LangChain- Develop LLM powered applications with LangChain from Udemy

COURSE WAS RE-RECORDED ON MID APRIL 2024- LangChain Version 0.1.16

Welcome to first LangChain Udemy course - Unleashing the Power of LLM. This comprehensive course is designed to teach you how to QUICKLY harness the power the LangChain library for LLM applications. This course will equip you with the skills and knowledge necessary to develop cutting-edge LLM solutions for a diverse range of topics.

Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python. I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts .In this course, you will embark on a journey from scratch to building a real-world LLM powered application using LangChain. We are going to do so by build 3 main applications:

Ice Breaker- LangChain agent that given a name, searches in google to find Linkedin and twitter profiles, scrape the internet for information about a name you provide and generate a couple of personalized ice breakers to kick off a conversation with the person.
Documentation Helper- Create chatbot over a python package documentation. (and over any other data you would like)
A slim version of ChatGPT Code-Interpreter

The topics covered in this course include:

LangChain
History
LLMs: Few shots prompting, Chain of Thought, ReAct prompting
Chat Models
Prompts, PromptTemplates
Output Parsers
Chains: SequentialChain, LLMChain, RetrievalQA chain
Agents, Custom Agents, Python Agents, CSV Agents, Agent Routers
OpenAI Functions
Tools, Toolkits
Memory
Vectorstores (Pinecone, FAISS)
DocumentLoaders, TextSplitters
Streamlit (for UI)
LCEL
LangSmith

Throughout the course, you will work on hands-on exercises and real-world projects to reinforce your understanding of the concepts and techniques covered. By the end of the course, you will be proficient in using LangChain to create powerful, efficient, and versatile LLM applications for a wide array of usages.This is not just a course, it's also a community. Along with lifetime access to the course, you'll get:

Dedicated 1 on 1 troubleshooting support with me
Github links with additional AI resources, FAQ, troubleshooting guides
Access to an exclusive Discord community to connect with other learners (5000+ members)
No extra cost for continuous updates and improvements to the course

This course assumes that you have a background in software engineering and are proficient in Python. I will be using Pycharm IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts.

The first project of the course (Ice-Breaker) requires usage of 3rd party APIs-ProxyURL, SerpAPI, Twitter API which are generally paid services.All of those 3rd parties have a free tier we will use to create stub responses development and testing.

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Develops skills and knowledge in using LLM for real-world applications, which is highly relevant to industry

Builds a strong foundation for beginners in using LLM

Taught by instructors who are recognized for their work in LLM

Includes hands-on labs and interactive materials

Requires proficiency in Python, which may be a barrier for some learners

Relies on third-party APIs which may require paid subscriptions

Reviews summary

Comprehensive and updated langchain development course

According to students, this course offers a highly comprehensive and practical approach to developing LLM applications with LangChain. Learners praise the project-based learning and the instructor's exceptional responsiveness and support, especially on Discord. A significant number of recent reviews highlight that the course has been re-recorded in April 2024 to LangChain v0.1.16, effectively addressing previous concerns about outdated code and breaking changes. This update has made the content current and highly relevant, leading to a largely positive reception. It is explicitly stated that the course assumes a strong background in Python and software engineering.

Not for beginners; requires proficiency in Python and software engineering.

"Overall, a great course if you want to develop LLM applications with LangChain and you already have a good understanding of Python."

"This course assumes that you have a background in software engineering and are proficient in Python."

Covers a wide range of LangChain features, explained simply.

"The instructor is brilliant, he explains the difficult concepts in a simple manner that is easy to understand."

"It’s incredible how the instructor made the course so comprehensive, yet easy to understand."

"It covered every LangChain feature I wanted to learn and even more."

Instructor provides exceptional 1-on-1 support and is highly responsive.

"The best part is the support from the instructor on Discord, he is always responsive and helpful."

"I loved the content, the practical applications and most of all the support I got from the instructor on Discord."

"The instructor is very good, he is very communicative and responsive, and he helps with any questions or issues with the code."

Features practical, project-based learning with real-world application.

"The content is very practical and I love that the course is project-based so I could have a real hands-on experience and apply the concepts."

"It takes you through building 3 projects in the course which are very useful and will help you to build your own projects."

"The projects are great, they take you through building practical applications and teach you how to apply the concepts in real-world scenarios."

Course re-recorded in April 2024 for highly relevant v0.1.16 material.

"I saw that the course was updated/re-recorded in April. I had to re-start the entire course... Now that I have completed the course, I must say that I am impressed!"

"Best course for LangChain, especially that it was re-recorded with the new LangChain version. This is the first course that I have found to be so comprehensive and up to date."

"I started learning LangChain about a month ago and was struggling to find a good course that is kept up to date. This course... is the best I have seen so far."

Prior to April 2024, the course had issues with outdated code and API changes.

"Totally outdated. I purchased this course a few months ago... a lot of the code is outdated and does not work with the new LangChain version."

"This course is a complete waste of money and time. The code is outdated and has a lot of breaking changes."

