DeepLearning.AI - AI For Everyone
- Offered byCoursera
AI For Everyone at Coursera Overview
Duration | 6 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course |
Credential | Certificate |
AI For Everyone at Coursera Highlights
- Earn a certificate from Coursera
- Learn from industry experts
AI For Everyone at Coursera Course details
- Ideally suited for Senior Managers, Product Managers, and Business professionals. Engineers can also take this course to learn business aspects of AI.
- 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
This course will help in learning about different AI terminologies such as data science, machine learning and deep learning
It will also help learners in understanding the realistic applications of AI
After this course, learners would be skilled in workflows of data science and machine learning projects
Learners will have a strong AI foundation with the capability to pick up appropriate AI projects
AI For Everyone at Coursera Curriculum
Week 1: What is AI?
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)
Week 2: Building AI Projects
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)
Week 3: Building AI In Your Company
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)
Week 4: AI and Society
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