
Start with one language that matches your goal. Python is a practical default because it supports web work, automation, and data analysis with readable syntax. Follow a free introductory course that teaches variables, loops, functions, and files, then move to small exercises where you fix real bugs. After the basics, choose a direction: build a simple command-line tool, create a web page, or analyze a public dataset. Learn Git early so you can save versions and share work. For data, practice loading a CSV, cleaning missing values, summarizing columns, and making one clear chart. Keep a project journal with the question you asked, the method you used, and what the result means. Publish your code in a public repository with a short README. Free resources become powerful when they lead to finished artifacts that you can explain, improve, and reuse in future work.