Artificial Intelligence for Managers

Why this course: 70% of AI initiatives in organizations fail today not because of a lack of good AI solutions but because of a lack of understanding of AI among the managers - the end users, decision makers and investors in AI. Recruiters & Executives are struggling to find business professionals with a practical understanding of AI. This course is designed specifically to teach current and future managers all that they need to know to lead and manage AI use, without having to code and build AI models. You will:

1) Learn both technical & managerial aspects of AI

2) Identify the right AI solution & learn rare managerial frameworks to lead AI journeys successfully in an organization.

3) Get recognized in the use and management of AI/ML/DL by getting certified.

4) Gain competitive advantage in a hiring process or at work by being AI ready.

• Understanding AI 29:46

  • 1: Overview Preview 05:04
  • 2: 1. AI Fundamentals Preview 09:50
  • 3: Artificial Intelligence (AI) vs. Machine Learning (ML) vs. Deep Learning (DL) 04:36
  • 4: How do "they" create AI? 10:16

• Getting Started with AI 28:53

  • 5: A Real-Life Example of AI Adoption 11:27
  • 6: Preparing Data for AI use 09:14
  • 7: Choosing the Right AI Solution 08:12

• Deciding the Type of AI to Build or Buy 1:34:44

  • 8: Overview of AI/ML/DL Techniques 02:37
  • 9: Predicting values & categories using AI – Part 1 04:45
  • 10: Predicting values & categories using AI – Part 2 05:14
  • 11: Predicting values & categories using AI – Part 3 06:23
  • 12: Identify Different Groups in a Population using AI 07:08
  • 13: Predict Behaviour using AI 05:28
  • 14: Find the Optimal Solution from a Set of Solutions using AI 06:56
  • 15: Teach AI to learn on its own 08:16
  • 16: Communicate using AI 08:34
  • 17: How AI starts to think like humans 07:47
  • 18: Recognize Images using AI 10:34
  • 19: S3L17A - Generative AI, LLM & ChatGPT Preview 21:02

• Ensuring Success with Using AI 56:41

  • 20: People, Process & Performance 12:00
  • 21: AI Valuation 10:11
  • 22: AI Strategy & Policy 11:10
  • 23: AI Ethics & Risk Management 10:57
  • 24: Conclusion 12:23

What this course covers:

1. What is AI, Machine Learning & Deep Learning, and how are they different from BI

2. 7 Principles of an AI Journey

3. How to decide whether a problem needs AI at all

4. If AI is needed, how to become data ready – Tuscane© Approach

5. Once ready, how to decide whether to build or buy a solution as well as what the risks really are with doing AI incorrectly – Fab-4© Model

6. How to tell whether a software uses AI, or what kind of AI it uses

7. How to differentiate powerful AI solutions from weaker ones

8. How to determine which AI technique(s) can solve your specific business or organizational problem

9. How AI analyzes different types of information, how it makes predictions, how it recognizes images, how it communicates with your customers, or how a robot learns to behave like humans! This will involve some of the most popular Machine Learning and Deep Learning techniques that are being used today: Classification, Regression, Decision Trees, Ensemble Learning, Clustering, Association Rules, Search Algorithm, Reinforcement Learning, Natural Language Processing, ANN & CNN and Generative AI

10. How to measure AI’s performance with a 4-step approach

11. How to get others to use it in the organization

12. How to implement it successfully so that you don't waste thousands of dollars and hours of effort

13. How to estimate the financial value of an AI solution

14. Best Practices to formulate an AI strategy

15. 7 Principles of Human-AI Work Policy Framing

16. How to minimize risks associated with AI for an individual and the organization

Ideal for: The classes have been designed to provide in-depth practical knowledge on AI, Machine Learning & Deep Learning if you:

1) Are interested in AI/ML/DL to advance your careers or to use it effectively to accomplish tasks at work

2) Have limited time but would like to get a thorough managerial understanding of AI/ML/DL

3) Do not need or are not interested in learning how to code AI/ML/DL

Common student profiles include:

• Executive Leaders
• Managers
• Administrators
• New Graduates
• University / College Students

Basic knowledge of management

Basic comfort with computer or statistical explanations

The course is useful for almost any career path. Typical examples include:

• Manager of AI-enabled tools and solutions, or their use in any function or organization
• Project, Change or Digital Transformation Manager/Leader
• Go-to-resource / subject matter expert for AI strategy & implementation in organizations

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Reed courses certificate of completion

Digital certificate - Included