I studied at a technical high school and have beginner-to-intermediate experience with C, Java, PHP, MySQL, and HTML/CSS/JavaScript. I'm now in my first year of an economics and technical degree focused on data science for business and finance.
Over the next few months, I want to become genuinely competent in Python, and possibly C++, with the goal of applying for a summer internship in machine learning or quantitative finance. I'm currently about one-third of the way through Think Python because I never formally learned Python, but I'm unsure what the best next step should be.
Should I follow a structured course, work through more books, build projects, or combine all of those approaches? I also struggle with procrastination and often leave projects unfinished, so I'm looking for a practical study plan that will help me stay consistent and make real progress.
3 Answers
Stop collecting resources and pick one clear path. Finish the introductory Python material, then build a small project related to your interests—for example, analyzing financial data, testing a simple trading strategy, or training a basic machine-learning model. Recreate an existing project first, then change it and extend it so you understand every part.
Use a combination, but keep it simple: spend a limited amount of time learning fundamentals, then spend most of your time applying them. Break one project into very small milestones and publish or demonstrate each finished stage. A fixed weekly schedule and studying alongside reliable people can help more than searching for the perfect course.
Don’t aim to master programming in a few months, and don’t get too attached to a specific language. Choose Python for now and focus on solving problems with it. Books and courses can give you structure, but programming is learned mainly by writing, debugging, reading, and explaining code. Find classmates or friends who are also motivated and work through projects together.
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