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Free Large Language Models (LLMs) Course
LLM Essentials
Join our free LLM course to learn how LLMs are organized, what they may be applied to, and how they can be implemented. Understand how they operate, learn the main examples, and examine their issues, constraints, and prospects.
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About this course
Through this free large language models course, you will gain an understanding of how these models work and how they generate human-like language, their abilities and influence in industries. You will learn about the various languages and systems they operate on, some notable examples in the AI space, and the transformer architecture which drives them. The course also goes through some of the key milestones in their development, the pragmatic applications of their use such as the creation of product descriptions and code debugging as well as issues related to their use such as bias, hallucinations, and scalability. By the end, you will be aware of the advantages, weaknesses, and future directions of the large language models and how they influence the current technology and productivity.
Why upskill with us?
Course Outline
In this module, you will learn about Large Language Models, including their ability to process and generate human-like language, and their key roles and capabilities in today’s AI-driven world.
In this module, you will learn what Large Language Models are, the diverse types of languages they understand, and explore key examples in the AI landscape.
In this module, you will learn how Large Language Models work using neural networks, machine learning, and transformer architecture to process and generate language efficiently.
In this module, you will explore key milestones in the development of Large Language Models and understand their powerful capabilities across various language tasks.You will also explore real-world use cases of Large Language Models, including product description generation and code debugging.
In this module, you will learn about the key challenges of LLMs, such as hallucinations, bias, domain mismatch, and scalability, and explore future trends including ethical AI, workforce shifts, and productivity gains with GenAI.
Earn a certificate of completion
Get free course content
Learn at your own pace
Master in-demand skills & tools
Test your skills with quizzes
Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Is this course free?
Who is this free Large Language Models (LLMs) course for?
The course will perfectly suit individuals interested in understanding how Large Language Models work, what they are capable of and how they are applied in different industries.
What topics are covered in the free LLM Online course?
The course talks about architecture of LLM, languages and systems, transformer models, capabilities, use cases, challenges, limitations and future trends.
Do I need any prior experience to take this course?
There is no particular prior experience needed, but knowledge of some basic AI or machine learning could be beneficial.
How is the free large language model course structured?
The course is divided into modules starting with the fundamentals of the LLM, followed by their design and capabilities and lastly the challenges, limitations and opportunities.
What do the course modules include?
The modules are:
- Introduction to Large Language Models
- LLM Languages, Systems and Examples
- Working of LLM Transformer Architecture
- Key Milestones, Capabilities and Use Cases of LLMs
- Challenges, Limitations, and Future of LLMs
What skills will I gain after completing the free LLM training course?
You will be able to explain how LLMs work, identify their capabilities and use cases, understand their architecture, and evaluate their challenges and potential future impact.
Why should I learn about Large Language Models?
The LLMs are transforming industries, and they have the potential of facilitating complex natural language processing. When you learn about them, you will have the knowledge of applying these technologies responsibly and effectively.
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