“AI Architects: Designing Tomorrow with LLMs and Generative Tech”

What Will You Learn?

• Foundations of Generative AI: Understand the basics of AI pipelines, transformer architectures, and how models like ChatGPT are trained.
• Data Preprocessing and Representation: Master data cleaning, vectorization, and feature extraction to build robust AI models.
• Large Language Models (LLMs): Dive into the architecture, capabilities, and training methodologies of LLMs like GPT, Falcon, and LLaMA.
• Hugging Face Mastery: Learn to utilize Hugging Face tools for model training, fine-tuning, and API integration.
• Prompt Engineering: Develop effective prompts to maximize the potential of AI models across various tasks.
• Hands-On AI Projects: Build real-world applications, including chatbots, text summarization, text-to-image generation, and text-to-speech systems.
• Vector Databases: Explore ChromaDB, Pinecone, and Weaviate for efficient data storage and retrieval in AI workflows.
• LangChain Framework: Learn to use LangChain for building multi-agent systems, memory management, and integrating open-source LLMs.
• RAG (Retrieval-Augmented Generation): Understand RAG concepts, fine-tuning, and applications for Q&A systems and document processing.
• Fine-Tuning Models: Gain expertise in fine-tuning foundation models using techniques like LoRA and QLoRA.
• LLMOps and Deployment: Discover how to manage, deploy, and scale AI applications using Google Cloud, AWS, and CICD pipelines.
• AI in Real-World Domains: Implement AI-powered solutions for industries like healthcare, finance, and e-commerce.