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ML Engineer

Machine learning, deep learning and model evaluation.

5 courses8 projects59 lessons~54h

Skills you'll build

LoopsVariablesConditionalsPython Data HandlingPython BasicsFunctionsProblem SolvingComputational Thinking

Your progress

0/59 lessons · 0%

Next step

Programming Foundations

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Courses in this path

  1. 01

    Programming Foundations

    Think like a programmer: values, logic, loops, functions and problem solving in JavaScript.

    ~14h17 lessons3 projectsbeginner

    start
  2. 02

    Python Foundations

    Learn Python from zero: syntax, data, control flow, functions, errors, and files.

    ~10h12 lessons2 projectsbeginner

    Finish Programming Foundations first.

    locked
  3. 03

    Algorithms & Data Structures

    Think algorithmically: master arrays, Big-O, searching, sorting, stacks/queues, hash maps, recursion, trees and graphs.

    ~12h10 lessons1 projectintermediate

    Finish Programming Foundations first.

    locked
  4. 04

    Modern AI Engineering

    Build real, production-minded features on top of large language models: prompting, structured output, embeddings, retrieval, tool calling, evaluation, and shipping responsibly.

    ~10h10 lessons1 projectintermediate

    Finish Programming Foundations first.

    locked
  5. 05

    Machine Learning Foundations

    Understand how machines actually learn from data, explained in plain language with runnable code.

    ~8h10 lessons1 projectintermediate

    Finish Programming Foundations first.

    locked

Projects you'll complete

  • Machine Learning Foundations Capstone

    Build the core toolkit every ML workflow depends on: splitting data honestly, measuring how good predictions really are, and scaling features so models learn fairly.

  • Build a Grounded AI Assistant Pipeline

    Design and implement the core logic of a retrieval-augmented AI assistant: chunking, embeddings, retrieval, prompt assembly, and output validation.

  • Practice Log Cleanup

    Use lists and dictionaries to clean up a messy practice log.

  • Score Tracker

    Turn variables and types into a working score tracker used by a small games night app.

  • Algorithms & Data Structures Capstone

    Bring together searching, stacks, hash maps, recursion, and graph traversal in five focused mini-implementations.

  • Number Guessing Engine

    Build the logic engine behind a guessing game using conditions and loops.

  • Build a Class Grade Report

    Model a Python program that reads student score records, validates them, computes averages, and produces a simple pass/fail summary report.

  • Study Coach

    Final project: a study coach that summarises practice sessions and reports back in plain English.