Semester | Subjects | Practicals/Labs |
---|---|---|
Semester 1 | Introduction to Data Analytics, Mathematics for Data Science, Programming Fundamentals, Communication Skills | Programming Fundamentals Lab, Communication Skills Lab |
Semester 2 | Database Management Systems, Data Structures, Statistical Methods for Data Analysis, Environmental Studies | Database Management Systems Lab, Data Structures Lab |
Semester 3 | Operating Systems, Object-Oriented Programming, Data Visualization, Business Intelligence | Object-Oriented Programming Lab, Data Visualization Lab |
Semester 4 | Machine Learning, Web Technologies, Big Data Analytics, Elective I | Machine Learning Lab, Web Technologies Lab |
Semester 5 | Cloud Computing, Data Mining, Elective II, Elective III | Data Mining Lab, Project Work I |
Semester 6 | Internet of Things (IoT), Elective IV, Elective V | IoT Lab, Major Project |
Module | Important Topics |
---|---|
Introduction to Data Analytics | Basics of Data Analytics, Data Types, Data Analytics Lifecycle |
Programming for Data Analytics | Python/R Programming, Data Structures, Control Structures |
Data Management and Manipulation | SQL for Data Analytics, Data Cleaning, Data Manipulation with Pandas |
Statistical Methods for Decision Making | Descriptive Statistics, Inferential Statistics, Hypothesis Testing |
Data Visualization | Principles of Data Visualization, Using Matplotlib and Seaborn, Dashboards |
Machine Learning | Supervised Learning, Unsupervised Learning, Model Evaluation |
Big Data Technologies | Introduction to Big Data, Hadoop Ecosystem, Spark for Big Data |
Business Intelligence and Applications | BI Concepts, Tools for BI, Applications of Data Analytics in various domains |