Programme Parameters
Advanced Postgrad
3 Weeks (30 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
AI Awareness for Executives is a non-technical, high-impact leadership program designed to introduce the core concepts of Artificial Intelligence, its disruptive potential across industries, and the ethical, strategic, and operational decisions leaders must make. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
AI Awareness for Executives is a non-technical, high-impact leadership program designed to introduce the core concepts of Artificial Intelligence, its disruptive potential across industries, and the ethical, strategic, and operational decisions leaders must make.
📋 Course Objectives
1. Apply AI Enablement methods to authentic research and industry problems.
2. Build a defensible project you can showcase to supervisors, reviewers, or employers.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in AI Enablement
• R&D engineers and working professionals applying AI Enablement in industry
• Academics and educators building research or teaching capacity in AI Enablement
🚀 Key Learning Outcomes
• A demonstrable AI Enablement project for your research or industry portfolio.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Understanding AI Fundamentals
Explore the basics of AI, including rule-based systems and machine learning. • Discover categories of AI, such as predictive models, generative AI, and autonomous systems. • Examine real-world use cases by industry, including healthcare, finance, retail, and the public sector.
Aligning AI with Business Strategy
Identify opportunities for AI adoption and assess AI ROI and business impact. • Develop executive decision-making skills in AI-driven environments. • Understand AI as a driver of digital transformation.
Understanding AI Risks and Regulation
Recognize key AI risks, including bias, explainability, security, and compliance. • Examine the global regulatory landscape, including the EU AI Act and U.S. Executive Orders. • Discuss responsible AI and ethical considerations.
Governance and Oversight
Build AI governance structures and understand the role of boards and leadership in AI oversight. • Manage third-party risk and vendor accountability. • Conduct audits, impact assessments, and identify red flag indicators.
Organizational Readiness and Execution
Develop AI talent, teams, and cross-functional collaboration. • Evaluate AI procurement and vendor selection. • Scale AI initiatives with governance in mind.
AI Culture and Communication
Lead change and address resistance to AI adoption. • Communicate AI strategy internally and externally. • Build an AI-literate executive team.
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Machine Learning |
| Covered Tool / Platform | Natural Language Processing |
| Covered Tool / Platform | Computer Vision |
| Covered Tool / Platform | Generative AI |
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