数据科学家的生成式人工智能分析专长
Generative AI for Data Scientists Analytics Specialization
- 1. Generative AI for Data Science and Data Analytics
- 1. Why Learn Generative AI
- 2. Course Introduction
- 2. Generative AI in Data Science
- 1. Generative AI and Data Science
- 2. Generative AI's Impact Across Industries
- 3. Leveraging Generative AI in Data Science Lifecycle
- 4. Types of Generative AI Models
- 3. Generative AI for Data Preparation and Querying
- 1. Demo Generative AI for Data Generation and Augmentation
- 2. Generative AI for Data Preparation and Data Querying
- 3. Demo Generative AI for Data Preparation
- 4. Demo Generative AI for Querying Databases
- 4. Generative AI for Understanding Data and Model Building
- 1. Demo Generative AI for Data Insights
- 2. Demo Generative AI for Data Visualization
- 3. Generative AI Tools for Model Development
- 4. Generative AI for Understanding Data and Model Development
- 5. AI Ethics
- 1. Considerations for Responsible Generative AI
- 2. Implementing Responsible AI in Diverse Industries
- 3. Limitations of Generative AI
- 4. Issues and Concerns About Generative AI
- 6. Introduction and Applications of Generative AI
- 1. Course Introduction
- 2. Introduction to Generative AI
- 4. Capabilities of Generative AI
- 5. Applications of Generative AI
- 6. Tools for Text Generation
- 7. Tools for Image Generation
- 8. Tools for Audio and Video Generation
- 9. Tools for Code Generation
- 7. Generative AI Prompt Engineering for Data Scientists
- 1. Course Introduction
- 3. What is Prompt
- 4. What is Prompt Engineering
- 5. Best Practices for Prompt Creation
- 6. Common Prompt Engineering Tools
- 8. Prompt Engineering Techniques and Approaches
- 1. Text-to-Text Prompt Techniques
- 2. Interview Pattern Approach
- 3. Chain of Thought Approach
- 4. Tree of Thought Approach
- 5. Text-to-Image Prompt Techniques
- 9. Farewell and Congrats
- 1. Course Conclusion