25% Off Learn LangChain, Pinecone & OpenAI: Build Next-Gen LLM Apps | Udemy Review & Coupon

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This course covers practical applications using LangChain, Pinecone, and OpenAI. Create web applications using Streamlit. Join the AI Revolution Today!

This course covers:

This course contains invaluable resources to help learners of all levels expand their knowledge and understanding in the subject. It includes 7.5 hours of on-demand video, 7 articles, 1 downloadable resource, access on mobile and TV, as well as a certificate of completion upon the courses end.

This comprehensive content is perfect for those looking to deepen their expertise, with an easy to digest online format that makes it convenient for any schedule or learning preference. The on-demand video allows users to watch at their own convenience and pause and rewatch anytime they want; the 7 articles provide additional reading materials for deeper exploration into concepts; and finally, the downloadable resource ensures learners have quick access to plenty of grounding information whenever they require a refresher. With access on mobile and TV devices too, this course is certainly versatile enough for students’ individual needs. Upon course completion, each participant will receive a certificate – an excellent way to mark the successful mastering of new skills! With this comprehensive package of materials in hand, learners are sure to reach greater heights in knowledge within no time!

What you'll learn

LangChain, Pinecone, and OpenAI are powerful tools to help developers build applications that use language modeling (LLM). With LangChain, developers can create LLM-powered applications that automate parts of a process or provide intelligent responses. This article will take you through the components necessary for building an application with LangChain, as well as discuss how embeddings and vector data stores can be used to improve its performance.

The first thing to understand is the difference between Prompt Templates, Chains, and Agents. Prompt Templates create prewritten questions for users to answer using natural language processing. The Chain component allows developers to create three types of chains: stuff, map_reduce and refine. Stuff chain involve extracting information related to a certain topic from a text while the map_reduce chain performs operations on this data set as well as refining it using more sophisticated techniques like semantic matching or clustering. Finally, LangChain agents are tools that allow developers to develop LLM-powered systems for their projects. Once you have all these components in place, it's important to understand how embeddings and vector data stores can help optimize your LLM app's performance. Embedding involves converting text into numerical representations while vector data stores allow developers to store and process large amounts of text.

By the end of this course, you’ll be able to:

• Understand the components necessary for building an application with LangChain

• Design a prompt template for users to answer with natural language processing

• Create three types of chains with stuff, map_reduce, and refine operations • Develop agents with LangChain to create LLM-powered systems

• Utilize embeddings and vector data stores to optimize an LLM app's performance

If you want to join the AI revolution, this course is perfect for you! Start learning today and build next-gen LLM applications.

About the author

Andrei Dumitrescu holds the position of Software Engineer and Lead Instructor. He has 15 years of experience as a Network and Software Engineer and possesses the qualities of a typical DevOps Engineer, including a passion for teaching that has been a part of his family for four generations.

He is a co-founder of Crystal Mind Academy, a reputable Cisco Academy and professional training center, and is committed to teaching advanced technologies to our students.

He has made contributions to education in various fields, including Programming, Blockchain, AI, Ethical Hacking, and Linux Operating Systems.

Crystal Mind Academy has empowered over 200,000 students through in-person and online training programs.

He has created detailed documentation, labs, and case studies for various training courses, including Python Programming, Go Programming, Blockchain Programming, OpenAI API with Python, Linux Administration, Ethical Hacking, and Cisco Technologies.

Outside of work, he maintains a balanced lifestyle by engaging in fitness activities such as working out and jogging, enjoying captivating books, and creating cherished memories with his wife and children through their shared love of travel.

Description

The AI revolution has already begun, and it's only a matter of time before its impact ripples across our entire society. Mastering key building blocks in this new world is essential for anyone hoping to stay ahead, and this course explores the fundamentals of three powerful platforms: LangChain, Pinecone and OpenAI.

With these tools at your disposal, you'll be able to create web-based applications powered by generative LLMs (Language Learning Machines) as well as building your own personalized front-ends with Streamlit. And keep in mind that the incredible potential of AI technology goes far beyond simple software development — by the end of this course you should have an excellent grasp of many concepts and technological advancements necessary for inventing the next big thing on the AI spectrum.

By the end of this course, learners will have a comprehensive understanding of the fundamentals of LangChain, Pinecone, and OpenAI. Streamlit allows you to create modern front-ends using pure Python.

The LangChain course is the second part of the "OpenAI API with Python Bootcamp." It is advisable to have some essential Python programming experience before attempting this, as it may not be suitable for complete beginners.

Currently, major technology corporations worldwide are investing their effort, knowledge, and money in AI.

This course teaches you how to build applications using LangChain, a state-of-the-art LLM technology.

What is the definition of LangChain?

LangChain is an open-source framework that enables developers in the AI field to integrate large language models (LLMs) like GPT-4 with external computation and data sources. It enables the building and deployment of AI applications that are scalable and performant.

Additionally, it allows individuals from various backgrounds to enter the field of AI and enables the provision of AI as a service.

This course will cover the LangChain components, LLM wrappers, Chains, and Agents. We will explore embeddings and vector databases like Pinecone in depth.

This will be an experiential learning opportunity. We will create real-world LLM applications with Python, LangChain, and OpenAI, following a systematic approach. The applications will be completed and will also include a modern web app front-end using Streamlit.

We are planning to create a question-answering application using LLM, LangChain, Pinecone, and OpenAI to cater to custom or private documents. This provides numerous practical use cases.

Additionally, a summarization system will be developed, serving as a valuable tool for individuals requiring the summarization of extensive text. The group includes students, researchers, and business professionals.

He will continue to develop and implement new projects that address various issues. This course and the technologies it covers are constantly evolving and being updated.

This course is intended for:

This course is designed for Python programmers who want to develop LLM-Powered applications utilizing the newly established LangChain, Pinecone and OpenAI development frameworks. It provides comprehensive knowledge on how to construct efficient models with natural language processing technology through these frameworks. Participants will learn how to design and deploy robust applications powered by artificial intelligence.

In this course, students will explore the most disruptive technology of this decade, namely Artificial Intelligence (AI). Through their Python programming skills they will gain a thorough understanding of AI models across Natural Language Processing (NLP), Machine Learning (ML) and other related topics. Furthermore, they will develop an understanding about the incorporation of AI into application backends using LangChain, Pinecone and OpenAI as foundational components for enhancing the overall user experience. This course is directed at any person technically interested in machine learning or AI technologies, providing them with the know-how required to venture into these realms while leveraging what new opportunities arise as it continues to advance.

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