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IT: Artificial Intelligence & Data
Advanced Generative Models and Careers
Curriculum
1 Section
36 Lessons
30 hours
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Unit 4 — Advanced Generative Models and Careers
36
1.1
Practical Examples and Use Cases
20 mins
1.2
Ethical Considerations and Limitations
20 mins
1.3
The Future of DeepFaceLab
20 mins
1.4
Getting to Know DeepArt Effects
20 mins
1.5
The Role of Prompts in DeepArt Effects
20 mins
1.6
Showcasing Real-World Scenarios
20 mins
1.7
Strengths and Weaknesses
20 mins
1.8
Future Trajectories of DeepArt Effects
20 mins
1.9
Introduction to AIVA
20 mins
1.10
How AIVA Utilizes Prompts
20 mins
1.11
Examples of AIVA Applications
20 mins
1.12
Limitations of AIVA
20 mins
1.13
The Future of AIVA
20 mins
1.14
Examples of AI Music Prompts (Source: https://contentatscale.ai/ai-music-prompt/)
20 mins
1.15
Understanding WaveNet
20 mins
1.16
The Significance of Prompts in WaveNet
20 mins
1.17
Showcasing WaveNet in Real-World Scenarios
20 mins
1.18
Accessibility Tools
20 mins
1.19
Limitations and Room for Improvement
20 mins
1.20
The Next Steps for WaveNet
20 mins
1.21
Getting to Know ImageNet
20 mins
1.22
How Prompts Play a Role in ImageNet
20 mins
1.23
Practical Applications and Examples
20 mins
1.24
Limitations of ImageNet
20 mins
1.25
Future Developments in ImageNet
20 mins
1.26
Introduction to VQ-VAE
20 mins
1.27
The Impact of Prompts on VQ-VAE
20 mins
1.28
Real-World Use Cases and Examples
20 mins
1.29
Limitations and Areas for Improvement
20 mins
1.30
Looking Forward: The Future of VQ-VAE
20 mins
1.31
Where Can Prompt Engineering Take You?
20 mins
1.32
Potential Career Paths and Opportunities
20 mins
1.33
Building a Portfolio in Prompt Engineering
20 mins
1.34
Continuing Your Education and Skills Development
20 mins
1.35
Joining the Global Community of Prompt Engineers
20 mins
1.36
Advanced Techniques: Staying Ahead in Prompt Engineering
20 mins
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