<h1 style="color: #2a4978; font-family: poppins; font-weight: 600">
 Semester 1 Syllabus
</h1>

 
 Core Courses:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Management Accounting:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Introduction to Accounting
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Cost-Volume-Profit Analysis
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Budgeting and Standard Costing
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Business Statistics:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Descriptive Statistics
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Probability Distributions
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Hypothesis Testing
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Marketing Management:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Marketing Environment
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Consumer Behavior
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Marketing Mix Strategies
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Organizational Behavior:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Foundations of Individual Behavior
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Group Dynamics
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Leadership
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Business Communication:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Communication Process
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Business Writing
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Presentation Skills
 </li>
 </ul>
 </li>
</ul>

 
 Business Analytics Specialization Courses:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Introduction to Business Analytics:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Overview of Business Analytics
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Data Types and Data Sources
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Analytics Tools and Techniques
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Data Management:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Database Management Systems
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Data Warehousing
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Data Quality and Governance
 </li>
 </ul>
 </li>
</ul>

<h1 style="color: #2a4978; font-family: poppins; font-weight: 600">
 Semester 2 Syllabus
</h1>

 
 Core Courses:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Financial Management:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Time Value of Money
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Capital Budgeting
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Working Capital Management
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Operations Management:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Process Design
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Supply Chain Management
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Inventory Management
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Human Resource Management:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Recruitment and Selection
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Training and Development
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Performance Management
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Business Economics:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Microeconomic Principles
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Macroeconomic Indicators
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Market Structures
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Research Methodology:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Research Design
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Data Collection Methods
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Statistical Analysis
 </li>
 </ul>
 </li>
</ul>

 
 Business Analytics Specialization Courses:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Data Visualization:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Principles of Data Visualization
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Visualization Tools (e.g., Tableau, Power BI)
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Creating Effective Dashboards
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Predictive Analytics:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Regression Analysis
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Time Series Analysis
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Machine Learning Fundamentals
 </li>
 </ul>
 </li>
</ul>

<h1 style="color: #2a4978; font-family: poppins; font-weight: 600">
 Semester 3 Syllabus
</h1>

 
 Core Courses:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Strategic Management:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Industry Analysis
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Competitive Advantage
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Strategic Planning
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Business Law:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Contract Law
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Company Law
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Intellectual Property Rights
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Entrepreneurship:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Business Plan Development
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Venture Capital
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Startup Management
 </li>
 </ul>
 </li>
</ul>

 
 Business Analytics Specialization Courses:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Data Mining:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Clustering Techniques
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Classification Techniques
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Association Rule Mining
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Big Data Analytics:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Introduction to Big Data
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Hadoop and Spark
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 NoSQL Databases
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Optimization Techniques:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Linear Programming
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Integer Programming
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Simulation
 </li>
 </ul>
 </li>
</ul>

<h1 style="color: #2a4978; font-family: poppins; font-weight: 600">
 Semester 4 Syllabus
</h1>

 
 Core Courses:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 International Business:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Global Trade
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Foreign Exchange
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 International Marketing
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Ethics in Business:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Ethical Theories
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Corporate Social Responsibility
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Business Ethics Dilemmas
 </li>
 </ul>
 </li>
</ul>

 
 Business Analytics Specialization Courses:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Advanced Predictive Analytics:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Advanced Regression Models
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Machine Learning Algorithms (e.g., SVM, Random Forest)
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Model Evaluation and Selection
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Business Intelligence:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 BI Tools and Platforms
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Data-Driven Decision Making
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Performance Measurement
 </li>
 </ul>
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Analytics Project Management:
 
 <ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Project Planning
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Team Management
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Communication and Reporting
 </li>
 </ul>
 </li>
</ul>

 
 Capstone Project:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 Apply business analytics techniques to solve a real-world business problem.
 </li>
</ul>

