AMPBA Curriculum

AMPBA
Curriculum
Cutting Edge Curriculum
The comprehensive AMPBA curriculum is a perfect blend of theory and practice offering a judicious mix of analytical skills, business knowledge, and a strategic perspective on the analytics industry. The curriculum is continuously and rigorously updated to bring cutting-edge learning tools and methods to the class. The combination of course modules and the industry-sponsored Capstone Project offers both exhaustive learning and real-world application across domains. In addition to the Capstone Project, students will be completing Foundation Projects too.
Bootcamp Modules
The knowledge of Python and R-programming is essential for AMPBA. Every student will have access* to four Bootcamp modules of asynchronous content, of which two modules will have built-in mandatory quizzes and exercises.
Foundational Courses
The Foundation Term courses covers probability, descriptive statistics, data collection and visualization foundations for analytics. Students need to attempt all four courses of the Foundation Term with a pass grade in all courses to proceed to Term 1.
Core Courses
These courses cover in-depth study in statistics, optimisation, forecasting, machine learning, AI, deep learning, GenAI, LLMs and other contemporary topics.
Application Courses
These courses teach the participants how to apply analytics & AI to different business domains such as marketing, finance, retail, supply chain, pricing, and more across industries. Students use analytical modeling techniques to solve business problems by applying them to data sets.
Experiential Course
The Foundation project and Capstone project teach participants about the life cycle of a project in analytics & AI and show them how to apply their skills from Core and Application courses to real business problems.
World Class Faculty
Our distinguished faculty comprises leading scholars, practitioners, and thought leaders who combine global expertise with Indian context to create knowledge that shapes academic theory, influences business practice, and drives policy innovation across sectors.
- Bootcamp Modules
- Introduction to Python
- Introduction to R-programming
- Introduction to SQL
- Introduction to Linear Algebra
- Mandatory to successfully complete two of the four Bootcamp Modules with asynchronous content before the Foundation Term.
- Introduction to Probability
- Descriptive Statistics using R
- Data Collection & Pre-Processing
- Data Visualization
- Students need to attempt all four courses and obtain a mandatory pass grade in all courses to proceed to Term 1.
- Statistical Analysis 1
- Big Data Management
- Optimization
- Data Engineering
- Machine Learning: Unsupervised Learning 1
- Statistical Analysis 2
- Machine Learning: Unsupervised Learning 2
- Machine Learning: Supervised Learning 1
- Advanced Optimization and Simulation
- Deep Learning
- Advanced Statistical Analysis
- Forecasting Analytics
- Machine Learning: Supervised Learning 2
- Natural Language Processing
- Network & Graph Analytics
- Contemporary Technologies
- Digital and Social Media Analytics
- Supply Chain and Retail Analytics
- Marketing and Customer Analytics
- Applications of AI
- Pricing & Demand Analytics
- Financial Analytics