Description
Who should attend
This course is designed for executives, managers, and decision-makers in various industries who want to understand the potential of Generative AI and how it can impact their business strategies and operations. No technical background in AI is necessary, making it accessible to a wide range of professionals, including but not limited to:
- CEOs, CTOs, and other C-suite executives
- Business Development Managers
- Product Managers
- Marketing and Sales Managers
- Innovation and R&D Leaders
- Strategy and Planning Executive
Prerequisites
- Familiarity with the fundamentals of data and Azure cloud
- No prior knowledge of Generative AI is required
Outline: Generative AI for Executives (GAIE)
Module 1: Quick recap of AI and ML
- AI Overview
- Traditional Systems vs Machine Learning based AI
- Taxonomy of AI
- Capabilities & Use Cases
- AI & Data Science
- Types of Machine Learning
- Understanding ML Algorithms in an Intuitive Way
- Introduction to Deep Learning
- Ways to Implement AI
- Demos on Sentiment analysis of Tweets and Pictures
Module 2: Generative AI Overview
- Introduction to Generative AI
- Evolution of Generative AI
- How Generative AI Differs from Other AI Technologies
- Understanding Generative AI and its Capabilities
- Distinctions Between Generative AI and Traditional AI/ML
- Exploring the Generative AI Value Chain
- Current Trends in Generative AI including ChatGPT
- Applications and Use Cases of Generative AI
- Demos to give broader perspective about Bard, ChatGPT, MidJourney and more
Module 3: Being an AI first company using Generative AI
- Organizational Requirements for Generative AI Adoption
- Preparing the Organization for Generative AI Integration
- Skillsets and Expertise Required for Implementing Generative AI
- Overcoming Challenges and Managing Risks in Generative AI Adoption
- Strategic Initiatives for Incorporating AI
- Building an AI-First Company Culture
- Vision, Risks, Assumptions, Acceptance and more
- Integrating Generative AI into Business Processes
- Exploring Opportunities for AI Innovation and Growth
- Adopting Generative AI Strategy
Module 4: Best Practices of Prompt Engineering
- Importance of Well-Defined Prompts in Generative AI
- Strategies for Crafting Effective Prompts
- Leveraging Prompt Engineering for Desired Outputs
- Lab Exercise on better prompt design
Module 5: Significance of Cloud and Data Strategy in Generative AI
- Cloud Computing and its Impact on Generative AI
- Data Collection, Privacy, and Security Considerations
- Leveraging Data for Improving Generative AI Performance
- Ethical and Responsible AI
- Understanding Ethical Concerns in Generative AI
- Responsible Use of Generative AI Technologies
- Building Trustworthy AI Systems
- Future Trends and Opportunities in Generative AI
- Exploring the Potential of Generative AI in Different Industries
- Anticipating Advancements and Innovations in Generative AI
- Identifying Opportunities for Business Growth and Competitive Advantage
- Demo on Cloud AI
Module 6: Implementing Generative AI in Business
- Implementing Generative AI Strategy
- Key considerations for integrating Generative AI into existing workflows
- Identifying use cases and projects suitable for Generative AI adoption
- Evaluating ROI and cost-benefit analysis of Generative AI implementation
Module 7: Ethical Considerations and Responsible AI
- Addressing biases and fairness in Generative AI models
- Understanding the potential societal impact of Generative AI
- Developing ethical guidelines for using Generative AI responsibly
