that the two models will be based on the gradient boosting decision trees and are designed on the long short-term memory recurrent neural networks. Furthermore, they will build investment portfolios according to the predictions and then will compare the performance with the return on investment.

9. Cyber Threat Analysis On Android Apps using Machine Learning

Security Solutions, statistics analysis, dynamic analysis, and artificial intelligence were put forward by researchers and developers to stop malware attacks. However, data science has become an important field in cybersecurity as the analytical model will help in the discovery of insights that can further help to know threats. Therefore, we can monitor cyber threats with the help of two techniques , static analysis and dynamic analysis.

10. Student Performance Prediction using Machine Learning

The main objective of this framework is to combine the demographic and study-related attributes along with the educational psychology field through the psychological characteristics of the student. We have chosen the most important attributes depending on the rationale and correlation with academic performance after checking the survey.

11. Tkinter Chatbot Application using NLP

We’re using a computer program called Python to look at health information from a group called Prime Indians. This info includes ages, genders, and symptoms related to diabetes. We’re making two sets of data, one for learning and one for testing.

Our big goal is to predict if someone might get diabetes in the next five years. We’re also turning the information into easy pictures to see patterns better. This helps us figure out who might need extra help to stay healthy and avoid diabetes. It’s like using smart technology to make predictions and keep people well.

12. Rainfall Prediction with the Machine Learning

Rainfall Prediction is used to give a critical analysis and feedback on the latest mining techniques. The published papers from 2013- 2017 in the online search libraries are being considered for the study.

Conclusion

To conclude, this will let you know more about the data science projects required for final-year students. Here, we have discussed the top 12 data science projects that can further enable them to perform well in their career ahead. Moreover,adding these projects in the resume will be more beneficial for your data science career

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