Training Outline

Master AI fundamentals and critical thinking with this engaging and practical training course. Dive into the fundamentals of AI and discover its real-world applications and ethical considerations. You’ll learn to identify the different types of AI, understand how they work, and explore their everyday uses.

This AI fundamentals and critical thinking course sharpens your thinking skills, helping you cut through the hype and evaluate AI claims with confidence. You’ll gain hands-on knowledge of machine learning, including popular algorithms and the latest AI technologies shaping industries like healthcare, finance, and law.

We don’t just stop at the technical side, we tackle the big questions too. Explore key ethical issues such as fairness, accountability, transparency, bias, data privacy, and security. Through real-world examples and case studies, you’ll learn how to spot problematic AI applications and create practical, ethical solutions.

By the end of this course, you’ll be ready to assess AI systems, understand their challenges, and design strategies for deploying AI responsibly and ethically. Whether you’re a professional, an organization, or an enthusiast looking to stay ahead in the AI revolution, this course equips you with the tools and insights to thrive.

Learning Objectives

1. Describe the fundamentals of AI, including different types and common applications in everyday life.
2. Understand and discuss key ethical issues in AI, such as fairness, accountability, transparency, and bias, with the help of real-world examples.
3. Apply critical thinking principles to evaluate claims about AI, differentiating between hype and reality through practical exercises.
4. Explain how machine learning works, identify commonly used algorithms in AI, and recognize AI technologies currently in use across various sectors.
5. Discuss the ethical implications of AI, including data privacy, security, and its impact on personal freedoms, and critically assess how to balance these issues with technological innovation.
6. Analyze the application of AI in key areas such as healthcare, finance, and law, evaluate case studies of both successful and problematic AI implementations, and develop AI solutions for real-world problems.
7. Critically evaluate the effectiveness and challenges of various AI implementations, identifying key factors that contribute to successful or problematic outcomes.
8. Gain an understanding of the ethical considerations and potential biases in AI systems, particularly in high-impact areas such as healthcare, finance, and law enforcement.
9. Propose best practices and strategies for developing and deploying AI systems responsibly and ethically.