Course Duration | 3 Years |
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Course Level | Undergraduate |
Course Tuition Fees | Varies by Program |
Mode of Study | Full Time |
Institute Type | Public University |
Course | Description |
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Introduction to Data Science | Foundational principles of data science, including basic data handling, visualization, and analysis. |
Programming for Data Science | Programming languages such as Python or R for data manipulation and analysis. |
Statistics for Data Science | Statistical methods and probability theory essential for data analysis. |
Machine Learning | Introduction to machine learning algorithms and their application in data science. |
Data Mining | Techniques for discovering patterns and knowledge from large datasets. |
Big Data Technologies | Tools and technologies for processing and analyzing big data (e.g., Hadoop, Spark). |
Data Visualization | Techniques for visualizing and communicating data insights. |
Database Management | Principles of database systems and management for structured and unstructured data. |
Business Intelligence | Using data analysis in business decision-making processes. |
Capstone Project | Practical project to apply data science skills to real-world problems. |