- Level Foundation
- المدة 11 ساعات hours
- الطبع بواسطة DeepLearning.AI
-
Offered by
عن
AI is not only for engineers. If you want your organization to become better at using AI, this is the course to tell everyone--especially your non-technical colleagues--to take. In this course, you will learn: - The meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science - What AI realistically can--and cannot--do - How to spot opportunities to apply AI to problems in your own organization - What it feels like to build machine learning and data science projects - How to work with an AI team and build an AI strategy in your company - How to navigate ethical and societal discussions surrounding AI Though this course is largely non-technical, engineers can also take this course to learn the business aspects of AI.الوحدات
What is AI?
1
Assignment
- Week 1 Quiz
1
External Tool
- Intake Survey
9
Videos
- Week 1 Introduction
- Machine Learning
- What is data?
- The terminology of AI
- What makes an AI company?
- What machine learning can and cannot do
- More examples of what machine learning can and cannot do
- Non-technical explanation of deep learning (Part 1, optional)
- Non-technical explanation of deep learning (Part 2, optional)
1
Readings
- [IMPORTANT] Have questions, issues or ideas? Join our Forum!
Lecture Notes (Optional)
1
Readings
- Lecture Notes Week 1
Building AI Projects
1
Assignment
- Week 2 Quiz
8
Videos
- Week 2 Introduction
- Workflow of a machine learning project
- Workflow of a data science project
- Every job function needs to learn how to use data
- How to choose an AI project (Part 1)
- How to choose an AI project (Part 2)
- Working with an AI team
- Technical tools for AI teams (optional)
Lecture Notes (Optional)
1
Readings
- Lecture Notes Week 2
Building AI in Your Company
1
Assignment
- Week 3 Quiz
10
Videos
- Week 3 Introduction
- Case study: Smart speaker
- Case study: Self-driving car
- Example roles of an AI team
- AI Transformation Playbook (Part 1)
- AI Transformation Playbook (Part 2)
- AI pitfalls to avoid
- Taking your first step in AI
- Survey of major AI application areas (optional)
- Survey of major AI techniques (optional)
1
Readings
- AI Transformation Playbook
Lecture Notes (Optional)
1
Readings
- Lecture Notes Week 3
AI and Society
1
Assignment
- Week 4 Quiz
8
Videos
- Week 4 Introduction
- A realistic view of AI
- Discrimination / Bias
- Adversarial attacks on AI
- Adverse uses of AI
- AI and developing economies
- AI and jobs
- Conclusion
1
Readings
- (Optional) Opportunity to Mentor Other Learners
Lecture Notes (Optional)
1
Readings
- Lecture Notes Week 4
Auto Summary
"AI For Everyone" is a foundational course designed to demystify artificial intelligence for a broad audience, particularly those in business and management. Led by Coursera, this course offers a comprehensive introduction to AI concepts, including neural networks, machine learning, deep learning, and data science. It's tailored for non-technical professionals looking to enhance their organization's AI capabilities, though engineers can also benefit from the business insights provided. Participants will gain a realistic understanding of AI's potential and limitations, learn to identify AI opportunities within their organizations, and experience what it's like to develop machine learning and data science projects. The course also covers collaboration with AI teams, building AI strategies, and engaging in ethical and societal discussions related to AI. Spanning 660 minutes, this course is available through a starter subscription, making it accessible for anyone seeking to build a solid foundation in AI. Whether you're a business leader, manager, or engineer, "AI For Everyone" equips you with the knowledge to leverage AI effectively in your professional environment.

Andrew Ng