Artificial Intelligence for Senior Leaders (Batch-12)
IIM Bangalore - Executive Education
Data Analytics
Partner Institution
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About Programme
Programme OverviewArtificial Intelligence (AI) has become a decisive technology for the growth of every organization. Sophistication in AI is expected to be the main differentiator between high-performing companies and low-performing companies. The use of AI and its components such as statistical, machine and deep learning are expected to increase the stakeholder value and customer experience and satisfaction. The algorithmic aspects of AI are available readily through many sources; however, many companies still struggle with adapting AI to the organization. For example, companies struggle to find answers to the following questions :
What constitutes an AI company?What should be the strategy for building an AI initiative within an organization? How to build an AI team? What problems can be solved using AI? Understate Generative AI and Its Applications.
Programme Content
Machine Learning: Supervised, Unsupervised and Reinforcement Learning Algorithms.AI/ML Model Development: Feature Extraction; Feature Engineering; Feature Selection; Model Selection and Model Deployment.
Introduction to Descriptive, Predictive and Prescriptive Analytics:Objectives of Descriptive Analytics: Storey telling using Data; Predictive Analytics Models: Regression, and Logistic Regression; Prescriptive Analytics: Linear Programming and Multi-Criteria Decision Making.
Cases:Package Pricing at Mission HospitalImproving Sales Conversion at Eureka Forbes Using Machine Learning Algorithms.
Setting up an AI team:Choosing the right team; roles and responsibilities; Organizational Structure: Centralized and Distributed Models; Key skill set; fresh hire vs internal training.
Analytics Technology Landscape:Choosing the right tools and platforms for development and deployment of AI based solutions.
Data Governance:Data Governance Framework; Data Privacy, Security, Quality and Responsibility; General Data Protection Regulation (GDPR);
AI Deployment:AI in sales and marketing: opportunity and sales conversion; channel optimization; customer lifetime value; AI in Operations: supply chain analytics; AI in Retail: Assortment planning, brand switching, promotion effectiveness; AI in Banking and Finance: Credit Rating
Programme Objective
Objectives of Descriptive Analytics: Storey telling using Data; Predictive Analytics Models: Regression, and Logistic Regression; Prescriptive Analytics: Linear Programming and Multi-Criteria Decision Making.
Cases:Package Pricing at Mission HospitalImproving Sales Conversion at Eureka Forbes Using Machine Learning Algorithms.
Setting up an AI team:Choosing the right team; roles and responsibilities; Organizational Structure: Centralized and Distributed Models; Key skill set; fresh hire vs internal training.
Analytics Technology Landscape:Choosing the right tools and platforms for development and deployment of AI based solutions.
Data Governance:Data Governance Framework; Data Privacy, Security, Quality and Responsibility; General Data Protection Regulation (GDPR);
AI Deployment:AI in sales and marketing: opportunity and sales conversion; channel optimization; customer lifetime value; AI in Operations: supply chain analytics; AI in Retail: Assortment planning, brand switching, promotion effectiveness; AI in Banking and Finance: Credit Rating
Program ObjectiveThis short-duration program is aimed at the managers who are currently leading and are likely to lead AI initiatives in the organization. The course covers aspects of the Organizational journey of AI transformation, data governance, data preparation for analytic model building and descriptive, predictive and prescriptive analytics. The objectives of the program are as follows:
Understand how to create a strategy for building AI initiatives within the organization with a special focus on the following:
Data governance strategy.
Technology and Platform Strategy
People and Skill Strategy
Learn to create a roadmap for an AI-first company.
Understand key factors that can lead to the success or failure of AI projects
Understand how to choose the right use cases and prioritize key AI project
Learn concepts and techniques in AI, such as statistical learning, machine learning, deep learning and Understand Generative AI and Large Language Models. Understand Generative Pre-Trained Transformer (GPT) and its business applications.
Learn tools and techniques of descriptive, predictive and prescriptive analytics
Understand the applications of supervised, unsupervised and reinforcement learning algorithms.
Understand what tasks can be automated using AI.
Understand data governance and data readiness for the application of AI.
Learn how an organization can build an AI team. Roles and responsibilities of AI team and hiring or training to build an AI team.
Learn about common mistakes while making AI transformation and how to avoid them
AI and society / responsible AI
How AI can be used or what are the different use cases in different industries.
This short-duration program is aimed at the managers who are currently leading and are likely to lead AI initiatives in the organization. The course covers aspects of the Organizational journey of AI transformation, data governance, data preparation for analytic model building and descriptive, predictive and prescriptive analytics. The objectives of the program are as follows:
Data governance strategy.
Technology and Platform Strategy
People and Skill Strategy
Learn to create a roadmap for an AI-first company.
Understand key factors that can lead to the success or failure of AI projects
Understand how to choose the right use cases and prioritize key AI project
Learn concepts and techniques in AI, such as statistical learning, machine learning, deep learning and Understand Generative AI and Large Language Models. Understand Generative Pre-Trained Transformer (GPT) and its business applications.
Learn tools and techniques of descriptive, predictive and prescriptive analytics
Understand the applications of supervised, unsupervised and reinforcement learning algorithms.
Understand what tasks can be automated using AI.
Understand data governance and data readiness for the application of AI.
Learn how an organization can build an AI team. Roles and responsibilities of AI team and hiring or training to build an AI team.
Learn about common mistakes while making AI transformation and how to avoid them
AI and society / responsible AI
How AI can be used or what are the different use cases in different industries.
Programme Audience
The program is designed for leaders with at least 10 years of experience who are either working in the field of AI or planning to set up AI team
The program will be driven by use cases from across different domains. The focus will be on strategic issues of AI with limited focus on hands-on experience.
As a participant of this Short Duration Programme, you will be able to enjoy some exclusive benefits other than the outcomes such as skills and knowledge enhancement and building specific competencies that can help shape your career growth.
Some of the exclusive benefits of attending this programme are listed below –
Receive Executive Education eNewsletters
Invitation to share articles to the EEP blog (subject to a shortlisting process
Participate in EEP webinars on various topics
Invitation to curated events and programs by the EEP office
