Course Outline
Introduction to LangChain
- Overview of LangChain and its purpose
- Setting up the development environment
Understanding Large Language Models (LLMs)
- LLMs vs traditional models
- Capabilities and limitations of LLMs
LangChain Components and Architecture
- Core components of LangChain
- Understanding the architecture and workflow
Integrating LangChain with LLMs
- Connecting LangChain to LLMs like GPT-4
- Building chains for specific tasks
Building Modular Applications
- Creating modular components with LangChain
- Reusing components across different applications
Practical Exercises with LangChain
- Hands-on coding sessions
- Developing sample applications using LangChain
Advanced LangChain Features
- Exploring advanced functionalities
- Customizing LangChain for complex use cases
Best Practices and Patterns
- Coding best practices with LangChain
- Design patterns for AI-powered applications
Troubleshooting
- Identifying common issues in LangChain applications
- Debugging techniques and solutions
Summary and Next Steps
Requirements
- Basic knowledge of Python programming
- Familiarity with AI concepts and large language models
Audience
- Developers
- Software engineers
- AI enthusiasts
Delivery Options
Private Group Training
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- Pre-course call with your trainer
- Customisation of the learning experience to achieve your goals -
- Bespoke outlines
- Practical hands-on exercises containing data / scenarios recognisable to the learners
- Training scheduled on a date of your choice
- Delivered online, onsite/classroom or hybrid by experts sharing real world experience
Private Group Prices RRP from €4560 online delivery, based on a group of 2 delegates, €1440 per additional delegate (excludes any certification / exam costs). We recommend a maximum group size of 12 for most learning events.
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Public Training
Please see our public courses