Top 30 Online Courses for Mastering Large Language Models (LLMs) [Free & Paid]

What Are Large Language Models?

Large Language Models (LLMs) are highly advanced artificial intelligence systems that utilize vast amounts of data and cutting-edge neural network architectures to perform tasks involving natural language understanding and generation. These models, such as GPT-4o and Gemini, leverage billions of parameters to process and generate coherent and contextually appropriate text.

Why Learn About Large Language Models?

Mastering the principles and applications of LLMs as LLMs become increasingly integrated into core business operations and public services. By understanding the theoretical and practical aspects of LLMs, learners can contribute to advancing the state of AI while addressing critical issues such as bias, interpretability, and scalability.

1. Large Language Models Course

• Level: Beginner (No technical background required)
• Instructors: Sander Schulhoff, Fady Yanni
• Duration: 3 days (self-paced)
• Free/Paid: Free audit (3-day free trial); included with Learn Prompting Plus (access to 15 courses)
• Certificate: Yes (instant upon completion)
• Visit Course: Large Language Models Course

Provides a practical, beginner-friendly introduction to Large Language Models (LLMs) for business leaders and non-tech professionals. Topics include how LLMs work, how they learn, and real-world use cases—empowering learners to lead AI adoption without diving into too much technical detail.

2. ChatGPT for Everyone by OpenAI and Learn Prompting

• Level: Beginner
• Instructors: Sander Schulhoff (Founder & CEO at Learn Prompting), Shyamal Anadkat (Applied AI at OpenAI)
• Duration: 1 hour
• Free/Paid: Free
• Certificate: Yes
• Visit Course: ChatGPT for Everyone

This course introduces you to the fundamentals of ChatGPT and generative AI. It covers how ChatGPT works, its applications, and techniques for effective prompt writing. It also addresses ethical considerations and provides practical strategies for enhancing productivity, writing, and content creation using ChatGPT.

3. Foundations of Large Language Models: Tools, Techniques, and Applications

• Level: Intermediate to Advanced (Python + ML background recommended)
• Instructors: Brian Zimmerman; contributions from Dr. Rodrigo Nogueira & Dr. Jimmy Lin
• Duration: 4 weeks (5 hours/week)
• Free/Paid: Paid ($1,450 + taxes; early bird/alumni discounts)
• Certificate: Yes
• Visit Course: Link

Explores LLM architectures (e.g., GPT, BERT), prompt engineering, fine-tuning, and end-to-end system integration. Emphasizes practical knowledge and hands-on experience, preparing participants to build, customize, and optimize NLP applications.

4. Large Language Models (LLMs) & Text Generation

• Level: Intermediate
• Instructors: Emily McMilin (Ph.D. Stanford), Victor Geislinger (Google), Jason Lin (Chief Scientist at Reasonly AI), Erick Galinkin (Principal AI Researcher at Rapid7)
• Duration: 2 weeks (self-paced)
• Free/Paid: Paid (starting at $249/month for All Access; bundle discounts)
• Certificate: Yes
• Visit Course: Link

Covers how LLMs understand and generate text, focusing on unsupervised learning, retrieval-augmented generation, prompt engineering, and transformers. Includes a hands-on project for building a chatbot with OpenAI’s API and a custom dataset.

5. Large Language Models (LLMs) Concepts

• Level: Beginner
• Instructor: Vidhi Chugh (AI Strategist & Ethicist), with Amy Peterson, James Chapman, Jasmin Ludolf
• Duration: 2 hours
• Free/Paid: Included with Premium or Teams subscription
• Certificate: Yes
• Visit Course: Link

Offers a conceptual overview of LLMs, including their applications, training methods, and ethical considerations. Discusses real-world transformations driven by LLMs, along with challenges like bias, privacy, and environmental impact.

