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| Course Duration | Course Level | Course Tuition Fees | Mode of Study | Institute Type |
|---|---|---|---|---|
| 2 Years | Post Graduate | INR 3.5 Lakhs | Full Time | Private |
| Semester | Subjects/Topics |
|---|---|
| 1st Semester | Data Science Fundamentals, Data Analysis and Visualization, Database Management, Business Intelligence, Data Mining, Machine Learning, Big Data Analytics, Statistical Analysis, Data Warehousing, Data Modeling, Data Structures and Algorithms |
| 2nd Semester | Data Science in Practice, Advanced Data Analysis and Visualization, Advanced Database Management, Advanced Business Intelligence, Advanced Data Mining, Advanced Machine Learning, Advanced Big Data Analytics, Advanced Statistical Analysis, Advanced Data Warehousing, Advanced Data Modeling, Advanced Data Structures and Algorithms |
| 3rd Semester | Data Science in Action, Applied Data Analysis and Visualization, Applied Database Management, Applied Business Intelligence, Applied Data Mining, Applied Machine Learning, Applied Big Data Analytics, Applied Statistical Analysis, Applied Data Warehousing, Applied Data Modeling, Applied Data Structures and Algorithms |
| 4th Semester | Data Science in the Real World, Professional Data Analysis and Visualization, Professional Database Management, Professional Business Intelligence, Professional Data Mining, Professional Machine Learning, Professional Big Data Analytics, Professional Statistical Analysis, Professional Data Warehousing, Professional Data Modeling, Professional Data Structures and Algorithms |
| Topic | Description |
|---|---|
| Data Mining and Machine Learning | Exploring the fundamentals of data mining and machine learning, including supervised and unsupervised learning, predictive analytics, and data visualization. |
| Data Warehousing and Business Intelligence | Exploring the fundamentals of data warehousing and business intelligence, including data architecture, ETL, OLAP, and data visualization. |
| Data Science and Analytics | Exploring the fundamentals of data science and analytics, including data wrangling, predictive analytics, and data visualization. |
| Big Data Technologies | Exploring the fundamentals of big data technologies, including Hadoop, Spark, and NoSQL. |
| Data Governance and Security | Exploring the fundamentals of data governance and security, including data privacy, data protection, and data security. |
