Course Duration | Course Level | Fee | Mode of Study | Institute Type |
---|---|---|---|---|
3 Years | Undergraduate | Varies | Full-time | Public |
Semester 1 | Semester 2 | Semester 3 | Semester 4 | Semester 5 | Semester 6 |
---|---|---|---|---|---|
Introduction to Programming | Object-Oriented Programming | Data Structures and Algorithms | Database Management Systems | Machine Learning | Big Data Analytics |
Discrete Mathematics | Operating Systems | Software Engineering | Web Technologies | Deep Learning | Cloud Computing for Data Science |
Principles of Data Science | Statistics for Data Science | Linear Algebra for Data Science | Data Visualization | Natural Language Processing | Capstone Project |
Course | Description |
---|---|
Introduction to Data Science | Basics of Data Science, its importance, and applications. |
Programming for Data Science | Introduction to programming languages like Python and R that are essential for data analysis. |
Statistics for Data Science | Statistical methods and probability theory crucial for data analysis and interpretation. |
Data Visualization | Techniques and tools for visualizing data for easier understanding and insights. |
Machine Learning | Basics of machine learning algorithms and their application in data science. |
Big Data Technologies | Introduction to technologies and tools for handling and analyzing big data. |
Data Mining | Methods and techniques for extracting useful information from large datasets. |
Database Management | Principles of database management systems and their use in storing and retrieving data. |