6. Large Language Model Operations (LLMOps) Specialization

• Level: Beginner
• Instructors: Derek Wales, Noah Gift, Alfredo Deza
• Duration: 5 months (10 hours/week)
• Free/Paid: Included with Coursera Plus
• Certificate: Yes
• Visit Course: Link

Teaches learners how to deploy, manage, and optimize LLMs on cloud platforms (Azure, AWS, Databricks) and on local infrastructure. Features 20+ coding projects focusing on generative AI techniques and LLM operational workflows.

7. Developing Large Language Models

• Level: Beginner
• Instructors: Maham Khan (Senior Data Scientist), Thomas Hossler (Senior ML Engineer), Shubham Jain (Data Scientist), Michał Oleszak (ML Engineer)
• Duration: ~16 hours
• Free/Paid: Included with Premium or Teams subscription
• Certificate: Yes
• Visit Course: Link

Focuses on building LLMs using PyTorch and Hugging Face. Covers deep learning fundamentals, transformer architectures, pre-trained models, and deployment challenges. Practical projects include fine-tuning and experimenting with Llama 3.

8. Large Language Models (BSCS5001)

• Level: Degree-Level Course
• Instructor: Prof. Mitesh M. Khapra (IIT Madras)
• Duration: Semester-long
• Free/Paid: Paid (part of IIT Madras Online Degree Program)
• Certificate: Yes (part of the degree program)
• Visit Course: Link

Focuses on transformer architectures, tokenization, pretraining, fine-tuning, and handling long-range context. Serves as an elective in IIT Madras’s online degree program, blending academic rigor with hands-on practice.

9. Large Language Models (1st Edition)

• Level: Advanced
• Instructor: Oier Lopez de Lacalle
• Duration: 20 hours (5 sessions)
• Free/Paid: Paid (€274, discounts available)
• Certificate: Optional (€27.96 extra)
• Visit Course: Link

Offers a masterclass on LLM architectures, scalability issues, and ethical challenges. Includes real-world labs on prompting, reasoning, and alignment, plus practical chatbot development exercises.

10. Large Language Models for Beginners

• Level: Beginner
• Instructors: Altaf Rehmani, Jyoti Gupta
• Duration: 4 weeks (4 hours/week)
• Free/Paid: Paid
• Certificate: Yes
• Visit Course: Link

A foundational course covering LLM architecture, training, and adaptation. Addresses ethics, bias, human alignment, and scalability. Features practical labs on prompting, Q&A, and chatbot development.

11. AI: Applied Local Large Language Models

• Level: Intermediate
• Instructors: Noah Gift (Pragmatic AI Labs), Alfredo Deza (Adjunct Professor, Pratt School of Engineering)
• Duration: 4 weeks (3–6 hours/week)
• Free/Paid: Free audit (limited); $249 for certificate
• Certificate: Available in paid track
• Visit Course: Link

Focuses on deploying and interacting with LLMs locally. Uses tools like Hugging Face and Mozilla’s Llamafile. Teaches Python-based integration and deployment strategies. Part of the Professional Certificate Program in LLMOps.

12. Generative AI with Large Language Models

• Level: Intermediate
• Instructors: Chris Fregly, Antje Barth, Shelbee Eigenbrode (DeepLearning.AI & AWS)
• Duration: ~16 hours (flexible)
• Free/Paid: Free audit (limited); paid track with certificate
• Certificate: Available in paid track
• Visit Course: Link

Examines generative AI and LLMs, from transformer architectures to scaling laws and deployment. Emphasizes best practices for fine-tuning and optimizing LLMs in real-world business solutions.

13. Generative AI and LLMs: Architecture and Data Preparation

• Level: Intermediate
• Instructors: Joseph Santarcangelo, Roodra Pratap Kanwar (IBM)
• Duration: ~5 hours (3 weeks @ ~1 hour/week)
• Free/Paid: Included with Coursera Plus or pay-per-course
• Certificate: Available in paid track
• Visit Course: Link

Covers generative AI architectures and practical skills for LLMs. Includes RNNs, Transformers, GANs, VAEs, and Diffusion Models. Students learn tokenization and data prep with Hugging Face, PyTorch, and other libraries.

