More free courses on great language models

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Given the potential of large language models (LLMs) and LLM applications, now is the best time to learn more about them! From fun personal projects to academic research and work, it’s always interesting to better understand LLMs in order to use them to create interesting applications.

In a previous article, we listed free courses and resources to help you learn about big language models. We have compiled another list of free courses to help you improve your skills.

Let’s start!

ChatGPT Prompt Engineering for Developers is offered by DeepLearning.AI in collaboration with the OpenAI team.

If you’re already using ChatGPT or GPT-4, this course will teach you how to get better at using them. You will learn how to use the OpenAI API effectively using agile engineering best practices.

Along the way, you’ll have the opportunity to build a custom chatbot and learn to use the OpenAI API for common use cases, including summarization, inference, translation, spelling, and grammar checks.

Also check out this detailed review of this crash course in engineering by Josep Ferrer.

The LangChain LLM for Application Development by DeepLearning.AI is co-taught by Harrison Chase, the creator of LangChain. Focusing on building applications using the LangChain ecosystem, this course will help you:

• Request handling and response parsing, memory and context window limits
• Using chains to perform a sequence of actions
• Answer to the question on the body of the document
• Exploiting Agents’ Reasoning Capabilities for Reasoning Capabilities

Build Systems with ChatGPT API also offers DeepLearning.AI in partnership with OpenAI. In this free course In this free course, you’ll build a customer service chatbot that uses the following concepts covered in the course:

• Building systems using large language models
• Using a multi-step query
• Building a pipeline of subtasks by dividing tasks into subtasks
• Assessment of LLM inputs and outputs

Note: All of the above are courses Free for a limited time.

Google Cloud recently launched a dedicated generative AI learning path. The series of micro-courses that make up this path are aimed at developing and deploying generative AI solutions on Google Cloud.

If you are interested in learning about large language models, you will find the following courses useful:

Introduction to Large Language Models with Google Cloud is part of Udacity’s free course library and covers understanding and building LLM applications, including:

• Fundamentals and use cases of large language models
• Quick tuning

LLM University by Cohere provides an easy-to-follow learning path: from LLM basics to building applications using them. The course includes:

• A concept such as embedding words and sentences
• Basic concepts of large language models: transformers and the mechanism of attention
• Using LLMs in Text Generation, Classification, and Analysis
• Build and deploy building applications using Cohere endpoints

The Full Stack LLM Bootcamp covers everything from agile engineering to getting the most out of GPT assistants to deploying and monitoring LLM applications. Here’s an overview of what this bootcamp has to offer:

• Rapid engineering
• LLM Foundations
• LLMOps
• Enhanced language models
• UX language for user interfaces

Here is a post breaking down the content of this Full Stack LLM bootcamp.

Here are some other interesting resources to help you get your LLMs up:

• State of GPT Talk: This talk by Andrei Karpathi at Microsoft Build 2023 provides a comprehensive overview of GPT Assistant training pipelines, including tokenization, pretraining, fine-tuning, and human feedback enhancements.

We hope you found this roundup of some of the best resources for learning about large language models useful. We had a great time making this list and we hope you enjoy learning and building! Happy learning!

Bala Priya C is a developer and technical writer from India. He enjoys working at the intersection of mathematics, programming, data science, and content creation. His areas of interest and expertise include DevOps, data science, and natural language processing. She loves reading, writing, coding, and coffee! He is currently working on learning and sharing his knowledge with the developer community by authoring tutorials, guides, reviews, and more.