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Given the potential of Large Language Models (LLMs) and LLM applications, now is the perfect time to learn more about them. From fun personal projects to academic research and work, it’s always exciting to learn more about LLM and be able to use it to build interesting applications.
In my last post, I listed free courses and resources to help you learn about large language models. We’ve curated a more curated list of free courses to help you improve your skills.
let’s start!
ChatGPT prompt engineering for developers is provided by DeepLearning.AI in collaboration with the OpenAI team.
If you already use ChatGPT or GPT-4, this course will teach you how to use them better. Learn how to effectively use the OpenAI API using prompt engineering best practices.
Along the way, you’ll have the opportunity to learn how to build custom chatbots and use the OpenAI API for common use cases such as summarizing, reasoning, translating, spell checking, and grammar checking.
See also Josep Ferrer’s in-depth review of this prompt engineering course.
LangChain for LLM Application Development by DeepLearning.AI is co-led by Harrison Chase, creator of LangChain. This course focuses on building applications leveraging the LangChain ecosystem and will help you master the following tricks:
- Parse prompts and responses, manage memory and context window constraints
- Use chains to perform a sequence of actions
- Question answering for document corpus
- Leverage the agent’s inference capabilities for inference capabilities
Building systems using the ChatGPT API is also offered by DeepLearning.AI in partnership with OpenAI. This free course builds a customer service chatbot that applies the following concepts discussed in the course:
- Building Systems Using Large Language Models
- Using multistage prompts
- Break tasks into subtasks and build subtask pipelines
- Evaluating LLM Inputs and Outputs
Note: All the above courses Free for a limited time.
Google Cloud recently released a dedicated Generative AI learning path. The series of micro-courses that make up this path are designed to enable you to develop and deploy generative AI solutions on Google Cloud.
If you’re interested in learning about language models at scale, the following courses will help you.
Introduction to Large Language Models with Google Cloud is part of Udacity’s free course library and covers getting started understanding and building LLM applications including:
- Large language model basics and use cases
- fast tuning
Cohere’s LLM University provides an easy-to-follow learning path from LLM basics to building applications with LLM. Course content includes:
- Concepts such as word and sentence embeddings
- Basic Concepts of Large Language Models: Transformers and Attention Mechanisms
- Applications of LLM in text generation, classification and analysis
- Building and deploying build applications using Cohere endpoints
The Full Stack LLM Bootcamp covers everything from prompt engineering to get the most out of the GPT Assistant to deploying and monitoring LLM applications. Here’s an overview of what this bootcamp offers:
- rapid engineering
- LLM Foundation
- LLMOps
- extended language model
- Language User Interface UX
Here is a post detailing the content of this full-stack LLM bootcamp:
Here are some other interesting resources to help you understand LLM.
- GPT Talk Status: This talk by Andrej Karpathy at Microsoft Build 2023 provides a comprehensive overview of the GPT Assistant training pipeline, including tokenization, pre-training, fine-tuning, and reinforcement learning from human feedback. increase.
We hope you found this roundup of the best resources for training language models at scale useful. We had a great time putting together this list. I hope you are excited to learn and start building. Have fun learning!
Bala Priya C I am a developer and technical writer from India. She likes working at the intersection of math, programming, data she science, and content creation. Her interests and areas of expertise include DevOps, Data Science, and Natural Language Processing. She likes reading, writing, coding and coffee. Now she’s working on creating tutorials, her how-to guides, opinion articles, and more to learn and share her knowledge with the developer community.