14. Large Language Model Agents

• Level: Intermediate to Advanced
• Instructors: Dawn Song (UC Berkeley), Xinyun Chen (Google DeepMind)
• Guest Speakers: Experts from Google DeepMind, OpenAI, NVIDIA, Stanford
• Free/Paid: Free to audit; optional completion tiers
• Certificate: Yes, optional (Trailblazer, Mastery, Ninja, Legendary, Honorary)
• Visit Course: Link

Explores LLM agent development in coding, robotics, web automation, and more. Includes foundational concepts, ethics, infrastructure setup, and hands-on labs. Features a capstone Hackathon for collaborative projects.

15. Free Large Language Models Course: Unlock AI Expertise

• Level: Beginner
• Instructor: Powered by Google Cloud (no specific instructor named)
• Duration: 1 hour (self-paced; 90-day access)
• Free/Paid: Free
• Certificate: Yes
• Visit Course: Link

Covers LLM architecture, frameworks, and applications. Introduces NLP basics, hyperparameter tuning, data augmentation, and model fine-tuning. Ideal for aspiring NLP/ML engineers seeking a quick-start overview.

16. Essentials of Large Language Models: A Beginner’s Journey

• Level: Beginner
• Instructor: Not specified
• Duration: 2 hours
• Free/Paid: Included with Educative subscription
• Certificate: Yes
• Visit Course: Link

Offers an interactive introduction to LLMs, focusing on core components, capabilities, and limitations. Features hands-on modules for fine-tuning, model evaluation, and performance comparison.

17. Generative AI with Large Language Models

• Level: Intermediate
• Instructors: Chris Fregly, with contributions by Antje Barth & Shelbee Eigenbrode
• Duration: ~16 hours
• Free/Paid: Included with Coursera Plus
• Certificate: Yes
• Visit Course: Link

Covers the entire project lifecycle of LLM-based generative AI—transformer architecture, data gathering, evaluation, fine-tuning, and deployment. Explains how to leverage LLMs for real-world business solutions.

18. Large Language Models Specialization

• Level: Intermediate
• Instructor: H2O.ai University
• Duration: 1 month (~1 hour/week)
• Free/Paid: Included with Coursera Plus
• Certificate: Yes
• Visit Course: Link

Focuses on developing, fine-tuning, and optimizing LLMs using H2O.ai tools. Includes hands-on projects for end-to-end NLP workflows, ensuring readiness for AI-driven roles in industry.

19. Introduction to Large Language Models Course

• Level: Beginner
• Instructor: Google Cloud Training
• Duration: ~1 hour
• Free/Paid: Included with Coursera Plus
• Certificate: Yes
• Visit Course: Link

A micro-learning course covering LLM fundamentals, basic use cases, and prompt tuning. Showcases Google’s generative AI tools for building practical AI applications.

20. CS324 - Large Language Models

• Level: Graduate/Advanced
• Instructors: Percy Liang, Tatsunori Hashimoto, Christopher Ré
• Course Assistants: Rishi Bommasani, Sang Michael Xie
• Free/Paid: Open materials, no certificate
• Visit Course: Link

Advanced coverage of LLM fundamentals, theory, applications, and ethical concerns. Projects involve building and evaluating models like GPT-3 and BERT, focusing on real-world capabilities and risks.

21. Large Language Model Course

• Level: Beginner to Advanced
• Instructor: Maxime Labonne
• Free/Paid: Open materials, no certificate
• Visit Course: Link

Presents a structured learning path from LLM basics to advanced deployment. Provides Colab notebooks, fine-tuning guides, and performance evaluation tools, suitable for novices and experts alike.

22. Large Language Models

• Level: Intermediate
• Instructors: Florian Tramèr, Mrinmaya Sachan, Ryan Cotterell
• Guest Lecturers: Alex Warstadt, Ethan Wilcox, Tiago Pimentel
• Free/Paid: Open materials, no certificate
• Visit Course: Link

Introduces fundamental language modeling theory, neural architectures, and LLM applications. Covers text generation, privacy considerations, ethical implications, and cross-domain use cases.

