What you’ll learn
- Introduction to Natural Language Processing (NLP)
- model implementation based on huggingface-models
- working with OpenAI
- Vector Databases
- Multimodal Vector Databases
- Retrieval-Augmented-Generation (RAG)
- Real-World Applications and Case Studies
- implement Zero-Shot Classification, Text Classification, Text Generation
- fine-tune models
- data augmentation
- Prompt Engineering
- Zero-Shot Promping
- Few-Shot Prompting
- Chain-of-Thought (Few-Shot CoT, Zero-Shot CoT)
- Self-Consistency Chain-of-Thought
- Prompt Chaining
- Tree-of-Thought
- Self-Feedback
- Self-Critique
- Claude 3
- Open Source Models, e.g. LLama 2, Mistral
How to Enroll Applied Generative AI and Natural Language Processing course?
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