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Курс: AI For Everyone. Чтобы вернуться, нажмите здесь.
- 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 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 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 Introduction
- A realistic view of AI
- Discrimination / Bias
- Adversarial attacks on AI
- Adverse uses of AI
- AI and developing economies
- AI and jobs
- Conclusion