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IT: Artificial Intelligence & Data
Generative AI Models and Prompts
Curriculum
1 Section
36 Lessons
30 hours
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Unit 2 — Generative AI Models and Prompts
36
1.1
Future Developments and Opportunities
20 mins
1.2
Introduction to ChatGPT
20 mins
1.3
How Prompts Play a Role in ChatGPT
20 mins
1.4
Use Cases and Examples
20 mins
1.5
Challenges and Areas of Improvement
20 mins
1.6
ChatGPT: The Next Steps
20 mins
1.7
The Concept of DALL-E
20 mins
1.8
How DALL-E Utilizes Prompts
20 mins
1.9
Examples of Generated Artwork
20 mins
1.10
Limitations of Dall-E
20 mins
1.11
The Future of DALL-E
20 mins
1.12
Ethical and Societal Implications
20 mins
1.13
An Overview of CTRL
20 mins
1.14
Prompts in CTRL: What’s Different?
20 mins
1.15
Showcasing CTRL in Action
20 mins
1.16
Limitations and Ethical Concerns
20 mins
1.17
CTRL’s Evolution and Future Trajectories
20 mins
1.18
Introduction to T2T
20 mins
1.19
The Role of Prompts in T2T
20 mins
1.20
Practical Applications of T2T
20 mins
1.21
Strengths and Weaknesses of T2T
20 mins
1.22
The Future of T2T
20 mins
1.23
Getting to Know BERT
20 mins
1.24
How BERT Handles Prompts
20 mins
1.25
Use Cases and Real-World Examples
20 mins
1.26
Limitations of BERT
20 mins
1.27
Future Developments in BERT
20 mins
1.28
Introduction to Tacotron
20 mins
1.29
The Significance of Prompts in Tacotron
20 mins
1.30
Showcasing Tacotron in Real-World Scenarios
20 mins
1.31
Limitations and Room for Improvement
20 mins
1.32
The Next Steps for Tacotron
20 mins
1.33
Introduction to MuseNet
20 mins
1.34
Role of Prompts in MuseNet
20 mins
1.35
Examples of MuseNet Outputs
20 mins
1.36
Limitations and Ethical Considerations
20 mins
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