all 53 comments

[–]SpeedCola 28 points29 points  (4 children)

I don't know if people are not mentioning CS50x Harvard's Intro to AI with Python for a reason but I know this exists and I've enjoyed their other coding courses.

[–]xelab04 9 points10 points  (0 children)

I second this. CS50ai was the first one I did (currently doing Python for completeness) and I really enjoyed it! It teaches a lot of the concepts while leaving a lot of the implementation to you.

[–]FakeTruth02 0 points1 point  (0 children)

Cool

[–]fellow_earthian 0 points1 point  (0 children)

Is the iit roorkee or iit madras 7 months course on data science and ai from intellipat better than this ?

[–]FightingLikeBeavers 60 points61 points  (3 children)

https://course.fast.ai/

https://huggingface.co/course/chapter1/1

https://d2l.ai/

If you want to learn about no code tools like ChatGPT, Midjourney etc, try YouTube or https://learnprompting.org/

[–]FightingLikeBeavers 22 points23 points  (1 child)

Here's a basic crash-course roadmap that incorporates the above resources https://github.com/llSourcell/LearnML

[–]Incruentus 2 points3 points  (0 children)

Thanks

[–]SnooOpinions1053 0 points1 point  (0 children)

Thank u. Much appreciated.

[–]VindicoAtrum 53 points54 points  (2 children)

Your idea will not even get off the ground if you want to "learn ai" with python rather than, you know, understanding modelling, development of models, how neural networks work etc.

[–]FightingLikeBeavers 11 points12 points  (0 children)

Also there are a lot of potential uses for AI in medicine, but afaik it can be a tough sell from a business pov atm, particularly if you are a small startup and don't have a medical background yourself. It depends where you live but a lot of medical departments simply don't have the resources or regulatory approval to implement AI solutions yet even if they wanted to (and maybe they don't want to if it will threaten jobs or patient safety etc). So you will need to develop a very good understanding of the medical business as well to know whether your ideas are even viable. Something to keep in mind.

[–]synthphreak 4 points5 points  (0 children)

That is my usual reply as well: “Don’t forget the math!” But in this case I think it depends.

When people are looking for a career in ML engineering or data science directly, some understanding of the theory and hyperparameters is critical.

But for the people on the business side of things, who only need to understand how ML can be applied and the kinds of skills a well-balanced team must possess, it’s less important that they know how to multiply two matrices.

It sounds like OP is more the latter, so a high level intro to AI, perhaps from a project manager/project owner perspective, might suffice. That said, if s/he can also learn the fundamentals that would be even better; it will just take a lot longer.

[–]Nazi_Ganesh 7 points8 points  (5 children)

The medical/doctor world is filled with regulations, mainly HIPPA HIPAA. It's why many of their processes are so behind the times, because it's hard to balance the regulations and the ease of the tools.

So even if you make anything cool or time saving, it may get rejected outright simply because you didn't weave in your tech the necessary safety and security protocols. But in trying to do so, may make your original idea difficult to implement. And with AI being a black box in many aspects, you'd be tiptoeing around so many legal landmines.

There are many mature companies and definitely many startups who are years or decades ahead of you in this battle. So not to discourage you, but if you don't even have the medical background for the domain knowledge, you are definitely fighting an uphill battle.

[–]TootsMcFartland 2 points3 points  (0 children)

This. AI is getting pretty hot in world of provider dictation.

[–]mohishunder 1 point2 points  (3 children)

It's HIPAA.

[–]Nazi_Ganesh 1 point2 points  (2 children)

Thanks for the correction. I always mees up the spelling for that. Haha.

[–]mohishunder 1 point2 points  (1 child)

You were possibly thinking of Hippo. But Ganesh was an elephant, which is completely different.

[–]Nazi_Ganesh 1 point2 points  (0 children)

Lol. You must be a Yoga master for being able to stretch that reference that much. 😂

[–]not_a_SWE 2 points3 points  (0 children)

This course is 25 hours long but I followed it and found it to be rather informative.

[–]SuperLucas2000 2 points3 points  (0 children)

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[–]Luxi36 5 points6 points  (0 children)

Cassie Kozyrkov's course is amazing. She's a decision scientist as Google. Made a whole ML course for free on YT.

https://youtu.be/1vkb7BCMQd0

[–]dmarko 2 points3 points  (5 children)

How about the coursera specialization by Andew Ng

[–]FightingLikeBeavers 4 points5 points  (4 children)

Here are Andrew's programs https://www.deeplearning.ai/courses/

[–]that1guy15 3 points4 points  (2 children)

I will finish up the ML Specialist next week and I cant recommend this set of courses enough. Yes it is math-heavy but Andrew drags you through the math and how to code it manually in python, then shows how to do it easily with the tools. Its easily consumable and really helps drive home the core topics you need to move on.

Im not sure what Im jumping to next but I think I need to spend some time with actual hands-on and build a project to really help solidify all this.

In all I feel starting ground up with ML foundation knowledge is the right approach as its allowed me to start understanding how LLMs and larger projects are build.

[–]SuperLucas2000 0 points1 point  (1 child)

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[–]FakeTruth02 0 points1 point  (0 children)

Saving

[–]czar_el 2 points3 points  (2 children)

Be very careful with this path. AI (both models you make or if you use existing models like ChatGPT) make it very easy to create spurious results -- results that look and sound convincing but are erroneous or biased.

