Program Description

This course is designed to provide business leaders with a comprehensive understanding of artificial intelligence and its strategic applications. By the end of this course, participants will be equipped with the knowledge and skills to effectively integrate AI into their organizations, enhancing decision-making and operational efficiency. The objectives of this course are structured to ensure a solid grasp of AI fundamentals, practical applications, and ethical considerations. The specific objectives of the course are as follows:

  • To explain the Evolution, Fundamentals and Economics of Artificial Intelligence (AI)
  • To explain the role of AI systems as agents 
  • To make use of RPA concepts in various domains
  • To distinguish appropriate machine learning and deep learning techniques to solve business problems
  • To appraise the ethical perspectives while developing AI applications

Registration open for Batch 2

Key Highlights

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Gain a Strategic AI Perspective – Understand the transformative power of AI and how it can drive business innovation and efficiency.

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Enhance Decision-Making with AI – Learn to integrate AI-driven insights into business strategies for smarter, data-backed decisions.

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Optimize Business Operations – Leverage AI tools and techniques to streamline processes, enhance productivity, and reduce operational inefficiencies.

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Navigate Ethical & Risk Considerations – Develop a responsible approach to AI adoption by identifying and mitigating ethical risks and compliance challenges.

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Stay Ahead in a Competitive Market – Harness AI to gain a competitive edge, unlocking new opportunities for business growth and digital transformation.

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Lead AI Implementation – Acquire practical skills to drive AI adoption within your organization, ensuring seamless integration into existing workflows.

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Expand Career Opportunities – Position yourself as a forward-thinking leader with AI expertise, opening doors to roles in AI strategy, business intelligence, and digital transformation.

Learning Format

Online

Duration

6 Months
3 hours on weekends

Certified by

IITM Pravartak Technologies Foundation
Technology Innovation Hub (TIH) of IIT Madras and
eduXLL

Program Fee

INR 60,000 + 18% GST

Program Description

Program Brochure

Education Qualification

This course is designed for managers, business leaders, and professionals who want to integrate AI into their organizations to enhance productivity, optimize processes, and stay competitive in the evolving market.

Suggested Prerequisites

No specific technical background is required, but familiarity with business operations and interest in AI applications will be helpful for participant.

Teaching Hours

60 Hours

Lead Faculty

DR. VANDANA SRIVASTAVA
Ph.D. (Jamia Millia Islamia, Delhi)
M.Tech (Computer Applications), IIT- Delhi
M.Sc (Physics), Lucknow University 

Learning Module

•    What is AI? (Defining AI, Machine Learning, Deep Learning, and Generative AI in a business context)
•    Historical evolution of AI and its current state
•    Key AI terminology for managers (algorithms, models, data, training, bias, ethics)
•    Business Impact of AI
•    AI strategy and Vision

•    AI systems as Agents
•    Searches and their role in AI 
•    Understanding Uninformed, Heuristic and Adversarial Search

•    Understanding different types of data (structured, unstructured, real-time)
•    Importance of data quality, privacy, ethics and governance
•    Basic Data Analysis and Visualization (Hands-on with Excel & simple dashboards using Power BI or Tableau)
•    Introduction to SPSS for Business Insights

•    Core Concepts of Machine Learning - Supervised vs. Unsupervised Learning
•    Regression (predicting continuous values, e.g., sales forecasting), Classification (categorizing data, e.g., customer churn prediction) and Clustering (identifying natural groupings, e.g., customer segmentation) using easy to use (No code/ Low Code) tools such as SPSS (Note: Focus on interpreting SPSS outputs rather than complex statistical modeling)

•    Basic concepts
•    Classification
•    Artificial Neural Networks

•    Learning Association
•    Clustering

•    Concept
•    Applications

•    Evolution of Workforce Dynamics
•    Impact on Employment



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