Everything You Need About the LLM University by Cohere

Want to kickstart a new career with LLMs? Or want to transfer to the next big thing in tech? You can do so now with the LLM University by Cohere.

Everything You Need About the LLM University by Cohere
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You’ve probably been hearing a lot about Large Language Models (LLMs). Some of you are interested in what the future holds. Some are wondering “How do I involve myself in this?!”. Regardless of what your thoughts about LLMs are - the end goal is to want to learn more about it. If you want to learn about LLMs to transition to a different career in the tech industry - The LLM University by Cohere can help you with exactly that! 

We are seeing more and more developers interested in taking their careers with LLMs to the next level. Natural language processing (NLP) is an area that a lot of developers thought they’d not dive into. But with the growth of LLMs and organizations such as Cohere providing education content - it’s making the transition a lot easier. 


What is LLM University?


Cohere aims to build the future of language AI by empowering developers and enterprises to make products that allow them to capture essential business value with language AI. to live up to this, they have created the LLM University for developers who want to learn more about NLP and LLMs.

They offer a comprehensive curriculum that aims to provide students and developers with a good foundational knowledge of NLP and build on this to develop their own applications. 

Don’t feel nervous when you hear that it’s for developers - because they are here to cater to all types of people from all types of backgrounds. You will learn the basics of NLP and LLMs and build on your knowledge to a more advanced level, such as building and using text representation and text generation models.

The theoretical aspect has clear explanations and analogies with examples to back it up and the practical aspect has code examples to solidify your knowledge. Once you have a good understanding of the sector, you will put your skills to the test with hands-on exercises which will then allow you to build and deploy your very own models.


Learning Route


So how does that work? Beginners and intermediates together? No. So there are two ways to learn:

  1. Sequential

If you are a new machine learning engineer, you may feel more comfortable starting from the beginning with NLP and LLMs. With the sequential route, you will go through the basics of NLP and LLMs, and their architecture. 

Although this route requires very little background knowledge, you can still brush up on your knowledge of Machine Learning and NLP using the following material: Appendix 1.

  1. Non-Sequential

If you feel a bit more confident about the basics of NLP and LLMs, you may not want to start from the basics. You can skip these basic modules and you can move on to particular modules that fit your requirements or will help you with a particular project in mind. You can have a look at what this entails by checking out the following material: Appendix 2.


LLM University Curriculum


Want to know what you will be learning about? Let's dive in…

In the following main modules, you will learn about LLMs, how they work, and work on practical hands-on labs to build your own language applications. The first module is completely theory-focused, and then in modules 2, 3, and 4, you will have a combination of theory and hands-on practice with code labs.

These are the modules:

  1. Module 1: What are Large Language Models?

In this module, you will learn the basics of LLMs, as well as learn more about embeddings, attention, transformer model architecture, semantic search, as well as practical examples and hands-on exercises.

  1. Module 2: Text Representation with Cohere Endpoints

In the second module, you will go through theory as well as practical labs where you will learn how to use Cohere's endpoints for Classification, Embeddings, and Semantic Search. By the end of this module, you will learn how to write code to call the Cohere API for several different endpoints.

  1. Module 3: Text Generation with Cohere Endpoints

In the third module, you will learn about using generative learning to generate text. You will start with a codelab that teaches you how to use the generated endpoint and then master prompt engineering.

  1. Module 4: Deployment

Last but not least, deployment! When you build your applications, you will then learn how to deploy them using platforms and frameworks, such as AWS SageMaker, Streamlit, and FastAPI.

Once you have completed these modules, you will have mastered the world of NLP and unlocked a world of new opportunities in the growing language technology.


Wrapping it up


For you to get the help you need, Cohere is taking in the first batch of learners and guiding them through the course materials together. They also have reading groups and will be hosting exclusive events. You can sign up for their Discord community: Cohere's Discord community where you will be able to connect with other learners, help each other through the process, share ideas and build together.
Nisha Arya is a Data Scientist, Freelance Technical Writer and Community Manager at KDnuggets. She is particularly interested in providing Data Science career advice or tutorials and theory based knowledge around Data Science. She also wishes to explore the different ways Artificial Intelligence is/can benefit the longevity of human life. A keen learner, seeking to broaden her tech knowledge and writing skills, whilst helping guide others.