Semester | Subjects |
---|---|
Semester 1 | Introduction to Data Science, Mathematics for Data Science, Programming Fundamentals, English Communication, Environmental Studies |
Semester 2 | Statistics for Data Science, Python Programming, Database Management Systems, Organizational Behavior, Elective I |
Semester 3 | Data Analysis and Visualization, Machine Learning I, Java Programming, Operating Systems, Elective II |
Semester 4 | Advanced Machine Learning, Big Data Analytics, Web Technologies, Professional Ethics, Elective III |
Semester 5 | Deep Learning, Cloud Computing for Data Science, Project Work I, Elective IV, Elective V |
Semester 6 | Capstone Project, Industry Internship, Elective VI, Elective VII |
Module | Important Topics |
---|---|
Introduction to Data Science | Basics of Data Science, Data Types, Data Science Lifecycle |
Programming for Data Science | Python/R Programming, Data Structures, Algorithms |
Mathematics for Data Science | Linear Algebra, Calculus, Statistics & Probability |
Data Management | Database Management, SQL, NoSQL, Data Warehousing |
Data Analysis | Data Preprocessing, Exploratory Data Analysis, Descriptive Statistics |
Machine Learning | Supervised Learning, Unsupervised Learning, Model Evaluation |
Deep Learning | Neural Networks, CNN, RNN, TensorFlow, Keras |
Data Visualization | Matplotlib, Seaborn, Tableau, Data Storytelling |
Big Data Technologies | Hadoop, Spark, Big Data Analytics |
Projects and Case Studies | Real-world Projects, Industry Case Studies |