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Large Language Model or LLM has recently become more popular thanks to products such as ChatGPT and Google Gemini. Decades ago, people never knew what AI was capable of, and currently, everyone tries their best to catch up with the trends. If I look at the job board, many companies now also seek LLMs skills as their prerequisite.

With the competitive advantage LLMs give, it’s a brainer that we should try to at least learn about them. Whether you are a beginner or a data professional, we should aim to master the LLMs to stand out.

In this article, I will discuss five courses to help you master LLM. What are these courses? Let’s get into it.

1. Full Stack LLM Bootcamp

First, we have the Full Stack LLM Bootcamp developed by the fullstackdeeplearning.com. The website offers excellent self-managed deep learning courses, but we would focus on the LLM courses.

Since 2023, the company has run the Bootcamp in person, but it’s also released all the learning material in reading and video format.  What is good about these courses is that you can start learning, no matter your knowledge level. However, you still already expect to have some machine learning knowledge, although LLM isn’t necessary.

The course aims to help you catch up to the state-of-the-art LLM and be ready to build and deploy LLM apps. To do that, the courses offer several topics:

• LLM Foundations
• Prompt Engineering
• LLMOps: Deployment and Learning in Production
• UX for Language User Interfaces
• Augmented Language Models

The course is easy to follow, so don’t miss this free LLM Bootcamp course to master LLM.

2. LLM University by Cohere

The next course is LLM University by Cohere. Cohere is a company specialising in LLM products and research development, which makes them know what LLM is all about. The company have a great initiative to help people understand LLM by launching a free LLM University course.

LLM University provides courses in natural language processing and large language models. The course aims to improve learners' skills and strengthen the NLP foundation and hands-on approach to applying LLM in real-world situations. 

The courses comprise several topics:

• NLP and ML Fundamentals
• Combining Endpoints to Build Apps
• What are Large Language Models?
• Text Representation with Cohere Endpoints
• Text Generation with Cohere Endpoints

The courses are suitable for beginners and professionals alike, as by the end of the course, you can launch production-ready LLM apps.

3. Building LLM-Powered Apps Course

The third course we have to master LLM is the Building LLM-Powered Apps Course by Weight & Biases (WB). The company is focused on developing an end-to-end machine learning platform, one of which is the LLM app.

The course offers many self-managed video courses that you can follow to learn how to develop LLM apps. The topic includes:

• LLM Application Introduction
• LLM APIs
• Building the LLM Applications
• Optimize LLM Application

It’s a more advanced course, so we are expected to know programming language and basic knowledge of LLM. However, the course is easy enough to follow so you can learn immediately.

4.LangChain & Vector Databases in Production

The LangChain & Vector Databases in Production by activeloop is an advanced course to master LLM production applications. Rather than focus only on the LLM, this course will guide you in enhancing the existing LLM so it is ready for any customer-facing application.

To advance in the LLM industry, we need to understand LangChain and Vector Databases, which are integral to the LLM application production. By taking this course, you will understand the following concepts:

• LangChain and LLM Introduction
• Prompting
• Vector Database usage
• Indexing Organization
• Combining things with Chain

The courses are great if you already know the basics of LLM, but everyone can still follow them, even if you are a beginner.

5. Large Language Models: Application through Production

The last course is the Large Language Models: Application through Production by Databricks. Databricks is a company that provides an intelligence platform for businesses, which includes building and deploying LLM applications. This course is an industrial standard that would be good if you want to apply for an LLM job.

The course is intended for developers, data scientists, and engineers, but it’s still acceptable to follow even if you are not. Using popular frameworks and SOTA techniques such as HuggingFace, LangChain, Vector Database, Data Embedding, and many others, you would learn advanced techniques for developing and producing LLM applications.

The courses would teach you many LLM-related topics, including:

• Applications with LLMs
• Embeddings, Vector Databases and Search
• Multi-stage Reasoning
• Fine-tuning and Evaluating LLMs
• Society and LLMs: Bias and Safety
• LLMOps

At the end of the course, you will be ready to build advanced LLM applications that businesses surely want to use.

Conclusion

This article discusses five courses designed for the learner to be ready to develop and produce LLM applications. Learn everything from this course, and you will be prepared to apply for LLM jobs.
 
 

Cornellius Yudha Wijaya is a data science assistant manager and data writer. While working full-time at Allianz Indonesia, he loves to share Python and data tips via social media and writing media. Cornellius writes on a variety of AI and machine learning topics.