Targeted Audience

Ethics Consultant

Product Manager

Data Analyst

Architect

Modules | 8

Examination | 1

Passing Score | 70%

COURSE AGENDA

Module 1: Introduction To Artificial Intelligence (AI)

1.1 What is Artificial Intelligence?
1.2 A Brief History of AI
1.3 Demystifying AI: Myths vs. Reality
1.4 The Significance of AI in Everyday Life

Module 2: AI Technologies

2.1 Machine Learning: Basics and Beyond
2.2 Deep Learning and Neural Networks
2.3 AI Technologies in Action: Simplified Examples
2.4 Interactive Workshop: Exploring AI

Module 3: AI in Action: Applications And Case Studies

3.1 Introduction to AI Applications
3.2 Case Study 1: Smart Speakers
3.3 Case Study 2: Self-Driving Cars
3.4 Case Study 3: Healthcare Applications

Module 4: The Workflow of AI Projects

4.1 Introduction to AI Project Workflow
4.2 Problem Definition and Data Preparation
4.3 Model Selection, Training, and Validation
4.4 Deployment and Integration
4.5 Evaluation and Iteration

Module 5: Ethics And Social Implications Of AI

5.1 Introduction to AI Ethics and Social Implications
5.2 Bias and Fairness in AI
5.3 Privacy and Security in the Age of AI
5.4 Responsible AI Development
5.5 AI and Society: Looking Ahead

Module 6: Generative AI And Creativity

6.1 Introduction to Generative AI
6.2 Applications of Generative AI in Creativity
6.3 Ethical Considerations in Generative AI
6.4 Exploring the Future of Creativity with A

Module 7: Preparing For An AI-Driven Future

7.1 The Future Landscape of AI
7.2 AI and the Transformation of Work
7.3 Lifelong Learning in an AI World
7.4 Staying Relevant in an AI-Driven World
7.5 Interactive Discussion: Preparing for the Future with AI

Module 8: Starting With AI: First Steps And Resources

8.1 Introduction to Starting with AI
8.2 Choosing AI Projects
8.3 Forming AI Teams
8.4 Resources for Learning and Development in AI

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