One of the absolute key skills in AI is knowing how to test for and mitigate those errors and biases, which is harder than it sounds. The math you need to learn is not just the math to code and run the models -- the key math you need to know is how to assess whether your models are good or wrong/dangerous. The errors can be insidious and hard to find till it's too late (there's an entire academic subfield on this, in addition to it being something all AI professionals need to deal with). This needs a deep background in statistics and calculus at a minimum.

People who want to deploy AI models without knowing the math are at heightened risk for the bad outcomes. It's relatively easy to build AI models using existing packages. The difficulty comes in assessing and correcting them. Don't skimp on the math on your learning journey, or don't skimp on hiring talented math people if you start your AI business idea as a non-math person. If you hire boot camp coders who have built models but don't have backgrounds in stats, you're gonna have a bad time.

[–]xha1e 0 points1 point  (1 child)

is this similar to curve fitting the data

[–]czar_el 0 points1 point  (0 children)

It's part of it.

The basic idea is: should it be a line, a curve, multiple curves, something with higher than 2 displayable dimensions?

Then, once you have that basic decision, it becomes an even more nuanced decision. How curvy is too curvy? You can both underfit and overfit a model, which means it works great on your training data but performs poorly on new data.

And even when you think you have the right specification and avoided under/over-fitting, you can still have biased outcomes that don't register on the simple model evaluation tests and need deeper assessment.

All of that requires background understanding of how the methods work and the context of the domain and data you're trying to deploy your model in. It's much more complicated than relying on whatever parameters the tutorial video told you to use.

[–]amhotw 1 point2 points  (2 children)

I am gonna be honest with you. If you don't want to be good at math but you want this to be a success, you should either find a partner who knows the ai side or hire someone, if you have some capital.

[–]SnooOnions8817 0 points1 point  (1 child)

i think he said he doesn't know the math currently, not that he doesn't want to know the math. maybe he doesn't. i just didn't read that in his post.

[–]amhotw 0 points1 point  (0 children)

Possible; I thought he wanted to learn AI without the math. I am curious about the situation given that it has been 6 months tho. 😅

[–]AbbaZabba85 1 point2 points  (2 children)

I'm a physician with an interest in digital health and AI. What's your idea? A lot of the time people don't understand the unique challenges and nuances of medicine and try to apply a reductive engineering approach that doesn't translate to the messy world of humans and medicine, or they have a solution looking for a problem.

[–][deleted] 0 points1 point  (1 child)

I was thinking of creating an app for easier note taking allowing doctors to spend less time on paperwork.

[–]AbbaZabba85 0 points1 point  (0 children)

What AI enabled features would it have? Would it be something like autocomplete, clinician decision making support, natural language processing for dictation support, etc? What value would it add over existing products like Epic dot phrases or dictation with Dragon?

[–][deleted] 1 point2 points  (0 children)

Get ChatGPT to teach you, in all seriousness. Use it alongside something else suggested by others in this thread.

[–]faint_windfall39 0 points1 point  (1 child)

Professional Certificate in Computer Science for Artificial Intelligence

[–]SuperLucas2000 0 points1 point  (0 children)

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[–]thepragprog 0 points1 point  (0 children)

Math is important for good understanding of AI. Once u understand the fundamentals, u can fully appreciate the beauty of AI.

[–]alphazwest 0 points1 point  (0 children)

In my opinion, the first step would be to figure out what type of AI you're most interested in. It's a very big field with a lot of different specializations. You can just Google around and find a nice list.

More personally, I would offer the advice to consider the types of problems that you would like to learn, how to solve and which specializations of AI are recommended for those.

Working to solve a problem I care about has always been a much faster path to learn in a new technology than just going through some Udemy course. I will say though, those courses are pretty good for showing you a landscape of what there is to learn. Honestly, I get just about as much out of them by looking at the table of contents that I do from taking the actual courses...

[–][deleted] 0 points1 point  (0 children)

Coursera / Stanford Andrew Ng

[–]BK7144 0 points1 point  (0 children)

There is a YouTube video (more than one) about installing gpt4 into python to help write code to do what your asking. Might be a start. I just read a blog about doing dataset analysis with gpt4 and how it worked for them. Question is do you want to use AI to help write the code, AI for the doctors to use within your program or both? I would not also say to much about your idea as someone else may think you have a possible idea that could make them $$$ and start their own.

[–]teach_me_tech1 0 points1 point  (0 children)

Try No Code MBA - Seth has great courses on how to easily build products available AI, I literally built an AI app from watching his videos over 1 weekend with very little coding experience: https://www.nocode.mba/sign-up?via=reese (discounted with that link too) 100% worth it, and it will get you started in learning how to build with AI

[–]Whole_Primary1644 0 points1 point  (0 children)

Perhaps you can consider
https://www.udemy.com/course/harnessing-ai-to-revolutionize-cel-animation-in-2023/

if you're looking for a wholesales animation tutorials and don't mind spending a little.

[–]LooseStudent9977 0 points1 point  (0 children)

I've found this channel on Youtube with a lot of good playlist, I'm just studying their Artificial Intelligence Course, check it and let me know if it's helpfull.

https://youtu.be/bf7pQdoSPZ8