"The content is outdated, I tried following along, but the code doesn't work. The LangChain library has updated its API, so all the examples are broken. Very frustrating."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in LangChain- Develop LLM powered applications with LangChain with these activities:

Review Python basics

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Ensure a solid understanding of Python before starting the course.

Browse courses on Python

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Review Python syntax and data structures
Practice writing simple Python programs

Read "Lady in the Water" by Emily St. John Mandel

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Review the similarities and differences in communication styles and their outcomes between The Last Hotel and Station Eleven.

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Read the book
Annotate important passages
Reflect on the book's themes

Read "The Last Hotel" by Emily St. John Mandel

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Review the similarities and differences in communication styles and their outcomes between The Last Hotel and Station Eleven.

View Sea of Tranquility: A novel on Amazon

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Read the book
Annotate important passages
Reflect on the book's themes

Five other activities

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Complete the official LangChain tutorial

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Gain hands-on experience and solidify your understanding of LangChain.

Browse courses on LangChain

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Install the LangChain library
Follow the official LangChain tutorial
Experiment with different LangChain features

Solve Leetcode 3-Sum Problem

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Practice solving and debugging coding problems.

Browse courses on Array Manipulation

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Understand the problem statement
Implement a brute force solution
Implement an optimized solution
Debug and test your code

Write a blog post about LLM applications

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Demonstrate your understanding of LLMs by writing about their applications.

Browse courses on LLM Applications

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Research LLM applications
Write the blog post
Publish and promote your blog post

Build a chatbot to simulate a customer support conversation

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Demonstrate your understanding of NLP and machine learning by building a practical application.

Browse courses on Chatbot Development

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Design the chatbot's conversation flow
Train a language model
Deploy the chatbot

Participate in a Kaggle competition

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Challenge yourself and showcase your skills by participating in a real-world competition.

Browse courses on Data Science

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Select a competition that aligns with your interests and skills
Build and submit your model
Analyze your results and learn from your experience

Career center

Learners who complete LangChain- Develop LLM powered applications with LangChain will develop knowledge and skills that may be useful to these careers:

Computational Linguist

Computational Linguists use large language models to analyze and understand human language. This course can help you create and use large language models for computational linguistic tasks.

See salaries and explore the career path for Computational Linguist

Natural Language Processing Engineer

Natural Language Processing Engineers specialize in developing and applying LLMs. This course offers the perfect foundation for a smooth entry into the field.

See salaries and explore the career path for Natural Language Processing Engineer

Artificial Intelligence Researcher

Artificial Intelligence Researchers use LLMs to develop new and innovative AI technologies. This course on LangChain will help you learn the basics of LLMs and apply them to your research.

See salaries and explore the career path for Artificial Intelligence Researcher

Machine Learning Engineer

Machine Learning Engineers use large language models to develop and deploy machine learning models. This course in LangChain can greatly help you master the fundamentals.

See salaries and explore the career path for Machine Learning Engineer

Technical Writer

Technical Writers use large language models to generate documentation, write code comments, and create training materials. This course on LangChain can help you learn how to use LLMs to improve your technical writing skills.

See salaries and explore the career path for Technical Writer

Consultant

Consultants use large language models to analyze data, identify trends, and develop solutions for clients. This course in LangChain can help you gain the skills you need to use LLMs in your consulting work.

See salaries and explore the career path for Consultant

Product Manager

Product Managers often use large language models to gather customer feedback, analyze market trends, and develop new products. This course on LangChain can help you get started with LLMs and apply them to your work.

See salaries and explore the career path for Product Manager

Business Analyst

Business Analysts use large language models to analyze data, identify trends, and develop recommendations for businesses. This course in LangChain can help you learn how to use LLMs to improve your business analysis skills.

See salaries and explore the career path for Business Analyst

Operations Manager

Operations Managers use large language models to analyze data, identify inefficiencies, and develop solutions to improve operations. This course on LangChain may be useful to you in developing operational strategies.

See salaries and explore the career path for Operations Manager

Educator

Educators use large language models to create lesson plans, develop educational materials, and provide feedback to students. This course on LangChain may be useful for you in developing lesson plans and study materials.

See salaries and explore the career path for Educator

Sales Manager

Sales Managers use large language models to analyze customer data, identify sales opportunities, and close deals. This course on LangChain may be useful to you in developing strategies and improving sales performance.

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Customer Success Manager

Customer Success Managers use large language models to analyze customer feedback, identify customer needs, and develop customer success strategies. This course on LangChain may be useful to you in developing customer success strategies.

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Marketing Manager

Marketing Managers use large language models to analyze customer data, create marketing campaigns, and track results. This course on LangChain may be useful to you in creating more sophisticated marketing campaigns.

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Data Scientist

Data Scientists use large language models to analyze data, build models, and generate insights. Taking this course on LangChain can help you master the basics of LLMs and apply them to your work.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers often use large language models in their work. This course on LangChain would help you get started in the domain.

See salaries and explore the career path for Software Engineer