Hello everyone,
I’m an AI student but also an aspiring UX designer, and I’m starting a new UX project focused on helping people who are beginning to learn AI or those who want to expand their knowledge in AI through DeepLearning.AI courses. I’d love to hear more about you, what you’re currently doing, what inspires you to learn AI, and what initial challenges you faced when looking for information about AI.
Have you ever searched for Roadmaps or asked someone with experience for guidance in your learning journey? Do you think an interactive guide to help structure your learning path would be useful?
I would love to hear your thoughts, and please feel free to express yourself openly.
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I think such a guide would be really helpfull.
For the course I am currently doing (deep learning specialization) I was also thinking about a cheat sheet where the most important explanations and tipps and tricks are written down
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A learning guide would be great. Would be really interested to see it if you have one!
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Dear MarcoATL,
I am interested in exploring free LLMs and their applications, particularly having full control over the model, its source code, training data, weights, hardware, and API. My motivation for learning AI stems from the ability to accumulate and understand knowledge at a level that was previously unattainable within a human lifespan. While I currently don’t face significant challenges, 20 years ago, my primary obstacles were the programming language VC++ and not dedicating enough time. However, with the advent of tools like ChatGPT, I am now determined to harness the full potential of AI.
Regarding your questions:
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I am working on fitting topics within AI, ML, NN, GA, and DL to understand the broader picture. ChatGPT and cross-reasoning with it have been instrumental in deepening my understanding. If you’re starting from the basics, I recommend the book available at scipy-lectures.org, which includes chapters on AI using scikit-learn. All examples can be reproduced in your own Jupyter notebook. For theoretical understanding, IBM offers excellent resources, including videos on AI topics. For more recent content with hands-on exercises, consider the short courses on DeepLearning.AI. If you’re looking to cover AI comprehensively, their specialization courses are a great choice. For reliable news on the latest developments, subscribe to the DeepLearning.AI mailing list. Hugging Face also provides excellent tutorials and reviews. If you’re interested in building your own LLM from scratch, I suggest following the YouTube playlist by Andrej Karpathy. Additionally, if you want to learn foundational topics through video, the YouTube channels 3Blue1Brown and StatQuest with Josh Starmer are excellent resources. These sources are reliable and original, whereas many others tend to be reproductions or potentially misleading.
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An interactive guide that combines video content with interactive and downloadable notebooks would be highly beneficial. If you’re looking to master a topic with scattered resources, I recommend using Google’s Notebook LM or developing your own RAG with better features than those I just mentioned.
I hope these points are helpful for your UX project.
Best regards,
FR
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Hi, Paul! I’m glad you find the idea of a learning guide helpful. It would be great if you could share a bit about what you do currently and how your experience has been in finding a learning path in AI. Have you found it challenging, or would you prefer having a clearer structure with the specialized programs from DeepLearning.AI? I’m working on a project about learning paths, and I’d love to know if you’d be interested in a guide with different AI areas so you can explore topics like natural language processing, computer vision, etc.
Hi, Nico! I’m happy to hear you’re interested in a learning guide. Would you mind sharing a bit about your career and whether you’ve had any difficulties finding a clear path to learn AI? I’m working on a project that focuses on AI learning paths using DeepLearning.AI’s specialized programs, and I’d love to know if a guide covering various AI areas (like computer vision, natural language processing, etc.) would be helpful to you. Looking forward to your thoughts!
Thank you so much for your detailed response and suggestions! I truly appreciate your insights and the resources you shared. Your experience will be really helpful as I continue working on my UX project. Thanks again for taking the time to contribute!
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Overall I would say the course is very good. I just would wish a comprehensive summary or a mind map like most important points would be helpfull (I am currently doing one myself and when finished will post it here).
I am also more on the technical side so doing also all the math (also without proofs) helped me to deepen my understanding from what I am actually doing.
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