Artificial Intelligence is evolving at a fast pace, and Large Language Models (LLMs) are at the heart of this transformation. Powerful models like GPT-4 can generate text, answer questions, and even assist in coding. Thus, understanding LLMs is becoming an essential skill.
Learning about them has become increasingly important in today’s rapidly evolving technological landscape. These models are at the forefront of advancements in artificial intelligence and natural language processing. Understanding their capabilities and limitations empowers individuals and professionals across various fields.
But where do you start? LLMs can feel overwhelming, with complex concepts like tokenization, fine-tuning, and prompt engineering.
The good news? YouTube is packed with high-quality educational content to help you grasp these concepts at your own pace.
Why YouTube Channels are a Good Resource?
Research papers, documentation, and textbooks are valuable resources but can be technical and difficult to digest, especially for beginners. That’s where YouTube comes in. It’s one of the best free resources for learning about LLMs, offering a mix of theory, practical tutorials, expert discussions, and real-world applications.
Here’s why YouTube is an excellent platform to kickstart and deepen your understanding of LLMs:
Visual and Hands-On Learning Makes Concepts Easier: LLMs involve complex topics that can feel abstract when explained through text alone. YouTube makes these concepts easier to grasp with visual demonstrations, step-by-step coding tutorials, and engaging animations that break down difficult ideas into digestible chunks.
Learn from AI Experts and Industry Leaders: YouTube provides direct access to leading AI researchers, developers, and engineers who share their expertise for free. Professionals from companies like OpenAI, Google, and Meta regularly post videos covering the latest breakthroughs in AI and real-world applications of LLMs.
Up-to-Date Content on the Rapidly Evolving AI Landscape: While traditional resources can quickly become outdated, YouTube creators continuously upload videos on new LLM models and AI tools. Emerging techniques like Retrieval-Augmented Generation (RAG) and fine-tuning strategies are frequently discussed, ensuring learners always have access to the latest advancements.
Free and Accessible for Everyone: One of YouTube’s greatest advantages is that it is completely free, making AI education accessible to everyone, regardless of their budget. Videos can be watched anywhere, anytime, and at your own pace, allowing learners to pause, rewind, and rewatch as needed.
Covers Every Learning Level – From Beginner to Advanced: YouTube caters to learners of all experience levels. From introductory videos explaining fundamental concepts to coding tutorials, API integrations, and more, YouTube covers it all. This flexibility allows everyone to progress at their own pace and choose content based on their current skills and goals.
Engaging Communities and Interactive Learning: Many AI-focused channels feature comment sections where learners can ask questions, Discord and Slack groups for deeper discussions, and live Q&A sessions with AI experts. This interactive learning environment provides support, motivation, and opportunities to connect with like-minded individuals, making AI education more engaging and collaborative.
These YouTube videos will help you learn large language models
In this blog, we will explore some of the top YouTube channels that cover everything from LLM basics to advanced AI techniques. Whether you’re a beginner or an experienced developer, these channels will help you build, experiment, and stay updated with the latest trends in AI. Let’s dive in!
1. Data Science Dojo: A YouTube Hub for Learning about LLMs
If you are looking to kickstart your learning about LLMs, this is the right place to start. From beginners to experienced AI enthusiasts, this channel will cater to all levels of learners in their journey to learn about LLMs.
Whether you want to understand the basics of LLMs or dive deep into advanced techniques, this channel has something for you. With clear explanations, hands-on tutorials, and expert insights, it covers key topics like Llama Index, LangChain, Redis, Retrieval Augmented Generation, AI observability, and more.
What You’ll Learn
The channel covers a wide range of AI topics, including:
- LLM Fundamentals – Learn how models like GPT and BERT process language.
- Hands-on Coding Tutorials – Follow step-by-step guides on fine-tuning and deploying LLMs.
- Expert Insights – Get valuable knowledge from AI professionals.
- Real-World Applications – See how LLMs power chatbots, automation, and text generation.
Data Science Dojo helps you stay updated with the latest trends and techniques with its informative and practical videos, making it easier to apply what you learn. If you’re looking for a structured way to understand and experiment with LLMs, visit and subscribe to Data Science Dojo’s YouTube channel.
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2. Databricks: Unlock the Power of LLMs
Known for its expertise in big data, AI, and machine learning, Databricks offers high-quality videos that break down complex topics into simple, actionable insights. From the basics of foundation models to fundamental concepts, you can find a ton of useful tutorials and talks that can help you get started with LLMs.
Databricks provides a structured approach, helping both beginners and professionals build, fine-tune, and scale AI models efficiently.
The channel covers:
- LLM Development – How to train and deploy models like GPT on scalable cloud platforms.
- Optimizing AI Workflows – Learn how to use Databricks’ tools to speed up model training.
- Real-World Use Cases – See how LLMs are transforming industries like healthcare and finance.
- Expert Talks & Demos – Insights from AI leaders and hands-on coding walkthroughs.
Whether you’re fine-tuning models or handling massive datasets, Databricks provides the tools and knowledge you need.
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3. AssemblyAI: Demystifying LLMs and AI
From speech AI, NLP, and deep learning to LLMs, the AssemblyAI channel covers all cutting-edge AI topics to make them easy to understand. It breaks down these complex topics into simple, engaging, and well-explained videos, making it easier for developers, researchers, and AI enthusiasts to stay ahead.
You can learn about Llama Index, vector databases, and LangChain while also exploring how to build your own coding assistant with ChatGPT. Thus, the AssemblyAI channel offers plentiful learning tutorials within the domain of LLMs.
