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, deep learning, NLP and AI.

Application Courses

These courses teach the participants how to apply data analytics 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 Courses

The Foundation project and Capstone project teach participants about the life cycle of a project in Data Science and show them how to apply their skills from Core and Application courses to real business problems.

 

*Access will be provided to the students after payment of Instalment-I fee.

*Some courses may undergo modification at the time of delivery.

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. 

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. 

Core Modules

 Statistical Analysis 1

 Big Data Management

 Optimization

 Introduction to Text Analytics

Advanced Modules

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

Application Modules

Digital and Social Media Analytics

Supply Chain and Retail Analytics

Marketing and Customer Analytics

Applications of AI

Pricing & Demand Analytics

Financial Analytics

Experiential Learning Modules

• Foundational Project

• Capstone Project.