Introduction to AI for Non Technical Professionals #254001

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

• Define key AI concepts (Machine Learning, Deep Learning, NLP, Generative AI) in simple, business-relevant language.

• Understand how AI models are built and trained without needing to code, focusing on the process of using data to find patterns.

• Identify practical use cases for AI across various business functions (e.g., marketing, HR, finance, operations).

• Evaluate the feasibility and ROI of potential AI projects, asking the right questions about data, cost, and value.

• Recognize ethical implications and biases in AI and understand frameworks for responsible AI adoption.

• Collaborate effectively with technical teams and vendors on AI initiatives, bridging the communication gap.

This course is ideal for professionals who need to understand AI’s impact on their industry and role, without needing to become technical experts.

• Managers, Directors, and VPs across all business units (Marketing, Sales, HR, Finance, Operations)

• Product Managers and Project Managers

• Business Analysts and Strategy Consultants

• Executives (CEOs, COOs, CMOs) and Entrepreneurs

• Legal, Compliance, and Risk Professionals

• Anyone curious about AI and its real-world applications

• 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

• Morning:

  • Module 1: AI in the Real World: Cutting through the hype. Definitions of AI, Machine Learning (ML), and Generative AI.

  • Module 2: A Brief History of AI: How we got here and why now is the tipping point.

• Afternoon:

  • Module 3: The Engine of AI: Data: Understanding how data is the fuel. Concepts of training data, features, and outcomes.

  • Interactive Workshop: AI in Your Pocket: A fun, group activity to identify AI-driven features in everyday apps (Netflix, Spotify, Google Maps).

  • Day 1 Recap: Key terminology and core concepts.

Day 2: How AI Works – The Magic Explained (Without Code)

• Morning:

  • Module 4: How Machines Learn: A simple analogy for supervised, unsupervised, and reinforcement learning.

  • Module 5: Introduction to Key Technologies: What are Natural Language Processing (NLP), Computer Vision, and Predictive Analytics?

• Afternoon:

  • Module 6: The AI Project Lifecycle: From defining the problem and gathering data to training, deploying, and monitoring a model.

  • Case Study: How Spotify Recommends Music: A breakdown of a familiar use case to illustrate the concepts.

  • Day 2 Recap: Understanding the process behind AI solutions.

Day 3: AI in Action – Industry and Function-Specific Applications

• Morning:

  • Module 7: AI for Marketing and Sales: Personalization, chatbots, lead scoring, and dynamic pricing.

  • Module 8: AI for Operations and HR: Process automation, fraud detection, resume screening, and employee retention prediction.

• Afternoon:

  • Module 9: AI in Your Industry: Deep dive into applications for healthcare, retail, finance, or manufacturing (can be tailored).

  • Workshop: Ideation Session: Teams brainstorm potential AI solutions to a real business problem within their company.

  • Day 3 Recap: Connecting AI capabilities to business value.

Day 4: The Business of AI – Implementation and Ethics

• Morning:

  • Module 10: Building vs. Buying: How to evaluate off-the-shelf AI solutions vs. building custom ones.

  • Module 11: Measuring Success: How to define and track KPIs and ROI for AI projects.

• Afternoon:

  • Module 12: The Ethical Imperative: Understanding algorithmic bias, fairness, transparency, and privacy (GDPR).

  • Group Discussion: An Ethical Dilemma: Discussing a real-world case of AI bias and its consequences.

  • Day 4 Recap: The practical and responsible path to adoption.

Day 5: The Future of AI and Your Role

• Morning:

  • Module 13: The Future of Work: How AI will augment (not replace) jobs. The skills needed to thrive.

  • Module 14: Getting Started: How to champion an AI pilot project in your organization.

• Afternoon:

  • Capstone Activity: The AI Proposal: Participants draft a one-page proposal for a small AI initiative, outlining the business problem, proposed solution, data needs, and ethical considerations.

  • Final Presentations & Peer Feedback: Presenting proposals in a “shark tank” style format.

  • Course Conclusion: Key takeaways, resources for continued learning, and Q&A.