Some key topics covered by the channel include:
- LLMs & NLP Fundamentals – Learn how models like GPT and BERT process language.
- Speech AI & Transcription Models – Discover how AI converts speech into text with high accuracy.
- Building & Optimizing AI Models – Get hands-on guidance for training and deploying models.
- AI Industry Insights – Stay updated with the latest advancements in deep learning and AI ethics.
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4. FreeCodeCamp: A Free Resource for Learning About LLMs
FreeCodeCamp offers a wide range of tutorials, including how to build LLMs with Python, prompt engineering for web developers, a LangChain course, and more. This channel can help you get started with the basics by providing everything you need to understand, build, and experiment with AI models, and that too without a paywall.
This channel offers:
- Beginner to Advanced AI Tutorials – Learn the basics and then move on to fine-tuning models.
- Hands-on Coding Lessons – Build and train LLMs using Python, TensorFlow, and PyTorch.
- Deep Learning & NLP Courses – Understand how models like GPT, BERT, and LLaMA work.
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5. Mathew Berman: Simplifying LLMs for Everyone
If you’re looking for straightforward and practical insights into LLMs, the Matthew Berman YouTube channel is a great place to start. His content focuses on AI, machine learning, and coding, making complex topics easy to understand.
From artificial intelligence to generative art, this channel sheds light on several significant areas, including AI art, ChatGPT, LLMs, machine learning, technology, and coding. Some key areas it covers include:
- LLM Basics & Fundamentals – Understand how models like GPT work.
- Practical AI Tutorials – Hands-on coding sessions to build and train LLMs.
- Fine-Tuning & Deployment – Learn how to customize AI models for specific tasks.
- AI Tools & Best Practices – Get tips on working efficiently with LLMs.
Subscribe now and start learning.
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6. IBM Technology: Exploring LLMs with Industry Experts
IBM has been a leader in AI research, cloud computing, and data science, making this channel a valuable resource for learning about technological advancements like LLMs and their real-world applications.
The channel includes several talks and tutorials pertaining to machine learning and generative AI. From useful tutorials like building a chatbot with AI to insightful talks like the rise of generative AI, it can help you navigate your learning path.
Some key aspects of the channel include:
- LLM Fundamentals & Development – Understand how IBM integrates AI into business solutions.
- AI Ethics & Responsible AI – Learn about fairness, bias, and security in LLMs.
- Watson & AI-Powered Tools – See how IBM’s AI models are applied in different industries.
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7. Yannic Kilcher: Deep Dives into LLMs and AI Research
Yannic specializes in breaking down AI papers, machine learning concepts, and cutting-edge research, making complex ideas easier to grasp. His videos make academic research more accessible to AI enthusiasts and professionals.
From detailed talks to short tutorials, this channel offers a number of resources to learn about LLMs. For instance, it covers ideas around Llama 2, ReST for language modeling, retentive networks, and more to assist you in building your LLM knowledge base.
It covers:
- LLM Research & Innovations – Breakdown of the latest AI papers and advancements.
- Model Architectures – Deep dives into how GPT, BERT, and other models are built.
- AI Ethics & Controversies – Discussions on bias, alignment, and responsible AI.
- Hands-on AI Experiments – Testing AI models and showcasing real-world applications.
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8. Nicholas Renotte: Hands-On Learning for LLMs
Unlike purely theoretical channels, Nicholas dives straight into coding. His step-by-step tutorials help you train, fine-tune, and deploy AI models, making complex topics feel simple. Whether you’re a beginner or an experienced developer, his videos provide clear, actionable guidance.
Nicholas shares practical ways to get started with data science, machine learning, and deep learning using a bunch of different tools but mainly Python and Javascript. The channel includes many useful talks, like breaking down the generative AI stack, building an AutoGPT, and using Llama 2 70B to rebuild GPT Banker.
This channel covers:
- Hands-on AI Projects – Build chatbots, text generators, and other AI-powered tools.
- Fine-Tuning & Deployment – Learn how to customize and optimize LLMs.
- AI & ML Workflows – Explore how AI fits into real-world applications.
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9. Eye on Tech: Breaking Down LLMs for Everyone
With clear, concise, and insightful discussions on LLMs, Eye on Tech is a great resource to learn and stay updated on the latest technological trends. It focuses on the latest business technology and IT topics, including AI, DevOps, security, networking, cloud, storage, and more.
This channel covers a number of useful talks, like the introduction to foundation models, AI buzzwords, conversational AI versus generative AI, and more that can help you get started with the basics. Some key features covered in the videos are:
- AI in Business & Tech – See how companies use LLMs for automation and efficiency.
- Industry Trends & Innovations – Stay ahead with the latest AI developments.
- Tech Explainers & Insights – Get expert opinions on the future of AI and machine learning.
Link to channel
Start Learning About Large Language Models Today!
Large language models (LLMs) are a type of artificial intelligence (AI) model that can generate and understand text. They are trained on massive datasets of text and code, which allows them to learn the statistical relationships between words and phrases.
The field of LLMs is rapidly growing, and new models are being developed all the time. In recent years, there have been a number of breakthroughs in LLM technology, including:
- The development of new training algorithms that allow LLMs to be trained on much larger datasets than ever before.
- The development of new hardware architectures that can support the training and inference of LLMs more efficiently.
- The release of open-source models has made LLMs more accessible to researchers and developers.
As a result of these advances, LLMs are becoming increasingly powerful and capable. By understanding LLMs, you can position yourself to take advantage of the opportunities that they create.
