This white paper provides a curated selection of video courses on Large Language Models (LLMs) offered by Udemy, Packt, and Coursera, along with recommendations based on user reviews and a comprehensive list of relevant resources.

1. Introduction

LLMs have revolutionized the field of Artificial Intelligence, demonstrating remarkable capabilities in natural language processing tasks such as text generation, translation, and summarization. This surge in interest has led to a plethora of online courses catering to diverse learning needs. This white paper aims to guide learners by providing a curated selection of high-quality courses on Udemy, Packt, and Coursera, along with valuable resources for further exploration.

2. Course Recommendations

2.1 Udemy

  • "**Building a Chatbot with ChatGPT and LangChain [invalid URL removed]" by Andrei Neagoie: This highly-rated course guides learners through building a sophisticated chatbot using ChatGPT and the powerful LangChain library.
    • Key Features: Hands-on projects, practical applications, and a focus on real-world use cases.
  • "**Mastering Prompt Engineering: Unlock the Power of Language Models [invalid URL removed]" by DeepLearning.AI: This course delves into the art of prompt engineering, a crucial skill for effectively interacting with and harnessing the power of LLMs.
    • Key Features: Expert instruction, practical exercises, and insights into optimizing prompts for various tasks.

2.2 Packt

  • "**Mastering Large Language Models with Python [invalid URL removed]" by Prateek Joshi: This comprehensive course covers key concepts, techniques, and applications of LLMs using Python.
    • Key Features: In-depth coverage of foundational concepts, practical coding exercises, and real-world project examples.
  • "**Building Chatbots with LangChain and Large Language Models [invalid URL removed]" by Prateek Joshi: This course focuses on building conversational AI applications using LangChain and popular LLM models.
    • Key Features: Practical approach, hands-on projects, and insights into building interactive and engaging chatbots.

2.3 Coursera

  • "**Generative AI with Large Language Models [invalid URL removed]" by DeepLearning.AI: This specialization offers a comprehensive introduction to LLMs, covering foundational concepts, advanced techniques, and real-world applications.
    • Key Features: High-quality instruction, hands-on projects, and a structured learning path.
  • "Natural Language Processing Specialization**" by University of Washington: This specialization provides a strong foundation in NLP, including topics relevant to LLMs such as text classification, sentiment analysis, and machine translation.
    • Key Features: Comprehensive coverage of NLP concepts, practical assignments, and a focus on real-world applications.

3. Recommended Resources

3.1 Books

  • "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
  • "Hands-On Machine1 Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron
  • "Speech and Language Processing" by Daniel Jurafsky and James H. Martin

3.2 Websites

3.3 Libraries

  • Transformers (Hugging Face): A powerful library for working with pre-trained transformer models.
  • TensorFlow/PyTorch: Popular deep learning frameworks for building and training LLMs.
  • LangChain: A framework for developing applications powered by LLMs.

3.4 GitHub Repos

4. Conclusion

This white paper has provided a comprehensive overview of video courses on LLMs offered by Udemy, Packt, and Coursera, along with valuable resources for further learning. By exploring these resources and engaging in hands-on projects, learners can gain a strong foundation in LLMs and unlock their potential for innovation and impact.

Disclaimer: This information is provided for general knowledge and educational purposes only. The recommendations and resources provided may change over time. It is recommended to conduct further research and evaluate courses based on individual learning goals and preferences.