Master LangChain & Gen AI -Build #16 AI Apps HuggingFace LLM from Udemy

Are you interested in harnessing the power of AI to create groundbreaking language-based applications?

Look no further than LangChain and Gen AI - a comprehensive course that will take you from a novice to an expert in no time.

Implement Generative AI (GenAI) apps with langchain framework using different LLMs.

By implementing AI applications powered with state-of-the-art LLM models like OpenAI and Hugging Face using Python, you will embark on an exciting project-based learning journey.

With LangChain, you will gain the skills and knowledge necessary to develop innovative LLM solutions for a wide range of problems.

Here are some of the projects we will work on:

Project 1: Construct a dynamic question-answering application with the unparalleled capabilities of LangChain, OpenAI, and Hugging Face Spaces.

Project 2: Develop an engaging conversational bot using LangChain and OpenAI to deliver an interactive user experience.

Project 3: Create an AI-powered app tailored for children, facilitating the discovery of related classes of objects and fostering educational growth.

Project 4: Build a captivating marketing campaign app that utilizes the persuasive potential of well-crafted sales copy, boosting sales and brand reach.

Project 5: Develop a ChatGPT clone with an added summarization feature, delivering a versatile and invaluable chatbot experience.

Project 6: MCQ Quiz Creator App - Seamlessly create multiple-choice quizzes for your students using LangChain and Pinecone.

Project 7: CSV Data Analysis Toll - Helps you analyze your CSV file by answering your queries about its data.

Project 8: Youtube Script Writing Tool - Effortlessly create compelling YouTube scripts with this user-friendly and efficient script-writing tool.

Project 9 - Support Chat Bot For Your Website - Helps your visitors/customers to find the relevant data or blog links that can be useful to them.

Project 10 - Automatic Ticket Classification Tool - The Automatic Ticket Classification Tool categorizes support tickets based on content to streamline ticket management and response processes.

Project 11 - HR - Resume Screening Assistance - HR project using AI to assist in screening resumes, optimizing the hiring process with smart analysis and recommendations

Project 12 - Email Generator using LLAMA 2- The Email Generator is a tool that automatically creates customized emails, saving time and effort in crafting personalized messages.

Project 13 - Invoice Extraction Bot using LLAMA 2- Invoice Extraction Bot: AI-powered tool that extracts key details from invoices accurately and efficiently. Simplify your data entry process.

Project 14 - Text to SQL Query Helper Tool: Convert natural language text into structured SQL queries effortlessly using the Text to SQL Query Tool for streamlined database interaction and data retrieval.

Project 15 - Customer Care Call Summary Alert - Concise notification highlighting key points and outcomes from recent customer service calls, aiding quick understanding and response

This course is designed to provide you with a complete understanding of LangChain, starting from the basics and progressing toward creating practical LLM-powered applications.

LangChain empowers programmers to fully utilize large language models, such as ChatGPT, pinecone This integration enhances the models' ability to comprehend and respond to human language.

Built with Python, LangChain offers a user-friendly interface tailored specifically for beginners, making it accessible to aspiring developers.

Course Overview:

Aspiring to build sophisticated language-based applications

LangChain is the perfect library for you.

Move beyond basic techniques like keyword matching or rule-based systems and maximize your reach by langchain.

Leverage the power of LLMs, and applications using LangChain and combine them with cognitive or information sources & pinecone.

Unlock tremendous potential and explore new possibilities with applications using LangChain and Pinecone.

Course Contents:

LangChain

LLMs

Chat Models

Prompts

Indexes

Chains

Agents

Memory

Google Gemini Pro

But this isn't just a theory-based course; it's a hands-on experience. You will engage in practical activities and real-world projects, reinforcing your understanding of these concepts and techniques.

By the end of the course, you will be equipped with the skills to apply Langchain effectively, building robust, pinecone, powerful, and scalable LLM applications for various purposes.

Don't miss this opportunity to become a language model expert.

Enroll in the LangChain course and embark on a transformative journey that will elevate your AI app development skills. LangChain , OpenAI , Chat

Get ready to unlock your full potential and become a hero in the world of language-based AI development through langchain.

You will do practical activities and real-world projects throughout the applications using LangChain pinecone Google Gemini Pro course to strengthen your understanding of the concepts and techniques.

You will be competent in applying Langchain pinecone to build strong, effective, and scalable LLM applications for a variety of uses by the end of the course.

What's inside

Learning objectives

Develop langchain based ai apps
Implement llm powered apps

Learn langchain from end to end
Complete project based approach

Develop langchain based ai apps
Implement llm powered apps
Learn langchain from end to end
Complete project based approach

Syllabus

Gen AI and LangChain Introduction

What You'll Get In This Course

Generative AI Introduction

What is LangChain?

