I'm a frontend developer who wants to move into AI engineering by learning Python, the necessary math, machine learning, and related technologies. I learn best by building projects, so I'd like to avoid tutorial hell and a purely book-based approach. I'm looking for a practical roadmap and an AI setup that can help me plan projects, explain difficult concepts, quiz me, review my work, and provide guidance without simply writing everything for me. I've tried Cursor with its automatic mode and planning agent and found it useful. How does it compare with tools such as GLM, Codex, Gemini, DeepSeek, Kimi, Zed, Kiro, or Windsurf? I'm also looking for reasonably priced options.
4 Answers
AI can help organize a curriculum, but it can’t replace actually studying the fundamentals. If you want to understand how models work rather than only build applications around existing APIs, make sure you personally work through the math, implement algorithms, and debug your own code. Otherwise it’s easy to produce impressive wrappers without developing real AI-engineering skills.
For a project-based path, focus on Python first, then linear algebra, probability and statistics, machine-learning fundamentals, deep learning, LLMs and generative AI, retrieval and agents, and finally deployment and MLOps. Build a small project at every stage. A simple combination such as ChatGPT or Gemini for learning and planning, Cursor for implementation, and DeepSeek or Kimi for occasional second opinions is enough. Constantly switching tools is likely to slow you down.
Since your goal is learning rather than just shipping, don’t let the assistant write code that you couldn’t reproduce yourself. Ask it to explain the reasoning, derive math step by step, critique your solution, and quiz you before moving on. You should type most of the code and use the model as a tutor and reviewer. The specific model matters less than maintaining that habit.
A practical setup is to use one general-purpose AI tutor for explanations and planning, plus one repo-aware coding assistant for implementation. ChatGPT or Gemini can create milestone-based roadmaps, explain math, generate quizzes, and review your understanding. Cursor or Windsurf can help with scaffolding and multi-file project changes, while Zed is convenient for lighter editing. DeepSeek or a local model through Ollama can provide cheaper second opinions. Try each tool on the same small project and compare the quality, errors, time saved, and cost.
That’s fair. I’m mainly interested in using AI for planning, explanations, and checking my understanding, not having it generate all the code. I still want to build the projects and learn the fundamentals myself.