Generative AI NLP Specialization | Level 4
Building Intelligent Solutions with Generative Al.
Type
PaidNovember 9 @ 9:00 am – 5:00 pm UTC+5:30
About the event
Join us for the exclusive “Generative AI NLP Specialization | Level 4” event—an extraordinary opportunity to explore the realm of cutting-edge AI and NLP. This event invites you to unlock the potential of Large Language Models (LLMs) for groundbreaking projects and applications.
Dive deep into revolutionary techniques such as RAG (Retrieval-Augmented Generation) and LangChain architectures. Navigate a diverse array of generative AI projects that expand your skill set and broaden your technological horizons. By participating, you’ll emerge with the expertise to craft advanced LLM-based applications harmonizing seamlessly with various platforms, ensuring responsible and impactful AI integration.
Key Takeaways
- Master RAG and LangChain architectures.
- Explore diverse generative AI projects.
- Integrate LLMs effectively into various environments.
- Oversee ethical and responsible AI implementation.
- Elevate your AI innovation capabilities.
This event is tailored for:
- Graduates of Generative AI NLP Specialization | Level 3 or equivalent.
- Developers and software engineers are curious about Generative AI.
- AI enthusiasts and professionals poised to create intelligent solutions.
- Data scientists and machine learning practitioners eager to enhance GenAI model skills.
Prerequisite:
Prior completion of Generative AI NLP Specialization | Level 3 or equivalent knowledge is recommended.
Don’t miss this chance to amplify your AI journey. Secure your spot today and be ready to reshape the future with cutting-edge Generative AI.
- RAG Architecture walk through
- Concepts for LangChain Projects
- Utilizing embeddings and vector data stores
- Enhancing LangChain performance
- LangChain Framework
- Taking LLMs out of the box
- Integrating LLMs into new environments using memories, chains, and agents
- Applications of Generative Models
- Importance and Usefulness
- Potential Applications
- Text Generation Use Cases
- Building NLP Applications using OpenAI API
- Summarization, Text Classification, and Fine-tuning GPT Models
- Generative AI Project Lifecycle
- Using LLMs in Applications
- Interacting with External Applications
- Helping LLMs Reason and Plan with Chain-of-Thought
- Program-aided Language Models
- LLM Application Architectures
- RAG Method
- Responsible AI Considerations
- Lab: Using RAG & LangChain modules – Developing a question-answering application with RAG, LangChain, OpenAI, and Hugging Face Spaces