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Uses LangChain, OpenAI, and Hugging Face, which are valuable tools for developing AI applications and are widely used in the field

Includes projects such as building a ChatGPT clone and a marketing campaign app, which are relevant to current industry trends

Covers Google Gemini Pro, which is a cutting-edge language model that can enhance the capabilities of AI applications

Requires learners to generate API keys for OpenAI and Hugging Face, which may present a barrier to some learners

Teaches Pinecone, which is a vector database that may require a subscription or fees for certain levels of usage

Features beginner, intermediate, and advanced level projects, which may be too broad for some learners

Reviews summary

Project-based langchain & gen ai

According to students, this course offers a highly practical and project-driven approach to learning LangChain and Generative AI. Learners particularly appreciate the opportunity to build 16 distinct AI applications, finding this hands-on experience invaluable for applying concepts with various LLMs like OpenAI, Hugging Face, and Gemini Pro. While the breadth of topics and projects is a major strength, a few reviewers noted the challenge of keeping pace with the rapidly evolving libraries and APIs in the field, sometimes requiring extra effort to troubleshoot code. Overall, the course is seen as providing a solid foundation for developing real-world AI applications.

Covers multiple tools and LLMs effectively.

"Appreciated the coverage of OpenAI, Hugging Face, and Google Gemini Pro, plus tools like Streamlit and Pinecone."

"Getting exposure to different LLMs within the projects was very valuable."

"The course touches upon various LangChain modules like Chains, Agents, and Memory through practical examples."

"Provides a good overview of the ecosystem needed to build full AI apps."

Excellent for applying LangChain concepts.

"This course really helped me move from theory to practice with LangChain. I feel confident building apps now."

"I learned practical skills using LangChain with OpenAI, Hugging Face, and Streamlit. Highly recommend for implementation."

"The course focuses on *doing*, which is exactly what I needed to get started with Gen AI applications."

"It provides great examples for integrating different LLMs and tools effectively."

Hands-on learning through building many apps.

"The project-based approach is fantastic; building 16 different applications really cemented my understanding of LangChain."

"I chose this course because of the sheer number of projects, and they delivered! Very practical."

"Having 16 diverse projects covering different use cases is the course's biggest strength."

"Building a chatbot clone and a marketing campaign app was very helpful for seeing practical uses."

Better suited for those with some Python/AI basics.

"Although it mentions 'novice', having a solid Python background is really necessary to keep up with the coding."

"Some prior understanding of AI or ML concepts is beneficial, as the course jumps quickly into application."

"Might be challenging for absolute beginners with no prior coding experience."

"I found that brushing up on Python and basic API calls helped me a lot before starting."

Libraries change fast, code needs adjustments.

"Be prepared to troubleshoot; the LangChain library and APIs change frequently, which means some code needs updating."

"While the concepts are clear, the fast pace of AI development means some specific library functions might be deprecated or changed."

"Staying current with the code required me to consult documentation outside the course."

"Some projects required minor tweaks due to library versioning issues."

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 Master LangChain & Gen AI -Build #16 AI Apps HuggingFace LLM with these activities:

Review Python Fundamentals

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Reinforce your understanding of Python syntax, data structures, and control flow to prepare for building LangChain applications.

Browse courses on Python

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Review basic Python syntax and data types.
Practice writing functions and classes.
Work through basic Python exercises on platforms like HackerRank or LeetCode.

Brush Up on Hugging Face Transformers

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Familiarize yourself with the Hugging Face Transformers library, which is used extensively in the course for working with pre-trained language models.

Browse courses on Hugging Face Transformers

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Explore the Hugging Face documentation.
Run example code snippets using pre-trained models.
Understand the basics of tokenization and model inference.

Read 'Natural Language Processing with Python'

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Gain a deeper understanding of NLP fundamentals to better grasp the concepts behind LangChain and generative AI.

View Natural Language Processing with Python:... on Amazon

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Read the chapters on text processing and feature extraction.
Experiment with the NLTK library for basic NLP tasks.
Relate the concepts to the applications covered in the course.

Five other activities

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Show all eight activities

Experiment with OpenAI API

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Practice using the OpenAI API to generate text, translate languages, and answer questions, reinforcing your understanding of how to interact with LLMs.

Browse courses on OpenAI API

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Obtain an OpenAI API key.
Use the API to generate text from different prompts.
Explore different API parameters like temperature and max tokens.

Build a Simple Chatbot with LangChain

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Create a basic chatbot using LangChain to solidify your understanding of the framework and its components.

