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11. Practice & Resources
Miscellaneous Topics
Capstone Project Ideas
Image Generator — Train a DCGAN or diffusion model on a custom dataset of 1000+ images
Chatbot Fine-tuning — Fine-tune Llama 2/3 on a custom dataset using LoRA
Text-to-Image Pipeline — Build a Streamlit app around Stable Diffusion with prompt engineering features
Music Generation — Implement a simple RNN or transformer for MIDI music generation
Quiz Questions
What is the difference between a generative and discriminative model?
Explain the GAN training objective (minimax game).
How does the attention mechanism compute relationships between tokens?
What problem does KL divergence solve in VAEs?
Describe the three stages of RLHF.
What is mode collapse in GANs and how can it be mitigated?
Compare autoregressive models with diffusion models for image generation.
What is the purpose of positional encoding in transformers?
Ethics & Limitations
Misinformation — Generative AI can create convincing fake content (deepfakes, fake news)
Copyright — Legal questions around training data and generated outputs
Environmental Impact — Training large models consumes significant energy
Job Displacement — Automation of creative and knowledge work raises economic concerns
Bias Amplification — Models may reinforce stereotypes present in training data
Future Trends
AI Agents — Autonomous systems that plan, use tools, and complete complex tasks
Real-Time Generation — Instant video/audio generation for live applications
Smaller, Efficient Models — Distillation and quantization for edge deployment
Multimodal Understanding — Seamless cross-modal generation and reasoning
Personalized AI — Models that learn and adapt to individual users
Study Plan (8 Weeks)
Weeks 1-2: Foundations — probability, ML basics, types of generative models
Weeks 3-4: GANs and VAEs — theory, implementation, experimentation
Weeks 5-6: Transformers and diffusion models — attention, GPT, Stable Diffusion
Weeks 7-8: Applications, fine-tuning, ethics, capstone project
Certification Recommendations
DeepLearning.AI Generative AI with LLMs — Coursera
Hugging Face NLP Course — Free, practical
Google Cloud Generative AI — Vertex AI
Fast.ai Practical Deep Learning — Free, hands-on
Final Challenge: Build a complete generative AI project of your choice. Document the problem, approach, architecture, training process, results, and ethical considerations. Deploy a demo (Streamlit, Gradio, or Hugging Face Spaces). Share your project with the community!
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