| Semester | Subjects |
|---|---|
| Semester 1 | Introduction to Data Analytics, Mathematics for Data Science, Programming Fundamentals using Python, English Communication, Environmental Studies |
| Semester 2 | Database Management Systems, Advanced Python for Data Analytics, Probability and Statistics, Principles of Management, Indian Constitution |
| Semester 3 | Data Structures and Algorithms, Machine Learning Basics, Web Technologies, Business Analytics, Soft Skills Development |
| Semester 4 | Big Data Analytics, Advanced Machine Learning, Data Visualization Techniques, Financial Accounting, Entrepreneurship Development |
| Semester 5 | Cloud Computing for Data Analytics, Artificial Intelligence, Elective 1, Project Work - I, Internship |
| Semester 6 | Deep Learning, Elective 2, Project Work - II, Cyber Security Fundamentals for Data Analytics, Professional Ethics and Human Values |
| Course | Description |
|---|---|
| Introduction to Data Analytics | Basics of data analysis, including data types, data collection, and data preprocessing. |
| Programming for Data Science | Introduction to programming languages such as Python or R that are essential for data analysis and data science. |
| Database Management Systems | Understanding of how databases are designed, managed, and utilized for data storage and retrieval. |
| Data Mining | Techniques and tools for discovering patterns, anomalies, and associations in large datasets. |
| Machine Learning | Study of algorithms and statistical models that computer systems use to perform tasks without explicit instructions. |
| Big Data Technologies | Introduction to technologies and tools used to process and analyze large datasets (e.g., Hadoop, Spark). |
| Business Intelligence | Techniques for transforming raw data into meaningful and useful information for business analysis purposes. |
| Data Visualization | Techniques and tools for representing data visually to communicate information clearly and efficiently. |
