Course Overview

What You Learn in BCA Data Analytics Course

This program is a mix of core computer science, analytics tools, AI/ML concepts, and real-world data applications, offered over six semesters.

Semester-wise Overview

Semester I

• Fundamentals of Information Technology
• Programming in C
• Computational Mathematics
• Office Automation (MS Word, Excel, PowerPoint, Access)
• C Programming Lab
• Focus: Basic computing, problem-solving, and programming foundations.

Semester II

• Data Structures using C
• Database Management Systems (SQL & PL/SQL)
• Computer Organization & Architecture
• DBMS & Data Structure Labs
• Focus: Data storage, manipulation, and computer internals.

Semester III

• Operating Systems
• Object-Oriented Programming using Java
• Computer Networks
• Java Lab, OS Lab
• Electives: Digital Marketing / Web Content / DevOps
• Focus: System-level understanding and object-oriented programming.

Semester IV

• Python Programming
• Statistical Computing using R
• Data Warehousing & Data Mining
• Python Lab, Data Analytics Lab
• Elective: Optimization / Internet Basics / OOAD
• Data Analytics using Excel (Compulsory)
• Focus: Key analytical tools (Python, R, Excel), mining and storing data.

Semester V

• Software Engineering
• Artificial Intelligence
• Business Intelligence and Analytics
• Web Development
• Machine Learning
• Design Analysis and Algorithms
• Labs: AI/ML Lab, Web Dev Lab, Algorithms Lab
• Data Visualization using Power BI & Tableau (Compulsory)
• Focus: Building AI/ML solutions, business insights, visualizations.

Semester VI

• Natural Language Processing
• Big Data Analytics
• Multivariate Data Analysis
• Cybersecurity Principles
• Project Work (Major Capstone Project)
• Focus: Advanced analytics, unstructured data, big data, final integration via project.

Tools & Technologies You Learn

• Languages: C, Java, Python, SQL, R
• Analytics Tools: Excel, R, Power BI, Tableau
• Databases: SQL, PL/SQL, Access
• Frameworks: Scikit-learn, Pandas, Matplotlib, NumPy
• Web Tech: HTML, CSS, JavaScript (via Web Development)
• Platforms: MS Office, Oracle, MySQL

Skills & Career Readiness

By the end of the program, a student can:

• Analyze and visualize structured and unstructured data.
• Build machine learning models.
• Use tools like Excel, R, Tableau, Power BI for dashboards and reporting.
• Develop AI applications.
• Create real-time web-based data-driven projects.
• Apply statistical methods to real-world problems.

Career Paths:

• Data Analyst
• Business Intelligence Developer
• Junior Data Scientist
• AI/ML Developer
• Web/Data App Developer
• BI Consultant