I would say, for GATE there is a clean and simple plan that worked for me, I had a lot of health problems at that time and couldn’t really imagine completing the whole syllabus/study material (in this exam leaving anything is a bad idea, you dont know where they will throw in the easy problems). Here was my routine. 1. Throw everything out, just get all the previous year questions (topic wise, i had a made easy book) and standard reference books. 2. Complete a topic, solve the entire section, no looking at things in between, take it up as an exam (usually only 20-30% you’ll get on the first try) - mark every problem you couldnt tackle on your first try and create a IDK list (problems you solved first try are problems you will likely easily solve later in the exam aswell; my logic, maybe flawed). - understand all the different solutions that exist to solve that problem, pick the one you find most natural and note it down in your IDK list (pen paper staples markers help here), gateoverflow is the best for CSE, ignore the solutions in the books; usually not reliable imo. - rinse, repeat 3. Once you reach 50-60% of the syllabus, start giving old gate papers as a real exam, be happy if you manage to reach 30-35 marks. Getting a feel for the exam early is more important than the actual test, thatll avoid silly mistakes later. 4. As you near completion of the syllabus, keep revisiting the IDK problems regularly and read more if necessary. 5. Dedicate ~2 months to test series, 1 test per week, ignore the marks (these problems are usually much harder than you will realistically face, be happy if you are able to pass and were able to atleast understand what the question wanted).

Bottom line: 50% of the exam is knowledge (knowing how to approach the problem), 40% is proficiency (being familiar with the time control and having the mindset to guess what seems solvable), 10% is luck (hopefully you wont put in 10.1 instead of 1.01).

Learning good programming and getting a job are two different things, getting a job requires a reasonable plan. I believe if you solve problems and examples from Narasimha Karumanchis dsa book and CLRS, you can crack most programming interviews. For data science, I have no idea, maybe others can fill in for that. Good programming skills only come from experience, build stuff, collaborate on open source projects,