82% Off LangChain- Develop LLM powered applications with LangChain | Udemy Review & Coupon

LangChain can be learned by developing a generative AI application using LLM in Python.

This course covers:

This course on LangChain- Develop LLM-powered applications with LangChain is an invaluable resource for anyone looking to learn how to develop LLM-powered applications. The course includes 4.5 hours of on-demand video, 4 downloadable resources, full lifetime access, access on mobile and TV, as well as a certificate of completion upon successful completion of the course.

What you'll learn

The LangChain Learning Experience will provide an in-depth exploration into the technology powering the popular generative AI applications. This comprehensive tutorial program will include instruction on Chain of Thought, ReAct, Few Shot prompting as well as how to navigate within LangChain’s open source codebase. Those attending this course will fully understand the theory behind large language models for software engineers and learn ways to maximize the benefit from using LangChain.

In addition, attendees of this course will become proficient in using all aspects of the platform including Chains, Agents, Vectorstores, DocumentLoader, TextSplitter, OutputParser and Memory. Each topic area are essential components to successful operation of LangChain which is why experienced instructors have been selected to guide those wishing to increase their skillset on how best utilize this powerful AI platform. After completion of the program all participants walk away with a working knowledge not only on how to use but also develop applications utilizing LangChain technology.

About Instructor

Eden Marco is a Software Engineer with extensive experience in back-end development. He previously worked as one of the first engineers at Orca Security and is currently employed as a customer engineer at Google Cloud.

The person has a Bachelor of Science degree in Computer Science from the Technion - Israel Institute of Technology.

He teaches CS courses, including Functional Programming and Introduction to CS, at Reichman University in Israel, and has a passion for teaching and mentorship.

Requirements

This course is not meant for those without software engineering knowledge. Students are assumed to have the basics down in terms of their software engineering skillset. They should be familiar with leading industry tools such as git, python, pipenv and have a good understanding of topics such as classes and testing.

Having a more solid knowledge of these topics will be essential as this course gives minimal guidance on the fundamentals. The focus here lies on more of an intermediate level where students will be applying their core principles into practical projects. Each project comes with its own set of challenges that they can use to expand their current knowledge and mastery of engineering practices. With this foundation already in place, the challenge won't only come from the material itself but from mastering comprehensive solutions to difficult situations that could present themselves throughout the course.

Description

This LangChain Udemy course is the perfect choice for people interested in leveraging to power of LLM applications. Throughout this course, participants will be taken through a journey from the basics of LangChain library to building a complete application using LlM capabilities. The final project will involve scraping the internet for information about a name and generating custom ice breakers as conversation starters.

The expansive lecture topics covered in this course include different aspects of LangChain, its history, API and use cases which provide students with an all-encompassing knowledge base to draw upon when creating their own projects. Each lesson is designed to equip participants with the required skills and information necessary for them to gain proficiency in the subject matter.

This course will guide you in developing a functional LLM powered application using LangChain, starting from the basics. The application has been developed to gather information from the internet based on a provided name, and create personalized ice breakers for initiating a conversation with the individual.

The course covers the following topics: LangChain, History

LLMs is a technique involving Few Shots Promping, Chain of Thought and ReAct Promping.

Chat Models, Prompts

PromptTemplates, Output Parsers

The following are chain types: LLMChain, SequentialChain, RetrievalQA chain.

Agents, Custom Agents

Memory

Tools, Toolkits

Vectorstores (Pinecone)

TextSplitters, DocumentLoaders

Streamlit (for UI)

During the course, practical exercises and tangible projects will be utilized to strengthen comprehension of the covered concepts and techniques. Upon completion of the course, you will have the skills to effectively utilize LangChain in order to develop LLM applications that are powerful, efficient, and versatile, suitable for various purposes.

It should be noted that this course is not designed for individuals who are new to the subject. Prior knowledge in software engineering and proficiency in Python are prerequisites for this course.

This course is intended for:

This course is designed for Software Engineers, Backend Developers, and Fullstack engineers that want to learn how to build Generative AI based applications with LangChain. This course will cover the fundamentals of using LangChain in developing fully-functioning AI solutions, ranging from natural language processing (NLP) to data generation and machine learning algorithms. For Software Engineers, this course will provide them with the know-how necessary to construct end-to-end software solutions with generative AI. For Backend Developers, this course will teach how to develop backends for complex AI systems by creating applications utilizing the integrated LangChain services. Finally, for Fullstack engineers, this course will introduce users on how to create middleware for complex interactions between front-ends and backends utilising AI through LangChain platforms and APIs.