Browse courses on LangChain

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Set up a LangChain environment.
Define a simple conversation flow.
Integrate with a language model like GPT-3.
Test and refine the chatbot's responses.

Read 'Generative Deep Learning'

Show steps

Explore the theoretical underpinnings of generative AI to enhance your understanding of the models used in LangChain.

View Generative Deep Learning 2nd Edition... on Amazon

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Read the chapters on GANs and VAEs.
Understand the mathematical principles behind these models.
Relate the concepts to the generative AI applications covered in the course.

Write a Blog Post on LangChain

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Write a blog post explaining the key concepts of LangChain and its applications to reinforce your understanding and share your knowledge with others.

Browse courses on LangChain

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Choose a specific aspect of LangChain to focus on.
Research and gather information on the topic.
Write a clear and concise explanation of the concepts.
Include examples and code snippets to illustrate the ideas.
Publish the blog post on a platform like Medium or your personal website.

Contribute to a LangChain Project

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Contribute to an open-source LangChain project to gain practical experience and collaborate with other developers.

Browse courses on LangChain

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Find a LangChain project on GitHub.
Identify an issue or feature to work on.
Fork the repository and create a branch.
Implement the changes and submit a pull request.
Respond to feedback and revise the code as needed.

Career center

Learners who complete Master LangChain & Gen AI -Build #16 AI Apps HuggingFace LLM will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Engineer

A Natural Language Processing Engineer specializes in creating algorithms that enable computers to understand, interpret, and generate human language. The core of this course is in alignment with the work of an NLP Engineer. The course dives deeply into LangChain, which is a library that is particularly useful for developing NLP applications. The multiple projects in this course all directly relate to natural language processing. Learning to build question-answering systems, chat bots, and text-analysis tools, for example, are all relevant. This course helps one learn all of the necessary skills required for a career as an NLP Engineer.

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

AI Application Developer

An AI Application Developer designs and builds AI-powered applications, and this course is very relevant for a person in this role. The course provides practical, hands-on experience creating AI applications using LangChain and LLMs. The various projects that are completed in this course directly align with the kind of work an AI Application Developer does. Building question-answering bots, chatbots, and data analysis tools are all practical applications that an AI Application Developer will work on. This course helps one build a strong portfolio of AI applications.

See salaries and explore the career path for AI Application Developer

Chatbot Developer

The core task of a Chatbot Developer is to design and implement conversational AI systems that interact with users, and this course is useful towards this. The course provides hands-on experience building chatbots using LangChain and LLMs, which are critical tools in the field. The projects in the course include building multiple different types of conversational bots, allowing one to gain practical experience in this field. This course is particularly useful for learning how to build chatbots that provide interactive user experiences. The course allows learners to master a variety of chatbot development techniques.

See salaries and explore the career path for Chatbot Developer

Generative AI Specialist

A Generative AI Specialist focuses on the development and implementation of generative models, and this course may be useful. This course helps an aspiring Generative AI Specialist learn to use LangChain to build practical applications with generative AI models. The hands-on projects, like creating marketing campaign apps, email generators, and summarization tools, provides practical experience with these. The course covers a range of generative AI applications, which is essential for anyone specializing in this field. The variety of projects will help one build a robust portfolio.

See salaries and explore the career path for Generative AI Specialist

Machine Learning Engineer

A Machine Learning Engineer focuses on creating and implementing machine learning models, and this course may be useful for those interested in this career. The course focuses on building applications with large language models using LangChain, which is a core skill for a Machine Learning Engineer working with natural language processing. The project-based approach, including developing apps such as a ChatGPT clone, will help advance one's practical skills. The course's focus on implementation using Python is also valuable, as its a language commonly used in machine learning.

See salaries and explore the career path for Machine Learning Engineer

Artificial Intelligence Engineer

An Artificial Intelligence Engineer designs, develops, and deploys AI solutions, and this course may be helpful for those looking to enter this field. The course provides hands-on experience with LangChain and LLMs, essential tools for AI application development, and helps build a foundation for working with language-based AI. Projects like building question-answering apps and conversational bots are directly applicable to the work of an AI Engineer, and the course covers practical implementation using Python, also vital for this role. The course helps facilitate more sophisticated language-based applications, something that is a growing need in AI engineering.

See salaries and explore the career path for Artificial Intelligence Engineer

Data Scientist

A Data Scientist analyzes complex data to derive insights, and this course may be useful for those in this role. The course provides experience in building AI applications that can be used to analyze text data, which is a useful skill for data scientists. The course projects, such as the CSV data analysis and the text-to-SQL query tool, will be very useful for a data scientist looking to expand their skill set. This course provides a strong foundation for integrating AI tools into data science workflows. Learning to work with LangChain will be helpful for a data scientist.

