Lang Chain for LLM Application Development Training

Live Online & Classroom Enterprise Training

The "Lang Chain for LLM Application Development" course, offered by DeepLearning.AI, provides a concise introduction to leveraging the Lang Chain framework for developing applications powered by Large Language Models (LLMs).

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What is Lang Chain for LLM Application Development Course about?

This course is designed to provide a comprehensive understanding of Lang Chain, a powerful framework for developing applications that leverage Large Language Models (LLMs). Participants will learn how to integrate LLMs into real-world applications by using Lang Chain’s tools and features for chaining prompts, managing memory, accessing external data, and deploying scalable solutions. The course blends theory and hands-on practice to empower learners to create robust, intelligent, and efficient language-based applications.

What are the objectives of Lang Chain for LLM Application Development Course ?

Build modular and scalable NLP applications using Lang Chain’s chaining techniques.
Implement memory capabilities to retain and utilize context in conversations or workflows.
Integrate external data sources, such as APIs and databases, to enhance LLM capabilities.
Deploy Lang Chain-based applications on cloud platforms with scalability and efficiency.
Develop innovative use cases for LLMs in domains like customer support, content generation, and data analysis.

Who is Lang Chain for LLM Application Development Course for?

AI Developers and Engineers: Professionals looking to harness Lang Chain for creating advanced LLM applications.
Data Scientists and Machine Learning Practitioners: Individuals aiming to extend the capabilities of LLMs in practical settings.
Solution Architects: Professionals designing enterprise-level applications powered by AI.
Tech Enthusiasts: Learners eager to explore cutting-edge LLM tools and frameworks for development.

What are the prerequisites for Lang Chain for LLM Application Development Course?

Basic understanding of Machine Learning and NLP concepts.
Familiarity with Python programming.
Prior experience working with API’s and cloud platforms is recommended, but not mandatory

Available Training Modes

Live Online Training

2 Days

Self-Paced Training

16 Hours

Course Outline Expand All

Expand All

Module 1: Introduction to LangChain

Overview of LangChain and its role in LLM application development

Key concepts: Prompt chaining, memory, and external integrations

Setting up the development environment

Module 2: Prompt Engineering and Chaining

Fundamentals of prompt engineering

Techniques for chaining prompts to create multi-step workflows

Hands-on lab: Developing a simple chain-based NLP application

Module 3: Memory Management

Types of memory in LangChain (short-term, long-term, and entity-based)

Building applications with memory retention for context-aware responses

Hands-on lab: Implementing conversational memory in a chatbot

Module 4: Integrating External Data Sources

Connecting LangChain with APIs, databases, and other external tools

Using LangChain to query and process unstructured data

Hands-on lab: Building a knowledge retrieval system with LangChain

Module 5: Advanced Techniques in LangChain

Fine-tuning chains for performance and scalability

Working with custom tools and components

Real-world case studies: Applications powered by LangChain

Module 6: Deploying LangChain Applications

Best practices for deploying applications on cloud platforms

Managing and scaling LLM workloads

Hands-on lab: Deploying a LangChain-based solution on Azure or AWS

Module 7: Ethics and Best Practices

Addressing biases in LLM applications

Ensuring privacy and security in AI workflows

Best practices for developing ethical AI applications

Who is the instructor for this training?

The trainer for this Lang Chain for LLM Application Development Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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