Semester | Subjects | Topics |
---|
Semester 1 | Introduction to Data Analytics, Programming Fundamentals, Mathematics for Data Science, Communication Skills | Basics of Data Analytics, Programming Concepts (Python/Java), Algebra, Statistics, Effective Communication |
Semester 2 | Database Management Systems, Data Structures, Advanced Mathematics, Environmental Studies | SQL, NoSQL, Trees, Graphs, Calculus, Probability, Environmental Awareness |
Semester 3 | Operating Systems, Object-Oriented Programming, Data Visualization, Business Intelligence | Linux, Windows, OOP Concepts, Tableau, Power BI, Market Strategies |
Semester 4 | Machine Learning, Web Technologies, Statistical Methods for Data Analysis, Elective I | Supervised Learning, HTML, CSS, JavaScript, Hypothesis Testing, Regression Analysis |
Semester 5 | Big Data Analytics, Cloud Computing, Elective II, Project Work I | Hadoop, Spark, AWS, Azure, Topic based on Elective, Research Methodology |
Semester 6 | Deep Learning, Data Security and Privacy, Elective III, Project Work II | Neural Networks, GDPR, Data Protection Laws, Topic based on Elective, Final Project Presentation |
This table is a generic template and should be adapted to match the specific curriculum offered by the Poddar Group of Institutions for their BCA in Data Analytics course. Electives and specific topics can vary widely between institutions.