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Generative AI with LangChain
Duration
1 Day
Course
PP-DSGE-101
Available Formats
Classroom Training, Online Training
Course Description
Overview
ChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This course discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Bard. It also demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this course will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.Objectives
Topics
- Introducing generative AI
- Understanding LLMs
- What are text-to-image models?
- What can AI do in other domains?
- Going beyond stochastic parrots
- What is LangChain?
- Exploring key components of LangChain
- How does LangChain work?
- Comparing LangChain with other frameworks
- How to set up the dependencies for this book
- Exploring API model integrations
- Exploring local models
- Building an application for customer service
- Mitigating hallucinations through fact-checking
- Summarizing information
- Extracting information from documents
- Answering questions with tools
- Exploring reasoning strategies
- What is a chatbot?
- Understanding retrieval and vectors
- Loading and retrieving in LangChain
- Implementing a chatbot
- Moderating responses
- Developing Software with Generative AI
- Software development and AI
- Writing code with LLMs
- Automating software development
- The impact of generative models on data science
- Automated data science
- Using agents to answer data science questions
- Data exploration with LLMs
- Conditioning LLMs
- Fine-tuning
- Prompt engineering
- How to get LLM apps ready for production
- How to evaluate LLM apps
- How to deploy LLM apps
- How to observe LLM apps
- The current state of generative AI
- Economic consequences
- Societal implications
- The road ahead
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Please take a moment to fill out this form. We will get back to you as soon as possible.
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