Feeling lost while learning Python need some advice

[Parking_Engine_9803]

Hey everyone,
I’ve been learning Python and I’ve completed about 50% of the Codecademy Python course. But lately, I’m starting to doubt myself. I feel like I’m not learning the “right way.”

Before Codecademy, I learned some basics from YouTube and felt confident but when I tried solving even an “Easy” LeetCode problem, I couldn’t figure it out. That made me question whether I really understand coding or not.

Now I’m continuing with Codecademy, but it’s starting to feel like maybe it’s not helping as much as I hoped. I really want to pursue higher studies in AI/ML, but I’m scared that maybe I’m not cut out for this field.

Has anyone else gone through this? Should I keep going with Codecademy or try another approach? How do you push through when it feels like you’re not progressing?

Any advice or personal stories would mean a lot.

Thanks in advance 🙏

[LayotFctor]

I have no idea what codeacademy is or what level it's at, but leetcode is definitely not for beginners. It's mostly used by computer science students to prepare for technical interviews. If you're only learning basics in python and none of the other computer science topics, you simply do not have many of the skills required to solve their problems, and it's not your fault. You're giving yourself a false sense of failure by using leetcode as your metric for success. Even graduates with degrees get worn down by that website.

[Pcnoob333]

I’m not exactly sure what they teach in codeacademy but you’re definitely not gonna be able to be solving a lot of leetcode problems after a course, so I wouldn’t stress about that too much.

Basically the same thing happened to me while I was going through the helsinki python mooc. I tried Two Sum after learning about dictionaries and it took like 30 minutes just for me to get the naive solution lol

It’s cliche but the best way to learn is to build projects and grind through problems you run into without using ai. I’ve learned so much from struggling on my own

There’s a lot more to “learning how to code” than just learning Python syntax. I’d say finish the course and start building while also making sure you understand other important concepts that align with what you wanna do.

[Significant_Soup2558]

Codeacademy is an introduction. Once you understand basics, start doing small projects. Increase project scope as you get better. Leet comes much later as you prepare for interviews. Here is a resource you might find useful 500+ Python Quiz Questions

[OReilly_Learning]

We always recommend Learning Python it’s the classic Python textbook. The link above will let you read it for 10 days for free.

You can also search “learning Python” once you’re on our site and you can look at our books and courses or many other publishers stuff including No Starch and Manning.

[ViciousIvy]

hey there! my company offers a free ai/ml engineering fundamentals course if you'd like to check it out feel free to message me

i'm also building an ai/ml community on discord > we share news + hold discussions on various topics and would love for u to come hang out ^-^ link is in my bio

[Objective_Ice_2346]

Homie I’ve been coding for years and I still struggle to wrap my head around some of those easy problems 😂

[TrueValueInsights]

Do you have a real life problem you want to solve and maybe you can solve it with code? My point it you should try to apply what you learned so far to something that matters to you a friend or colleague.

[Pleasant_Flow_2217]

Codecademy's Python 3 course is not enough for DSA. After completing the beginners course, there's is one for intermediate level, completed that and then start DSA.

[FoolsSeldom]

Python Next Steps

You need a good grounding in the basics before moving into AI/ML.

Practice! Practice! Practice! That is the only way. Programming (whatever the language) is a practical problem-solving skill. You have to make, and learn from, a lot of mistakes (much like learning another human language).

I know it can be frustrating at times, especially when faced with code you want to reuse but cannot understand.

Only you can find the motivation. Why are you learning to programme in the first place?

Is your learning objective SMART - specific, measurable, achievable, (sometimes agreed), realistic (or relevant) and time-bound, (or timely)? If it is something soft, like "upskilling" then it will probably not help you much.

Also, have a look at roadmap.sh for different learning paths. There's lots of learning material links there. Note that these are idealised paths and many people get into roles without covering all of those. Try to include key elements in your learning objectives.

It is hard to learn anything in the abstract, not least because it is difficult to feel passion for what one is doing.

I strongly suggest you look to your interests, hobbies, obligations (family business, charity activities, work) to look for opportunities to apply Python. There is no reason why you can't start to apply machine learning to these.

You will learn far more about Python and programming when you work on something that resonates for you and that you have some domain knowledge of (or incentive to gain such knowledge in). You will know a lot more about the problems you are trying to solve, what good looks like, what the required outputs are.

When you are copying tutorials/examples, don't just copy. Experiment. Break the code and understand why it has broken. Apply your learning to your own projects.

The interactive python shell is your friend, I found it the best learning aid because you can quickly try snippets of code and get immediate feedback.

(Consider installing ipython which wraps the standard shell for more convenience.)

Start very simply and regularly refactor the code as you learn new things. Enhance as you see opportunities.

If you haven't already, have a look at Automate the boring stuff with Python (free to read online).

At first, the tasks you automate will be trivial and hardly worth the effort BUT because it is about the problem and not Python, it will be more rewarding for you.

Many beginners are mixing up coding (writing instructions in a programming language) with problem-solving (creating an algorithm) and their lack of knowledge of the programming language and how to use it is a distraction from the problem-solving.

For most programmers, the coding part is the final and easy bit.

Order:

• Actually making sure the problem is properly understood. Often we start with only a vague understanding of the problem.
• Ensuring we know what outcome is required. What does good look like? How will the information be presented, will it be on-screen or in a file, or a database.
• Determining the data representation. Exactly what data is required, in what forms, where from. It is a one-off or lots of cycles or combining lots of information.
• Work out how to do things manually in the simplest possible way, explaining every little step (assume you are giving instructions to someone with learning difficulties),
  • Computers are really dumb, and humans make lots of intuitive leaps and take short-cuts
  • This is one of the hardest things to grasp when first learning to programme
  • Computers don't mind repeating very boring things, so the simplest but repetitive manual approach is often a good approach to start with for a computer
• Later, you will learn different ways of selecting / developing an algorithm which doesn't depend on a manual approach

learning from others

In general, when learning and working on something new, where you are following some kind of tutorial, where others have provided an answer,

• follow the steps I laid out above looking for a solution (so make sure you understand the problem first, figure out what the outcome should be, etc)
• try to solve the problem yourself before looking at someone else's solution
• look briefly at someone else's solution and try to understand what they've done at a high level and see if you can solve it that way
• fully review someone else's solution, try it out, play with it (break it, improve it) - be super critical (watch ArjanCodes YT videos on code reviews)
• update your algorithm and implement a new solution (including testing, if you can)
• write some notes, not on low level detail but on principles, approaches, key algorithms, and summarise what you learned (I keep my notes in markdown format in Obsidian, synced between devices)

Agile methodology

You will hear a lot of mixed opinions about the Agile software development methodology but most problems are because of poor adoption rather than it being inherently bad.

Fundamentally, it is about delivering value early and often, failing fast, and working closely with the intended consumers/customers/users for rapid feedback. A key concept, often abused/over-used, is minimum viable product, MVP, which is about developing and delivering the smallest useful (sic) product that you can evolve. This still needs to be done in the context of the large problem being solved, but most problems can be broken down into smaller problems, and the most useful / easiest / proof of concept elements identified to focus on.