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Course Description

 

LangChain for Business: Building LLM (Large Language Models) Applications for Real-World Problems

 

Unleash the Power of Large Language Models with LangChain

Embrace the next frontier of AI (Artificial Intelligence) development with LangChain, the groundbreaking framework that empowers you to harness the full potential of large language models (LLMs).

In this comprehensive course, you will master the art of building intelligent applications using LangChain, gaining hands-on experience in creating chatbots, question answering systems, and more.

No prior experience with LLMs or LangChain is required. Whether you are a seasoned developer or a curious newcomer, this course will equip you with the skills and knowledge to become a LangChain expert.

Objectives

 

The program aims to ensure that anyone can actively participate in our AI-powered future. It provides a valuable opportunity for individuals from various backgrounds and levels of expertise to learn about and effectively utilize generative AI. By equipping learners with the necessary knowledge and skills, this course enables them to harness the potential of generative AI and contribute to its advancement in a collaborative and inclusive manner.

Audience

 

Developers interested in building AI applications with LLMs.

Anyone curious about the future of AI and the role of LLMs.

Prerequisites

 

Anyone can attend the course.

Content

     

 Introduction to LangChain

 

                  1. Introduction to LangChain

                  2. Evolution of LangChain

                  3. Importance in Business

                  4. Real-World Applications

                  5. LangChain vs. Traditional Language Models

                  6. Challenges and Solutions

                  7. Module Summary and Key takeaways

                  LAB: 1 Introduction to Langchain

 

      Fundamentals of LangChain

 

                  1. Understanding Nodes in LangChain

                  2. The Concept of Chains

                  3. Command Processing in LangChain

                  4. Integration with Existing Systems

                  5. Customizing LangChain for Business Needs

                  6. LangChain’s Scalability

                  7. Data Handling and Privacy in LangChain

                  8. Error Handling and Debugging in LangChain

                 9. Extending LangChain with Custom Nodes

                 10. Performance Optimization in LangChain

                 11.  LangChain’s Application in Different Industries

                 12.  Future Developments in LangChain

                 13.  Best Practices for Implementing LangChain

                 14.  Recap and Key Takeaways

                 LAB: 2 Prompting and Parsing

                 LAB: 3 Prompt Templating

 

      Building Intelligent Systems 

 

               1. Building Composable Pipelines with Chains

               2. Conversational Memory

               3. Retrieval Augmentation

               4. AI Agents

               LAB: 4 Memory

               LAB: 5 LangChain Chains

               LAB: 6 Langchain Documents Loaders

               LAB: 7 Langchain Agents

 

      Implementing LangChain in Business Operations

 

              1. Introduction to Module 4

              2. Benefits of Implementing LangChain

              3. Steps for Successful Implementation

              4. Case Studies

              5. Best Practices

              6. Cultural Sensitivity

              7. Security and Compliance

              8. Training and Skill Development

              9. Monitoring and Continuous Improvement

              10. Challenges and Solutions

              11. Future Trends

               LAB: 8 Vector DataBases and Advanced Retrieval

 

     Case Studies and Best Practices

 

        1. Insightful Journey: Understanding real-world implications and strategies behind    successful LangChain implementations.

            2. Diverse Industries: In-depth case studies from E-commerce, Financial Services, and Healthcare.

            3. Learning Objectives: Gain insights into challenges and innovative approaches, and extract best practices for your own business applications.

            4. Module Goal: Equip with practical knowledge and actionable insights for leveraging LangChain technology in business.

          Course Wrap-up

          Summary of Key Concepts

          Case Studies Revisited

          Practical Applications

          Future of LangChain in Business

          Project: Building Chat Bot with Langchain