Applied Generative AI and Natural Language Processing

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