If you're eager to unlock the full potential of Chained AI Models and bridge the gap between artificial intelligence and external sources, you've come to the right place. Here, we will explore the best LangChain courses available in 2023, designed specifically for beginners. Whether you're a business professional seeking to leverage AI in your industry or an enthusiast curious about the possibilities, these courses will equip you with the knowledge and skills to excel. Get ready to embark on a transformative learning journey and discover the top LangChain courses that will propel you forward in the exciting world of artificial intelligence.
Top LangChain Courses & Tutorials List
- LangChain- Develop LLM-powered applications with LangChain
- LangChain Explained in 13 Minutes | QuickStart Tutorial for Beginners
- LangChain Crash Course: Build a AutoGPT app in 25 minutes
- LangChain Crash Course - Build apps with language models
- What Is LangChain? - LangChain + ChatGPT Overview
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Learn LangChain by building a real-world generative ai LLM-powered application LLM (Python). This course will equip you with the skills and knowledge to develop cutting-edge LLM solutions. You will also learn prompt engineering in this course.
In this Langchain tutorial, you will learn the following:
- Become proficient in LangChain.
- Have an end-to-end working LangChain-based generative AI application
- Prompt Engineering Theory: Chain of Thought, ReAct, Few Shot prompting and understanding how LangChain is building under the hood.
- Understand how to navigate inside the LangChain open-source codebase.
- Large Language Models Theory for software engineers.
- LangChain: Lots of chains Chains, Agents, DocumentLoader, TextSplitter, OutputParser, Memory.
- Vectorestores/ Vector Databasrs (Pinecone, FAISS).
This course will guide you through building a real-world LLM-powered application using LangChain from scratch. Using this application, you will collect online information about a name you provide and generate icebreakers tailored to a conversation with that person.
Students will work on hands-on exercises and real-world projects to reinforce their understanding of concepts and techniques. This course will prepare you to build powerful, efficient, and versatile LLM applications for various purposes by the end of the course.
- Course rating: 4.8 out of 5.0 (97 Rating total)
- Duration: 5 Hours
- Certificate: Certificate on completion
In this Langchain course, developers will explore Lang Chain, an open-source framework integrating large language models, such as GPT-4, with external data sources. Students will learn to connect language models to databases and documents, allowing for specific information retrieval and subsequent actions.
Students also explore the concept of chains, which combine multiple components to solve specific tasks and agents that enable language models to interact with external APIs. The course emphasizes the framework's integration with popular machine learning frameworks and its support for distributed computing.
By the end of the course, students possess a comprehensive understanding of Lang Chain's architecture and functionalities. They can effectively connect language models to external data sources, build interactive applications, and leverage the power of combining language models with advanced APIs.
The course from Nicholas Renotte will demonstrate how to build an Auto GPT model using the Langchain framework and explain why more companies should build their large language models. This course covers setting up the Langchain server, configuring API keys, downloading and installing dependencies, triggering prompts, rendering responses, and implementing prompt templates.
Second, we will explore using prompt templates and sequential chains in OpenAI's language model to generate YouTube video titles and scripts. With the help of these techniques, we can automate the process of creating engaging content for YouTube channels. The course will walk through the code implementation step-by-step, highlighting the key concepts and explaining how they work together to generate dynamic and context-specific video titles and scripts.
Lastly, we will learn how to use Lang Chain to create a deep learning application capable of generating video scripts based on a given topic. We will also learn how to incorporate memory and leverage external tools like the Wikipedia API to enhance the capabilities of our application.
This comprehensive tutorial presents Lang Chain, a powerful framework for developing language-based applications. In this course, Patrick Loeber will guide you to Lang Chain's key features and demonstrate how to utilize them to build your own AI applications. Whether you need to create a chatbot or perform complex language tasks, Lang Chain can help.
The course begins with an introduction to Lang Chain, highlighting its features and benefits. It explains how Lang Chain simplifies the integration of language models into applications and offers flexibility in accessing different models based on specific requirements.
The course then guides participants through the installation and setup process of Lang Chain, ensuring that they have the necessary tools and packages installed to begin building AI apps.
Overall, this course empowers developers to harness the power of large language models through the Lang Chain framework, enabling them to create intelligent and dynamic AI applications that understand, converse, and collaborate with humans seamlessly.
This LangChain tutorial series offers a comprehensive guide to Lane Chain, an innovative library that enables the chaining of AI models and external systems. This course series provides participants with practical knowledge and real-world applications to leverage Lane Chain's full potential in various areas.
The series begins with an introductory video outlining the goals of the tutorial and explaining the significance of Lane Chain. It emphasizes the need for bridging the gap between AI models and external sources and highlights the unique capabilities of Lane Chain in achieving this integration.
The instructor focuses on real-world applications rather than theoretical concepts, aiming to help participants make a tangible impact in both B2B environments and personal endeavors. The tutorials provide practical knowledge and guide participants in applying Lane Chain to their specific use cases.
Overall, this Langchain course series equips participants with the skills and knowledge to effectively use Lane Chain in connecting AI models and external systems. By exploring real-world applications and leveraging the power of Lane Chain, participants can unlock the potential of chained AI models and drive meaningful outcomes in their respective domains.
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