IIM Amritsar Executive Master of Business Administration - Batch 06

• Managing People and Organizations
• Managerial Economics
• Financial Reporting and Analysis
• Quantitative Methods
• Essentials of Marketing

• Business Computing
• Managerial Communication
• Operations Research
• Advanced Marketing Management
• Macro Economics and Policy

• Talent Management & Development
• Legal Aspects of Business
• Business Research and Methods
• Operations Management
• Financial Management

• Competition and Strategy
• Consumer Behavior
• Elective*
• Elective*
• Security Analysis & Portfolio Management

In the real of advanced analytics, two transformative topics stand out: Big Data and Cloud Computing. Big Data involves the processing and analysis of immense volumes of structured and unstructured data, surpassing the capabilities of traditional database systems. It encompasses the challenges of capturing, storing, managing, and analyzing this data to extract valuable insights and patterns that can inform decision-making. Cloud Computing, on the other hand, revolutionizes data analytics by providing scalable and flexible computational resources over the internet. It offers a vast infrastructure capable of handling the computational demands of Big Data analytics, allowing for efficient storage, processing, and real-time analysis. The synergy of Big Data and Cloud Computing empowers organizations to derive actionable insights, enhance operational efficiency, and gain a competitive edge by leveraging the massive potential of data in a cost-effective and agile manner. The broad outline is as follows:

• Business Intelligence and Digital Transformation
• Business, Society and Public Policy
• Sales and Distribution Management
• Elective*
• Integrated Field Project/Elective

This module will cover supervised machine learning to train a model on a labeled dataset, where the model learns to predict output labels or values based on input features. During the training process, the model iteratively adjusts its parameters to minimize the difference between its predictions and the true labels provided in the training data. The key idea is to generalize this learned relationship to accurately predict new, unseen data. In other words, the model learns the mapping between inputs and outputs, enabling it to make informed decisions or predictions on future, unseen examples, making supervised learning a fundamental approach in solving a wide array of real-world problems. The broad outline of the module is as follows:

• Business Ethics
• Capstone Simulation
• Strategic Leadership and Decision
• Making
• Elective*
• Elective*
• Integrated Field Project/Elective

• Mergers, Acquisitions and Corporate Restructuring
• Financial Risk Management

• Product and Brand Management
• Business to Business Marketing
• Digitial Marketing
• Business Storytelling
• Marketing Analytics

• Industrial Relations and Labor Laws
• Compensation and Reward Management
• Negotiations and Conflict Management
• HR Analytics
• Managing Career Transitions
• International HRM

• Supply Chain Management and Logistics
• Services Operations
• Project Management
• Analytics for Cross-Functional Excellence
• Managing Digital Supply Chains

• Venture Capital and Entrepreneurship
• Design thinking
• Strategy Implementation
• Strategy thinking
• Advanced strategy: Creating and sustaining competitive advantage
• Games of Strategy
• Econometric Analysis of Data
• Time Series Analysis and Business Forecasting
• Behavioral Economics

• Visual Analytics
• Business Models for Digital Platforms 
• Artificial Intelligence and Machine Learning