See salaries and explore the career path for Data Scientist

Software Developer

A Software Developer creates and maintains software applications, and this course is useful for those looking for a career in this role. This course offers a project-based learning approach to build AI applications, which helps aspiring software developers gain experience. This course provides practical experience working with Python, LLMs, and LangChain. These are all relevant technologies for a software developer working on AI-driven projects. Building multiple AI applications using LangChain will help a software developer build their skills.

See salaries and explore the career path for Software Developer

Data Analyst

A Data Analyst interprets data to identify trends and patterns, and this course may be useful. The course helps one learn to build AI-powered tools for analyzing data, such as the CSV data analysis tool provided in this course. The course projects help build a foundation in the use of AI to extract information from text-based data which is helpful for a data analyst to know. This course provides a good introduction to using natural language processing AI techniques for data analysis. The methods taught will be quite useful in a data analyst's workflow.

See salaries and explore the career path for Data Analyst

Solutions Architect

A Solutions Architect designs and oversees the implementation of technical solutions, and this course may be useful. The course helps one understand practical applications of AI and large language models. The course’s hands-on projects provide a broader understanding of how AI applications can be built and deployed. This course will be helpful for a Solutions Architect looking to add AI-based solutions to their portfolio, since it covers a variety of AI applications using LangChain. An architect might use this to better understand the technology.

See salaries and explore the career path for Solutions Architect

AI Product Manager

An AI Product Manager defines the strategy and roadmap for AI-driven products, and this course may be useful. The course introduces the practical aspects of developing AI applications using LangChain and LLMs. The hands-on projects help provide insight into the capabilities and limitations of AI technologies. This course may help a Product Manager better communicate with engineering teams and envision the potential for AI applications. This course will help them understand the process of AI development. The projects offer exposure to real-world AI applications.

See salaries and explore the career path for AI Product Manager

Research Scientist

A Research Scientist conducts research to advance scientific knowledge, and this course may be of interest to them. The course provides a practical understanding of LangChain and LLMs, which may be useful for those doing research in the field of language processing. The project-based learning will help expand one’s understanding of how these technologies can be implemented. For someone looking to research applications of language models, this course will be valuable. It may help a Research Scientist build a strong foundation for their work.

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Technical Consultant

A Technical Consultant provides expert advice on technology solutions, and this course may be useful. The course provides experience building various AI applications using LangChain and LLMs. It will help a Technical Consultant who wishes to understand the practical implications of these technologies. The course’s project-based approach demonstrates the development and implementation of various use cases for AI. This course will broaden a Technical Consultant's portfolio of expertise in the AI domain. It may be particularly useful for someone advising on natural language solutions.

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Technical Writer

A Technical Writer creates documentation for technical products, including those related to AI, and this course may be useful. By taking the course, a Technical Writer gains deeper insights into the underlying technologies, such as LangChain and LLMs. This course allows one to understand how these AI systems are constructed and their real-world applications. This course may be useful for any technical writer who is looking to expand their expertise in the area of AI. Understanding the core functionality of the tools will be helpful in writing documentation.

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AI Ethicist

An AI Ethicist examines the ethical implications of AI technologies, and this course may be useful as an introduction. The course provides practical experience building various AI applications using LangChain. A practical understanding of how AI systems work will provide one with a well-rounded background for their work. The projects in the course illustrate the impact of these technologies. This course may help an AI Ethicist better understand the potential risks of these technologies. Understanding these systems is a first step toward studying their ethics.

See salaries and explore the career path for AI Ethicist

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Master LangChain & Gen AI -Build #16 AI Apps HuggingFace LLM.

Generative Deep Learning

Save

Dives deep into the world of generative models, including GANs, VAEs, and autoregressive models. It provides a strong theoretical foundation for understanding how these models work and how they can be used to generate new data. While the course focuses on practical applications, this book offers valuable insights into the underlying technology. This book is commonly used as a textbook at academic institutions.

(中文) Generative Deep Learning 2nd Edition...

Paperback

$$$$

Natural Language Processing with Python

Save

Provides a solid foundation in NLP concepts and techniques using Python. It covers topics like text processing, classification, and information extraction. While not directly focused on LangChain, it provides valuable background knowledge for understanding the underlying principles of language models. This book is more valuable as additional reading than it is as a current reference.

Natural Language Processing with Python: Analyzing...

Paperback

$$$

Natural Language Processing with Python: Analyzing...

Kindle Edition

Master LangChain & Gen AI -Build #16 AI Apps HuggingFace LLM

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Project-based langchain & gen ai

Activities

Career center

Reading list

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