23. CS224N: Natural Language Processing with Deep Learning

• Level: Intermediate to Advanced
• Instructors: Diyi Yang, Tatsunori Hashimoto
• Free/Paid: Open materials, no certificate
• Visit Course: Link

A Stanford course diving deep into NLP, covering transformers, pretraining, fine-tuning, and advanced applications. Hands-on projects in Python and PyTorch underscore both practical and research insights.

24. Hugging Face NLP Course

• Level: Intermediate
• Instructors: Abubakar Abid, Matthew Carrigan, Lysandre Debut, Sylvain Gugger, Dawood Khan, Merve Noyan, Lucile Saulnier, Lewis Tunstall, Leandro von Werra
• Duration: Self-paced (~6-8 hours/week)
• Free/Paid: Open materials, no certificate
• Visit Course: Link

Comprehensive coverage of NLP with Hugging Face tools and libraries. Teaches use of pre-trained models, fine-tuning, deployment, and specialized libraries (Transformers, Datasets, Tokenizers, Accelerate).

25. COS 597G: Understanding Large Language Models

• Level: Advanced (Graduate)
• Instructor: Danqi Chen
• Free/Paid: Open materials, no certificate
• Visit Course: Link

A Princeton graduate course focused on the research, design, and capabilities of LLMs. Explores GPT, T5, few-shot learning, ethics, scalability, and security. Emphasizes research skills, paper critiques, and project work.

26. Training & Fine-Tuning LLMs for Production

• Level: Intermediate
• Instructor: Collaboration by Activeloop, Towards AI, Intel Disruptor Initiative
• Free/Paid: Open materials, no certificate
• Visit Course: Link

Focuses on both theory and hands-on practice for training, fine-tuning, and deploying LLMs. Covers foundational concepts, advanced operational techniques, and real-world project integrations.

27. CS 194/294-267: Understanding Large Language Models: Foundations and Safety

• Level: Advanced (Graduate/Senior Undergrad)
• Instructors: Dawn Song, Dan Hendrycks, Yu Gai
• Free/Paid: Open materials, no certificate
• Visit Course: Link

Investigates LLM foundations, interpretability, adversarial robustness, and AI alignment. Addresses ethical AI practices, real-world risks, and labs or projects focusing on safe LLM deployment.

28. CSC 6203 Large Language Models

• Level: Advanced (Graduate)
• Instructor: Benyou Wang; TAs: Junying Chen, Ke Ji
• Free/Paid: Open materials, no certificate
• Visit Course: Link

Covers LLM development, prompt engineering, multimodality, domain-specific applications, ethics, and alignment. Includes advanced topics on scaling laws and real-world deployment scenarios.

29. LLM University by Cohere

• Level: Beginner to Intermediate
• Instructor: Cohere Team
• Free/Paid: Open materials, no certificate
• Visit Course: Link

Free educational platform created by Cohere. Teaches the fundamentals of LLMs, including embeddings, fine-tuning, and practical use cases for real-world applications.

30. Fine-Tuning Large Language Models Project

• Level: Intermediate
• Instructor: Sharon Zhou
• Free/Paid: Open materials, no certificate
• Visit Course: Link

A project-based course focused on data preparation, model training, and evaluation for specialized tasks. Learners practice adapting LLMs to new contexts and optimizing performance for specific domains.

Conclusion

We hope this list helps you find the right course to enhance your LLM and NLP skills. If you’re still unsure about diving into a specific program, you can always start with a free course or consult our Prompt Engineering Guide.

Happy learning!

Valeriia Kuka

Valeriia Kuka, Head of Content at Learn Prompting, is passionate about making AI and ML accessible. Valeriia previously grew a 60K+ follower AI-focused social media account, earning reposts from Stanford NLP, Amazon Research, Hugging Face, and AI researchers. She has also worked with AI/ML newsletters and global communities with 100K+ members and authored clear and concise explainers and historical articles.