AI For Everyone
AI is not only for engineers. “AI for Everyone”, a non-technical course, will help you understand AI technologies and spot opportunities to apply AI to problems in your own organization. You will see examples of what today’s AI can – and cannot – do. Finally, you will understand how AI is impacting society and how to navigate through this technological change.
If you are a non-technical business professional, “AI for Everyone” will help you understand how to build a sustainable AI strategy. If you are a machine learning engineer or data scientist, this is the course to ask your manager, VP or CEO to take if you want them to understand what you can (and cannot!) do.

Week 1

Week 2

Week 3

Week 4
Course syllabus
Week 1: What is AI
- Introduction
- Machine Learning
- What is data
- The terminology of AI
- What makes an AI company?
- What Machine Learning can and cannot do
- Intuitive explanation of deep learning
Week 2: Building AI Projects
- Workflow of a Machine Learning project
- Workflow of a Data Science project
- Every job function needs to learn to use data
- How to choose an AI project
- Working with an AI team
- Technical tools for AI teams
Week 3: AI in Your Company
- Case study: Smart speaker
- Case study: Self-driving car
- Example roles of an AI team
- AI Transformation Playbook
- AI pitfalls to avoid
- Taking your first step in AI
- Survey of major AI applications
- Survey of major AI techniques
Week 4: AI and Society
- A realistic view of AI
- Discrimination / Bias
- Adversarial attacks
- Adverse uses
- AI and developing nations
- AI and jobs
- Conclusion


Frequently Asked Questions
Who is the course for?
What will I learn?
Are there any prerequisites?
How do I take the course?
You can enroll in AI For Everyone on Coursera’s platform. You will watch videos and complete assignments on Coursera as well.
How much does the course cost?
Can I apply for financial aid?
Will I receive a certificate at the end of the course?
How long is the course?
About the Instructor

He was until recently Chief Scientist at Baidu, where he was responsible for driving the company’s global AI strategy and infrastructure. He was also the founding lead of the Google Brain team. Dr. Ng has authored or co-authored over 100 research papers in machine learning, robotics and related fields. He holds degrees from Carnegie Mellon University, MIT and the University of California, Berkeley.