AI Study Plan

• Short Deep Learning Course (3Blue1Brown) - https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
  • Large Language Models explained briefly - https://www.youtube.com/watch?v=LPZh9BOjkQs
  • But what is a neural network? | Deep learning chapter 1 - https://www.youtube.com/watch?v=aircAruvnKk
  • Gradient descent, how neural networks learn | Deep Learning Chapter 2 - https://www.youtube.com/watch?v=IHZwWFHWa-w
  • Backpropagation, intuitively | Deep Learning Chapter 3 - https://www.youtube.com/watch?v=Ilg3gGewQ5U
  • Backpropagation calculus | Deep Learning Chapter 4 - https://www.youtube.com/watch?v=tIeHLnjs5U8
  • Transformers, the tech behind LLMs | Deep Learning Chapter 5 - https://www.youtube.com/watch?v=wjZofJX0v4M
  • Attention in transformers, step-by-step | Deep Learning Chapter 6 - https://www.youtube.com/watch?v=eMlx5fFNoYc
  • How might LLMs store facts | Deep Learning Chapter 7 - https://www.youtube.com/watch?v=9-Jl0dxWQs8
  • But what is a convolution? (CNN) - https://www.youtube.com/watch?v=KuXjwB4LzSA
• Fundamental AI Courses
  • 1/ AI for Everyone (DeepLearning.AI) - 7h
    • Cut through AI hype and understand what it actually does.
    • Perfect when you need to sound more confident when speaking about AI.
    • See: https://www.deeplearning.ai/courses/ai-for-everyone
  • 2/ Introduction to Generative AI (Google) - 1h
    • Google's no-nonsense take on generative AI basics.
    • Real examples you can steal immediately.
    • See: https://www.coursera.org/learn/introduction-to-generative-ai
  • 3/ Prompt Engineering for ChatGPT (Vanderbilt) - 18h
    • Stop fumbling with prompts that don't work.
    • Learn the mechanics of getting AI to do what you want.
    • See: https://www.coursera.org/learn/prompt-engineering
  • 4/ Google AI Essentials - 10h
    • Google's blueprint for workplace AI literacy.
    • Practical applications across every industry.
    • See: https://grow.google/intl/uk/
  • 5/ Generative AI for Everyone (DeepLearning.AI) - 6h
    • Business applications that make sense.
    • Implementation focus, not just theory.
    • See: https://www.coursera.org/learn/generative-ai-for-everyone
  • 6/ AI Foundations (IBM)- 5h
    • Enterprise perspective on AI fundamentals.
    • IBM's approach to AI strategy that works.
    • See: https://skillsbuild.org/adult-learners/explore-learning/artificial-intelligence
  • 7/ CS50's Introduction to AI with Python (Harvard) - 7w
    • Harvard's rigorous programming approach to AI.
    • Real code, real algorithms, real results.
    • See: https://pll.harvard.edu/course/cs50s-introduction-artificial-intelligence-python
  • 8/ Artificial Intelligence (MIT OpenCourseWare) - 10w
    • MIT's complete AI curriculum without the tuition.
    • Deep technical foundation that actually matters.
    • See: https://ocw.mit.edu/courses/6-034-artificial-intelligence-fall-2010/
  • 9/ Career Essentials in Generative AI (Microsoft + LinkedIn) - 4h
    • Career-focused AI understanding.
    • Microsoft's take on workplace transformation.
    • See: https://www.linkedin.com/learning/paths/career-essentials-in-generative-ai-by-microsoft-and-linkedin
• Harvard Free Classes
  • CS50's Introduction to CS https://cs50.harvard.edu/x/weeks/ai/
  • The Science and Implications of Generative AI
    • How Generative AI Works https://generative-ai-course.hks.harvard.edu/1-how-genai-works/class-1
    • Deep Neural Networks https://generative-ai-course.hks.harvard.edu/1-how-genai-works/class-2
    • The alignment problem https://generative-ai-course.hks.harvard.edu/1-how-genai-works/class-3
    • Prompt Engineering https://generative-ai-course.hks.harvard.edu/2-using-genai/class-4
    • Beyond Chatbots https://generative-ai-course.hks.harvard.edu/2-using-genai/class-5
    • When and how to use generative ai https://generative-ai-course.hks.harvard.edu/2-using-genai/class-6
    • Using AI tools in practice: a case study https://generative-ai-course.hks.harvard.edu/2-using-genai/class-7
    • Risks of generative ai https://generative-ai-course.hks.harvard.edu/society/class-8
    • Intellectual property https://generative-ai-course.hks.harvard.edu/society/class-9
    • The future of work https://generative-ai-course.hks.harvard.edu/society/class-10
    • Mis/disinformation https://generative-ai-course.hks.harvard.edu/society/class-11
  • The Basics of Generative AI https://sites.google.com/g.harvard.edu/hksslate-genai/the-basics-of-generative-ai
  • GPT-4 - How does it work, and how do I build apps with it? https://www.youtube.com/watch?v=vw-KWfKwvTQ
  • Large Language Models and The End of Programming https://www.youtube.com/watch?v=JhCl-GeT4jw
• Stanford/ CS153 - Frontier Systems
  • Sam Altman / Scale, AGI, and the Future of Everything
• [Book]Hands-On Large Language Models: Language Understanding and Generation - Jay Alammar (Author), Maarten Grootendorst
• [Collection] https://30papers.com/ by Ilya Sutskever
• More resources:
  • Anthropic: https://anthropic.skilljar.com
  • Google: https://grow.google/ai
  • Meta: https://ai.meta.com/resources/
  • NVIDIA: https://developer.nvidia.com/cuda
  • Microsoft: https://learn.microsoft.com/en-us/training/
  • OpenAI: https://academy.openai.com
  • IBM: https://skillsbuild.org
  • AWS: https://skillbuilder.aws
  • DeepLearningAI: https://deeplearning.ai
  • Hugging Face: https://huggingface.co/learn

References

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