Semester-wise Syllabus for a  BBA in Artificial Intelligence & Business Intelligence

Semester 1: Foundation Courses

1. Principles of Management

   • Introduction to management theories, functions, and organizational behavior.

2. Business Mathematics & Statistics

   • Mathematical and statistical concepts applied in business decision-making.

3. Financial Accounting

   • Basics of accounting, financial statements, and reporting.

4. Business Communication

   • Effective communication skills for professional environments.

5. Introduction to Artificial Intelligence

   • Overview of AI, history, applications, and basic concepts.

6. Computer Fundamentals & Office Automation

   • Basics of computer systems, software, and productivity tools.

Semester 2: Core Business & Computing Skills

1. Marketing Management

   • Fundamentals of marketing strategies, consumer behavior, and branding.

2. Business Economics

   • Micro and macroeconomic principles affecting businesses.

3. Database Management Systems (DBMS)

   • Introduction to SQL, relational databases, and data modeling.

4. Programming Fundamentals (Python/R)

   • Basics of programming for AI and data analysis.

5. Business Intelligence Concepts

   • Introduction to BI tools, dashboards, and data visualization.

6. Environmental Studies

   • Sustainability and corporate social responsibility.

Semester 3: Data & AI Foundations

1. Data Structures & Algorithms

   • Essential algorithms and data structures for AI applications.

2. Machine Learning Fundamentals

   • Supervised & unsupervised learning, regression, classification.

3. Business Analytics

   • Statistical tools, predictive modeling, and decision-making.

4. Financial Management

   • Capital budgeting, risk analysis, and financial planning.

5. Operations Research

   • Optimization techniques for business problems.

6. Ethics in AI & Business

   • Ethical considerations in AI deployment and data privacy.

Semester 4: Advanced AI & BI Techniques

1. Deep Learning Basics

   • Neural networks, CNNs, RNNs, and AI model training.

2. Big Data Analytics

   • Hadoop, Spark, and handling large datasets.

3. Natural Language Processing (NLP)

   • Text mining, sentiment analysis, chatbots.

4. Cloud Computing for Business

   • AWS/Azure, cloud-based AI solutions.

5. Digital Marketing & AI in Marketing

   • AI-driven customer insights, automation in marketing.

6. Project Management

   • Agile, Scrum, and AI project lifecycle.

Semester 5: Industry Applications & Specializations

1. AI in Finance & FinTech

   • AI in risk assessment, fraud detection, and algorithmic trading.

2. Supply Chain & AI Optimization

   • AI in logistics, demand forecasting, and automation.

3. Business Intelligence Tools (Power BI, Tableau)

   • Advanced visualization and reporting techniques.

4. Robotic Process Automation (RPA)

   • Automating business processes using AI bots.

5. Elective 1 (Choose one)

   • Healthcare AI / AI in HR / AI in E-commerce

6. Internship / Industry Project

   • Hands-on AI/BI project with industry collaboration.

Semester 6: Capstone & Research

1. AI Strategy & Business Transformation

   • Implementing AI in enterprises for competitive advantage.

2. Blockchain & AI Integration

   • Decentralized AI applications and smart contracts.

3. Research Methodology & Dissertation

   • Independent research project in AI/BI domain.

4. Entrepreneurship & AI Startups

   • Building AI-driven business models.

5. Elective 2 (Choose one)

   • Cybersecurity for AI / AI in IoT / Cognitive Computing

6. Final Project & Viva

   • End-of-program AI/BI solution demonstration.