MHB How to deal with learning plateau in CS?

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Reaching a learning plateau in computer science can be frustrating, especially when trying to grasp advanced concepts like artificial intelligence. Engaging with practical projects rather than abstract theories enhances understanding and retention of coding principles. Many suggest following structured courses, practicing deliberately, and reading material aloud to reinforce learning. Revisiting foundational math and computer science subjects is common and can be beneficial, even if it requires significant time investment. Emphasizing hands-on problem-solving is crucial for overcoming stagnation and deepening comprehension in the field.
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I have reached a place where I can no more learn new concepts. I feel totally stuck.How do I deal with learning plateau? How do I overcome this plateau. Few things that come in my mind-:

1) Follow a good course from a good teacher.

2) Read it aloud.

3) Practice the same thing multiple things to get insights. deliberate practice

What else can I do to overcome this learning plateau? https://drive.google.com/file/d/1fpksOvK5bLVC5C0njB-fNPgzOwj4GjqW/view These are the types of questions I need to deal with and where I am facing this learning plateau..
 
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I work in the tech industry for a machine learning software company. I also have a theoretical and not so practical interest in coding concepts and topics. In my path to learning Python really well over the last few years I've discovered that trying to solve actual problems is better for my learning than abstract hypotheticals. If I am learning about classes for example, I can cover the basics with some videos and tutorials, but unless I start coding object-oriented projects I won't care of have use for these concepts. Same thing for machine learning. I can answer all the questions in the world about unsupervised vs. supervised learning, defining NLP, etc. but if I don't use them I will not really appreciate or care about the nuances.

What do you want to do in CS?
 
Jameson said:
I work in the tech industry for a machine learning software company. I also have a theoretical and not so practical interest in coding concepts and topics. In my path to learning Python really well over the last few years I've discovered that trying to solve actual problems is better for my learning than abstract hypotheticals. If I am learning about classes for example, I can cover the basics with some videos and tutorials, but unless I start coding object-oriented projects I won't care of have use for these concepts. Same thing for machine learning. I can answer all the questions in the world about unsupervised vs. supervised learning, defining NLP, etc. but if I don't use them I will not really appreciate or care about the nuances.

What do you want to do in CS?
Currently my goal is to learn artificial intelligence and excel in theory. So that I am ready for advanced concepts. I have math foundations as I am engineering student and studied tons of mathematics. And was really good at it. But it feels like I need to re read all these math and cs subjects as I didn't make proper notes for this subject. Will take me full 1-2 year to do all this.. What do you think about this? Is this normal? Did you guys had to reread your college subjects again after graduation...I wish I made proper notes :(
 
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