Image 4

```markdown
Choosing between an MBA in Business Analytics and an MBA in Finance can be a tough decision for Indian students. Both offer promising career paths, but cater to different interests and skill sets. Let's break down the key differences:


 
 MBA in Business Analytics:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Focus:
 
 Data-driven decision making. You'll learn to analyze large datasets, identify trends, and use statistical models to solve business problems.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Skills:
 
 Data mining, statistical analysis, machine learning, data visualization (Tableau, Power BI), programming (Python, R).
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Career Paths:
 
 Data Analyst, Business Intelligence Analyst, Data Scientist, Marketing Analyst, Consultant.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Ideal for:
 
 Students with a strong aptitude for mathematics, statistics, and computer science. Those who enjoy problem-solving and finding insights from data.
 </li>
</ul>

 
 MBA in Finance:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Focus:
 
 Financial management, investment analysis, and corporate finance.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Skills:
 
 Financial modeling, investment banking, portfolio management, risk management, financial accounting.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Career Paths:
 
 Financial Analyst, Investment Banker, Portfolio Manager, Corporate Treasurer, Management Consultant (Finance).
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Ideal for:
 
 Students with an interest in financial markets, investment strategies, and corporate financial planning.
 </li>
</ul>

 
 Here's a table summarizing the key differences:
 

<table>
 <thead>
 <tr>
 <th>
 Feature
 </th>
 <th>
 MBA in Business Analytics
 </th>
 <th>
 MBA in Finance
 </th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td>
 
 Core Focus
 
 </td>
 <td>
 Data analysis and interpretation
 </td>
 <td>
 Financial management and investment
 </td>
 </tr>
 <tr>
 <td>
 
 Key Skills
 
 </td>
 <td>
 Data mining, statistical modeling, data visualization
 </td>
 <td>
 Financial modeling, portfolio management, risk management
 </td>
 </tr>
 <tr>
 <td>
 
 Typical Roles
 
 </td>
 <td>
 Data Analyst, Data Scientist, Business Intelligence Analyst
 </td>
 <td>
 Financial Analyst, Investment Banker, Portfolio Manager
 </td>
 </tr>
 <tr>
 <td>
 
 Ideal Student
 
 </td>
 <td>
 Analytical, detail-oriented, enjoys working with data
 </td>
 <td>
 Interested in financial markets, strategic thinking
 </td>
 </tr>
 </tbody>
</table>

 
 Which one should you choose?
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 If you enjoy working with numbers, analyzing data, and uncovering insights, an MBA in Business Analytics might be a better fit.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 If you are passionate about financial markets, investment strategies, and corporate finance, an MBA in Finance could be the right choice.
 </li>
</ul>

 Consider your strengths, interests, and career goals when making your decision. Research the specific curriculum of each program to ensure it aligns with your aspirations. Many Indian B-schools now offer specialized MBA programs in both Business Analytics and Finance, so you'll have plenty of options to choose from.
```

MBA in Business Analytics vs. MBA in Finance: Which is Right for You?

```markdown
For Indian students aiming for a career in data, the choice between an MBA in Business Analytics and a PGDM (Post Graduate Diploma in Management) in Data Science can be confusing. While both focus on data, they differ in scope and approach.


 
 MBA in Business Analytics:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Focus:
 
 Applying data analysis to solve business problems and improve decision-making. It combines business acumen with data science techniques.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Curriculum:
 
 Includes core MBA subjects like marketing, finance, and operations, along with specialized courses in data mining, statistical modeling, and data visualization.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Target Audience:
 
 Professionals with some work experience who want to leverage data to advance their careers in management roles.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Career Goals:
 
 Leadership positions, consulting roles, and strategic decision-making roles where data insights are crucial.
 </li>
</ul>

 
 PGDM in Data Science:
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Focus:
 
 Deep dive into the technical aspects of data science, including machine learning, artificial intelligence, and big data technologies.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Curriculum:
 
 Heavily focused on programming (Python, R), statistical modeling, machine learning algorithms, and data engineering.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Target Audience:
 
 Fresh graduates or professionals with a strong technical background who want to become data scientists or data engineers.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 
 Career Goals:
 
 Data Scientist, Machine Learning Engineer, Data Engineer, AI Specialist.
 </li>
</ul>

 
 Key Differences Summarized:
 

<table>
 <thead>
 <tr>
 <th>
 Feature
 </th>
 <th>
 MBA in Business Analytics
 </th>
 <th>
 PGDM in Data Science
 </th>
 </tr>
 </thead>
 <tbody>
 <tr>
 <td>
 
 Core Focus
 
 </td>
 <td>
 Business problem-solving using data
 </td>
 <td>
 Technical expertise in data science and AI
 </td>
 </tr>
 <tr>
 <td>
 
 Curriculum
 
 </td>
 <td>
 Business + Data Science
 </td>
 <td>
 Primarily Data Science and related technologies
 </td>
 </tr>
 <tr>
 <td>
 
 Target Audience
 
 </td>
 <td>
 Experienced professionals seeking management roles
 </td>
 <td>
 Fresh graduates or technical professionals
 </td>
 </tr>
 <tr>
 <td>
 
 Career Goals
 
 </td>
 <td>
 Management, Consulting, Strategic Decision-Making
 </td>
 <td>
 Data Science, Machine Learning, AI Engineering
 </td>
 </tr>
 </tbody>
</table>

 
 Which is the right choice for you?
 

<ul>
 <li style="color: black; font-family: poppins; font-weight: 400">
 If you have a business background and want to use data to improve business outcomes, an MBA in Business Analytics is a good fit.
 </li>
 <li style="color: black; font-family: poppins; font-weight: 400">
 If you are passionate about the technical aspects of data science and want to build AI-powered solutions, a PGDM in Data Science is a better choice.
 </li>
</ul>

 Consider your career aspirations, technical skills, and desired level of technical depth when making your decision. Research the specific curriculum and faculty of each program to ensure it aligns with your goals. Many top institutes in India offer both programs, so compare them carefully.
```

MBA in Business Analytics vs. PGDM in Data Science: Understanding the Differences

An MBA in Business Analytics equips you with skills in data analysis, business strategy, and decision-making. Ideal for professionals seeking leadership roles.

MBA with Specialization in Business Analytics

Course Comparision

Curriculum