LangChain: Building AI-Powered Applications Training Course
LangChain is an open-source framework engineered to streamline the creation of applications leveraging large language models (LLMs).
Delivered by an instructor either online or on-site, this training is tailored for intermediate developers and software engineers seeking to develop AI-driven applications using the LangChain framework.
Upon completion of this training, participants will be equipped to:
- Grasp the core principles of LangChain and its constituent parts.
- Integrate LangChain with leading large language models (LLMs) such as GPT-4.
- Construct modular AI applications utilizing LangChain.
- Resolve common challenges within LangChain-based applications.
Course Format
- Engaging lectures paired with open discussions.
- Extensive exercises and practical drills.
- Real-world implementation within a live-lab setting.
Customization Options
- For bespoke training arrangements regarding this course, please reach out to us to make the necessary arrangements.
Course Outline
Introduction to LangChain
- Overview of LangChain’s role and objectives
- Configuring the development workspace
Grasping Large Language Models (LLMs)
- Distinguishing LLMs from conventional models
- Assessing the strengths and constraints of LLMs
LangChain Components and Structure
- Identifying the essential elements of LangChain
- Analyzing the system architecture and operational flow
Combining LangChain with LLMs
- Linking LangChain to LLMs like GPT-4
- Designing chains for designated tasks
Constructing Modular Applications
- Developing distinct modules using LangChain
- Leveraging components across multiple projects
Practical LangChain Exercises
- Live coding workshops
- Building demonstration projects with LangChain
Advanced Features in LangChain
- Investigating higher-level capabilities
- Adapting LangChain for intricate scenarios
Best Practices and Design Patterns
- Recommended coding standards in LangChain
- Architectural patterns for AI-integrated applications
Resolving Issues
- Recognizing frequent problems in LangChain projects
- Application of debugging methods and fixes
Conclusion and Future Steps
Requirements
- Foundational proficiency in Python programming
- Acquired knowledge of AI concepts and large language models
Target Audience
- Software Developers
- Software Engineers
- Enthusiasts of Artificial Intelligence
Open Training Courses require 5+ participants.
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