S01710

Artificial Intelligence for Senior Leaders (Batch-1)

Venue/Deadlines Program Dates Program Fees
Venue : IIMB Campus
Early Bird Discount Date : 13 May,2024
Last date for registration: 24 May,2024

Start Date : 03 June 2024
End Date : 05 June 2024

Residential Fee(excluding GST) :  Rs. 1,14,000
Residential Early Bird Fee(excluding GST) :  Rs. 102,600
Non-Residential Fee(excluding GST) :  Rs. 99,000
Non-residential Early Bird Fee(excluding GST) :   Rs. 89,100

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Important Deadlines

Venue : IIMB Campus
Early Bird Discount Date : 13 May,2024
Last date for registration: 24 May,2024
 

Who Should Attend

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

Pedagogy

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.

Contact Us

Ms. Preethi
Landline No.:+91-80-26993375
Mobile No. +91-8951974073
Email: preethi.s@iimb.ac.in

Mode
In-Person
Starting In
Apr-June
Level
Senior Leaders
Duration
Short Duration
International Travel
No
Alumni Status
No

Programme Overview
Artificial 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.

Content
Introduction to Artificial Intelligence (AI), Machine Learning (ML), Statistical Learning (SL) and Deep Learning (DL):
Intuitive understanding of AI; Relationship between AI, ML, SL and DL; Converting a business problem into an analytics problem, analytics problem-solving framework; Use cases of AI across different functional areas and different industries; Business process automation using AI.

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 Hospital
Improving 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 Objective
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:

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.

Key Benefits/Takeaways

The program would result in the following benefits:

  • Understanding of AI and its components.
  • Ability to develop an AI initiation strategy for the organization.
  • Understand various AI techniques and its applications across different functional areas and sectors.
  • Understanding of data governance and setting up AI team within the organizations.
  • Learn framework of developing deployable solution using AI

Participant Benefits

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

Programme Director

U Dinesh Kumar is a Professor of Decision Sciences and Chairperson of Data Centre and Analytics Lab (DCAL) at IIM Bangalore and holds a Ph.D. in Mathematics from IIT Bombay. Dr Dinesh Kumar introduced Business Analytics elective course in 2008 to the PGP students at IIM Bangalore and started one of the first certificate programmes in Business Analytics in India in 2010.

Dr Dinesh Kumar has over 20 years of teaching and research experience. Prior to joining IIM Bangalore, Dr Dinesh Kumar has worked at several reputed Institutes across the world including Stevens Institute of Technology, USA; University of Exeter, UK; University of Toronto, Canada; Federal Institute of Technology, Zurich, Switzerland; Queensland University of Technology, Australia; Australian National University, Australia and the Indian Institute of Management Calcutta.

Dr Dinesh Kumar has published more than 70 research articles in leading academic journals. Forty two of his case studies on Business Analytics based on Indian and multinational organizations such as Aavin Milk Dairy, Apollo Hospitals, Bigbasket, Bollywood, Flipkart.com, Hewlett and Packard, ISKCON, Jayalaxmi Agro Tech, Larsen & Toubro, Manipal Hospitals, Mission Hospital, Hindustan Aeronautics Limited, Indian Premier League, Reliance Retail, Shubham Housing Finance Limited, VMWare have been published at the Harvard Business Publishing’s case portal. His case studies are used by more than 220 Institutions across 61 countries across the world. He has authored 3 books, his recent book is titled, “Business Analytics – The Science of Data Driven Decision Making”, published by Wiley in 2017 which was an Amazon Best Seller.

Dr Dinesh Kumar has carried out predictive and prescriptive analytics consulting projects for organizations such as The Boston Consulting Group (India) Private Limited, Cavinkare, Hindustan Aeronautics Limited, Indian Army, Qatar Airways, Mission Hospital, Manipal Hospitals, Scalene Works, Wipro Limited, UNIBIC and the World Health Organization etc.

Dr Dinesh Kumar has conducted training program on Analytics for several companies’ companies such as Accenture, Aditya Birla Group, Ashok Leyland, Bank of America, Blue Ocean Market Intelligence, Cisco, Fidelity, Hindustan Aeronautics Limited, Honey Well, Infosys, ITC Info Tech, Ocwen financial Services and so on. Dr Dinesh Kumar conducts corporate training programme in Analytics and trained more than 1000 professionals in the field of analytics.

He is the founding president of the Analytics Society of India (ASI). Dr Dinesh Kumar was awarded the Best Young Teacher Award by the Association of Indian Management Institutions in 2003. He is listed as one of the top 10 analytics academics in India by the analytics India magazine. He is the governing council member of the Karnataka Government’s Centre of excellence for Data Science and Artificial Intelligence set up in Collaboration with NASSCOM.

Programme Charges

Programme Fee
INR 1,14,000/- Residential and INR 99,000/- Non -Residential (+ Applicable GST) per person for participants from India and its equivalent in US Dollars for participants from other countries.

Early Bird Discount
Nominations received with payments on or before 13-May-24 will be entitled to an early bird Discount of 10%.
Early Bird Fee (Residential) INR 1,02,600/-(+ Applicable GST)
Early Bird Fee (Non-Residential) INR 89,100/-(+ Applicable GST)

Group Discount
Group Discount of 5% percentage can be availed for a group of 3 or more participants when nominations received from the same organization.

Please Note
All enrolments are subject to review and approval by the programme director. Joining Instructions will be sent to the selected candidates 10 days prior the start of the programme.

  • The programme fee should be received by the Executive Education Office before the programme commencement date.
  • In case of cancellations, the fee will be refunded only if a request is received at least 15 days prior to the start of the programme.
  • If a nomination is not accepted,the fee will be refunded to the person/ organisation concerned.
  • A certificate of participation will be awarded to the participants by IIMB.

How To Apply for the Programme

Certificate Sample

 

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