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JustI will give my perspective of how to learn AI. I myself was in the same situation as you are now. I didn't know where to start and I dont know anyone who can literally guide me or show me the well driven and systematic path to learn AI.
So I started learning from here and there, took one course on udacity and while learning that course I found out their are many things used in that course which I don't know about . AI is reinforcement learning. While learning the course,I came across the terms like supervised learning ,machine learning etc etc.
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Firstly , AI is not one independent field, atleast thats what I have figured out so far. You need to have knowledge of a lot of independent fields like neural networks , deep learning, machine learning and so and so on. So I started with machine learning ,halted the AI course mid way cause I could not connect the dots as I didn't know most of the terminologies. It was a long journey like 2–3 months only after that I was able to figure out where to start from.
I learned few algos of machine learning like linear regression, logistic regression etc etc. What is the technicality behind this ? Well, I couldn't answer myself . Just knowing how to implement things and not knowing what's happening behind it, is not my area. So I went on to dig deep down.
I figured out that statistics, linear algebra and probability are the main topics that have been implemented in those algos. I didn't have good acedemic, even in college I didn't study well statstics and probability.
So I started looking for courses here and there which teaches in such a way so that I can relate statistics and probability to real life problems and how they are implemented in machine learning. I found one course ,probability and statistics,by Stanford University . This course not only teaches you these topics as calculation method but how you can use these topics in data science . You can start from there.
There is also one course by prof. Andrew Ng on machine learning on Coursera (not sure) , take that as well it will give you insights about machine learning and this course is as simple as it can get. Prof.
Andrew Ng has explained things the way that you can visualise it . Course is good but as it progresses it uses statistics, probability and linear algebra, so I recommend first you get good with these topics and then take that course. You can use R or python among other languages used to implement ML. Both R and python are very strong and have a lot of libraries to implement ML.
Journey to self learning of AI or in that case any of its independent fields could be very difficult if you don't have well planned path, like I started from studying AI, then switched to ML and now I am doing basics like stats and probability.
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Few points:
I am no expert just a beginner ,who aspire to eat AI algos for breakfast one day.
I may not be completely right with few things and others may disagree with my answer. Well, I also did with many answers on quora to the question, how to learn AI. But after spending like 5–6 months desperately studying and trying to figure out the path ,I have reached to above conclusions.
When self learning AI , be patient , be curious to find every small small details. Don't overlook any concept or term you come across and couldn't understand. It's a long path, enjoy the process of learning rather than thinking about only goal. You will enjoy it,then.
Lastly, start only when you really have decided to learn it and is ready to give around one year completely to it without any second thought.
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