| Course Duration | Course Level | Tuition Fees | Mode of Study | Institute Type |
|---|---|---|---|---|
| 3 Years | Undergraduate | Varies by region and quota | Full-time | Private |
| Semester | Subjects |
|---|---|
| Semester 1 | Introduction to Data Science, Mathematics for Data Science, Programming Fundamentals using Python, Database Management Systems, English Communication Skills |
| Semester 2 | Statistics for Data Science, Data Structures and Algorithms, Object-Oriented Programming with Python, Operating Systems, Environmental Studies |
| Semester 3 | Machine Learning Basics, Web Technologies, Advanced Database Management Systems, Linear Algebra for Data Science, Business Communication |
| Semester 4 | Advanced Machine Learning, Big Data Analytics, Data Visualization Techniques, Elective I (Cloud Computing/ IoT/ Blockchain Technology), Research Methodology and Mini Project |
| Semester 5 | Deep Learning, Natural Language Processing, Elective II (Cyber Security/ Digital Image Processing/ Robotics), Internship/Project Work, Professional Ethics and Human Values |
| Semester 6 | Capstone Project, Elective III (Advanced Web Technologies/ Mobile Application Development/ Game Development), Industry Oriented Project Work, Seminar on Emerging Technologies, Comprehensive Viva |
| Course | Description |
|---|---|
| Programming Fundamentals | Introduction to programming concepts using languages like Python or Java. |
| Database Management Systems | Concepts of database architecture, SQL, and NoSQL databases. |
| Data Structures and Algorithms | Understanding of various data structures and algorithms for efficient data manipulation. |
| Mathematics for Data Science | Mathematical foundations including statistics, probability, and linear algebra. |
| Machine Learning | Basics of machine learning algorithms and their applications. |
| Data Visualization | Techniques for visualizing data using tools like Tableau or PowerBI. |
| Big Data Technologies | Introduction to big data concepts and technologies like Hadoop and Spark. |
| Deep Learning | Advanced machine learning concepts focusing on neural networks and deep learning. |
| Cloud Computing for Data Science | Utilizing cloud platforms for data storage, processing, and analysis. |
| Capstone Project | Practical project to apply data science concepts to real-world problems. |
