Turning a single course into a career is a worthy ambition, but the method matters more than the milestone. The question isn't whether you should take notes from every lecture, it's whether your current system is building understanding or just accumulating paper. If you're generating three to five pages of notes from a fifteen-minute video, you're not studying; you're transcribing anxiety. That density is a signal, not a strategy.
The instinct to capture everything is understandable. You want to be interview-ready, and missing a subtle point feels like a risk. But here's the uncomfortable truth: notes that try to be comprehensive become impossible to revise. When every topic gets equal weight, nothing stands out. You lose the ability to distinguish the core idea from the supporting detail, and that distinction is exactly what separates a data scientist from someone who merely watched the videos. This is where a more deliberate approach pays off. Instead of asking AI to expand a transcript, ask it to compress it. Pull out the one or two concepts that truly matter, the formulas or frameworks you must internalize, and leave the rest as context. Your notebook should be a place for the ideas that need repetition, not a full transcript of every course you've ever taken. For a broader sense of what this path actually requires, our weekly compass for navigating a career in data science and our guide on charting your path into data science offer practical frames for pacing yourself.
The deeper issue here is trust, trust in your own retention and trust in the learning process. Writing things down does help memory, but only when you're writing the right things. A better rule is to write what you couldn't explain out loud without looking at the screen. If you can paraphrase a lecture's main idea in a few sentences, you've understood it. If you can't, more pages won't fix that. Use AI to check your understanding instead of generating volume. Ask it to quiz you on the topic, or to compare your one-paragraph summary against the lecture's key points. That turns the tool from a note factory into a study partner. And when you revise later, you're not rereading pages, you're testing yourself against a short list of essential ideas. That is how you retain knowledge across hundreds of lectures without drowning in them.
One concrete takeaway: cap every lecture at one handwritten page. If you can't fit the essentials there, you haven't identified what's essential yet. That constraint forces you to prioritize, which is a skill in itself. Apply this to the Andrew Ng course you're starting, and you'll finish it with notes you actually revisit, not a binder you're afraid to open. The goal isn't to document the course; it's to internalize the concepts so they work for you in an interview or on the job. If your current method leaves you with more paper and less clarity, change the method. The course is the map, not the destination.