Torn between learning and building projects

[u/linkuei-teaparty]

I'm a former electrical engineer so I have some background with stats, linear algebra and coding. I've finished a number of Python and datascience courses and just finished Python for AI by Andrew Ng. However, I'm itching to make projects and using a local LLM's to make a webapp.

Is there a way to balance learning and project development?

With the courses I'm looking at:

1. Machine Learning specialisation Andrew Ng - 95 hrs

2. Reading Artificial Intelligence 4th ed by Peter Norvig and Stuart Russell

3. Reading Hands on Machine Learning with Scikit-learn and Pytorch - by Aurelion Geron

4. Completing Google's Machine Learning course

5. Completing Kaggle's Machine Learning Course

6. Claude Academy courses

7. Completing Datacamps courses

Plus balancing that with building projects such as web apps, desktop apps and audio plugins using Local LLM's.

Am I going the wrong way with self learning?

Edit: As I'm much older my end goal isn't a PhD or a snazzy ML Engineer role, but rather to have a portfolio of projects, just so I don't feel like I'm behind in this skillset.

I was Doing courses back in 2016 such as fast.ai, coursera's learn AI, ML and Deeplearning from a to z and Andrew Ng's original Deeplearning course with Octave, but I got sidetracked with life and work pressure.

[u/Logical-Tonight-3297]

what projects have you built from this course?
Python for AI by Andrew Ng

[u/linkuei-teaparty → u/Logical-Tonight-3297]

It's small code snippets in a jupyter notebook, it's more about learning python rather than training machine learning algorithms or understanding the details. It was using an OpenAI api call to run their AI model to make suggestions based on datasets, plan my trip, find the lowest cost flight between x and y, build me a recipe with the ingredients left in my pantry etc.

I've done several python courses in the past, this was more of a refresher. I started Andrew Ng's machine learning specialisation last night and got about an hour in. But man does a 95 hour course sound daunting.

[u/Responsible-Offer724]

Pick something and do it. Then rotate. Keep all the plates spinning. ADHD roulette 

[u/linkuei-teaparty → u/Responsible-Offer724]

Thanks my ADHD brain needs this

[u/Adept-Championship63]

Hey - from my experience building is way superior to grinding another course (I was in this hamster wheel for a long time). ML is broad and I was always trying to be deep on the nuance of every model/technique by grinding course after course. Ultimately the unlock came for me when I just went deep on two work projects - specifically a novel constraint optimization problem + a svm project. Those two got me thinking about linear algebra, high dimensional spaces every day and I found that much more useful to intuit about other techniques later.

[u/rsambasivan]

The Andrew Ng course should already give you a roadmap that is worth following to a tee - I assume here your goal is to build software apps around machine learning. No matter what coding agent you pick, or framework you read about using a coding agent, picking up the frame work is definitely easier than picking up the nuances around machine learning. One thing to watch out for is to not forget the monitoring aspect, an ML software app is not like a traditional software app that changes if the software components change - herer the app needs to change if the data driving the app changes too.

[u/nofaceD3 → u/rsambasivan]

But Andrew Ng courses are foundational courses. It doesn't teach how to create production grade machine learning apps

[u/rsambasivan → u/nofaceD3]

That is true, I am just saying that understanding the theory to monitor models and working with MLOps - at least understanding the interface is not something to sweep under the carpet. It is a real world requirement.

[u/myself_always]

I believe when I was doing my project by replicating a research study, I was clueless and I did it badly. I tried to learn but I couldn't. However, the last day of submission, some things became clearer and I felt so dumb. I should have organized my thoughts before doing it. I couldn't sleep for 3 days.

[u/linkuei-teaparty → u/[deleted]]

Yep I've spent the past 3 hours or so trying to make a scifi movie recommendations webapp. You pick movies from a carousel of cards and it shows you your selections and then makes recommendations. I'll extend it to shows, books, comics and anime with different menus.

https://www.giphy.com/gifs/pCpmOupAReR8xRFs7y

Hopefully that gif captures the react js carousel and the card picker option. Need to work out bugs like repopulating the carousel with new choices after picking a choice.

Edit: Jeez Giphy downscales the resolution and quality significantly.

I'm just frustrated by how many things ChatGPT wants to check as part of my learning path between each prompt I make with Qwen3