Foundations of Artificial Intelligence (ICP-FAI)

After completing this course, you will be able to:

• Discuss how AI has evolved to its current state
• Name and use key AI-related terminology
• Use AI as it continues to evolve
• Describe the ethical issues that AI can present, and mitigate those issues
• Use Agility in your AI initiatives
• Develop your ability to prompt Generative AI tools
• Use AI to deliver business value and support business strategy

Audience/Prerequisites

All professionals would benefit from this training. There is no need for a technical background or any knowledge of AI to complete this course.

Credits/Exams

Although there is not an ICAgile official exam, ICAgile allows for their course accreditors to determine appropriate means for retention of the learning outcomes. Depending on your provider, there may be some type of assessment in order to earn certification.

Many providers assess via participation, activity, and understanding conveyed via exercises and discussion, withholding certification when appropriate.

Outline

1. Introduction to Artificial Intelligence

1.1. Evolution of AI

1.1.1. Understanding AI

• Key concepts
• Potential applications
• Limitations of AI in the workplace
• Practical applications and potential of AI
• How AI differs from traditional computing

1.1.2. Pieces of the AI Puzzle

• Machine learning
• Deep learning
• Algorithms
• Data processing
• Generative AI

1.1.3. Evolving State of AI

• Why is AI evolving at such a rapid rate?
• Artificial Narrow Intelligence (ANI) vs. Artificial General Intelligence (AGI)
• Common myths and misconceptions surrounding AI

Exercise – (In the style of Jeopardy)

• Identify concepts
• Define terms
• Which enabled the other?

1.2. Ethical and Legal Considerations of AI

1.2.1. Ethics in the Context of AI

• Moral principles and guidelines
• Ethical considerations to address

1.2.2. The Inherent Bias of AI

• The impact of bias
• Approaches and strategies to ensure ethical AI
• Human validation of AI

1.2.3. Data Compliance and Privacy

• Regulatory considerations (e.g. GDPR & HIPAA)
• Compliance strategies

1.3. Prompt Engineering

1.3.1. Introduction to Prompt Engineering

• The basics of effective AI Prompt Engineering
• Recognizing well-crafted prompts that lead to useful, specific answers

1.3.2. Effective Prompts

• Techniques for crafting prompts that produce accurate, reliable, and unbiased results
• Recognizing when to revise prompts based on the AI's results
• The importance and impact of context in prompt engineering
• Creating prompts based on clearly identified goals

1.3.3. All Prompts are Not Created Equal

• Contrast results from various LLMs and Generative AI tools
• Sources for syntax guidance for different AI solutions
• Patterns and strategies for crafting effective prompts

Exercise

• Use several prompting techniques with ChatGPT

2. Artificial Intelligence in the Enterprise

2.1. The Agile Advantage

2.1.1. Agile Mindset and AI

• The connection between the agile mindset, values, and principles and AI
• How a culture of learning, reflecting and adapting enables AI success

2.1.2. Agile Behaviors and AI

• Applying iterative development, continuous feedback, and collaboration to AI solutions
• How planning, designing, testing, and keeping AI systems up to date differs from other efforts.

2.1.3. Cross-Functional Teams and AI

• The cross-functional skills needed in a team focused on AI (e.g., prompt engineering, data literacy, data science, software engineering, ethics, domain-specific knowledge)
• Evolving the cross-functional AI team

2.2 Leveraging AI in the Organization

2.2.1. Business Value of AI

• How AI can be used to create competitive advantages, optimize operations, and enhance customer engagement
• Making strategic decisions about investing in, developing, or implementing AI solutions based on AI's business value
• How AI supports and complements the skills and creativity of humans

2.2.2. Align AI with Strategy

• Aligning AI initiatives with strategic objectives
• Infrastructure to support AI initiatives
• The cultural shift towards data-driven decision-making
• Oversight for responsible AI governance

2.2.3. AI Initiative in the Real World

• Examples of real-world AI initiatives
• Types of AI solutions and their potential impacts on an organization

Exercise – Plan your Path Forward

• What steps can you take to use AI right away?
• What will you plan to do in the next few months?
• What will take longer to achieve, but would be worth it?