AI for Everyone Unleashing the Power of Innovation #254029

Upon completion of this course, participants will be able to:

• Demystify Core AI Concepts: Define key terms like Machine Learning, Deep Learning, Neural Networks, and Generative AI in simple, accessible language.

• Identify Real-World Applications: Recognize how AI is being applied across different industries to solve problems, create new products, and improve efficiency.

• Understand the AI Project Workflow: Comprehend the steps involved in building an AI system, from data collection and model training to deployment and monitoring.

• Evaluate AI Opportunities: Develop a framework for spotting high-impact AI opportunities within your own role or organization.

• Navigate Ethical and Societal Implications: Engage in informed discussions about AI ethics, including bias, privacy, job displacement, and responsible innovation.

• Build a Culture of AI Innovation: Learn strategies to foster collaboration between technical and non-technical teams and champion AI initiatives.

This course is intentionally designed for a broad, cross-functional audience with no prior technical background required:

• Business Leaders & Executives: CEOs, VPs, and Directors who need to set AI strategy.

• Managers & Team Leads from any department (Marketing, HR, Finance, Operations, Legal).

• Entrepreneurs & Business Owners looking to innovate and gain a competitive edge.

• Project Managers & Product Managers overseeing digital transformation projects.

• Consultants & Strategists advising clients on technology and innovation.

• Creatives, Designers, & Writers interested in the intersection of AI and their fields.

• Anyone curious about AI and its potential to reshape the future of work and society.

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

Day 1: Demystifying AI: What It Is and Why It Matters

• AM: Welcome to the AI Revolution

  • Beyond Science Fiction: Dispelling common myths and fears about AI.

  • Key Concepts Made Simple: AI vs. Machine Learning vs. Deep Learning.

  • The State of AI Today: A tour of groundbreaking real-world applications.

• PM: How Machines Learn

  • A non-technical explanation of how AI models are trained with data.

  • Supervised, Unsupervised, and Reinforcement Learning explained with analogies.

  • Interactive Workshop: “Teaching” a simple AI concept as a group.

Day 2: The AI Toolbox: Technologies Transforming Our World

• AM: Seeing and Understanding: Computer Vision & Natural Language Processing (NLP)

  • How AI “sees” images and videos (facial recognition, medical imaging, self-driving cars).

  • How AI “understands” language (chatbots, translation, sentiment analysis).

  • Case Studies: Spotify’s recommendations, Netflix’s personalization.

• PM: The Creative Machine: Generative AI

  • Introduction to Generative AI tools like ChatGPT, DALL-E, and Midjourney.

  • Exploring use cases for content creation, design, and ideation.

  • Hands-on Demo: Experimenting with a user-friendly Generative AI tool.

Day 3: Building an AI-Powered Business: Strategy and Implementation

• AM: The AI Project Lifecycle (Without the Code)

  • A step-by-step guide: From defining the problem and gathering data to deployment and feedback.

  • Understanding the importance of data quality and ethics from the start.

  • Group Exercise: Brainstorming AI solutions to a common business problem.

• PM: Finding AI Opportunities in Your Work

  • Frameworks for identifying tasks that can be augmented or automated with AI.

  • How to conduct an “AI Opportunity Audit” for your team or department.

  • Workshop: Mapping AI opportunities to your own professional challenges.

Day 4: Navigating the Human Side of AI: Ethics, Bias, and the Future of Work

• AM: Responsible Innovation: Ethics and Bias in AI

  • How bias can creep into AI systems and how to mitigate it.

  • Discussions on privacy, surveillance, and accountability.

  • Debate Session: Analyzing a controversial AI case study (e.g., facial recognition in policing).

• PM: AI and the Future of Work

  • Will AI take my job? Redefining roles and building human-AI collaboration.

  • The essential human skills needed in an AI-augmented world.

  • Strategies for lifelong learning and upskilling.

Day 5: Becoming an AI Leader: Your Innovation Action Plan

• AM: Building a Culture of AI Innovation

  • How to communicate about AI with technical teams and stakeholders.

  • Leading pilot projects and building a business case for AI investment.

  • Guest Speaker (or Case Study): A leader who successfully championed an AI project.

• PM: Capstone: Your AI Innovation Plan

  • Final Project: Participants develop a one-page proposal for an AI initiative relevant to their work.

  • Peer feedback and presentation session.

  • Course Wrap-Up: Resources for continued learning and committing to action.