Technology

How to Become a AI / ML Engineer

Learn the programming, mathematics, machine learning, and AI engineering skills needed to build intelligent systems.

Advanced5 core skills3 learning phases

What does a AI / ML Engineer do?

AI and machine learning engineers develop, deploy, and maintain systems that use machine learning and modern AI techniques.

Use Python for programming, automation, data analysis, and AI.

essential

Why it matters: Python is one of the primary programming languages used throughout modern AI and machine learning.

Use statistical concepts to understand data and evaluate conclusions.

essential

Why it matters: Statistics provides the foundation for understanding data, uncertainty, and model evaluation.

Build and evaluate models that learn patterns from data.

essential

Why it matters: Machine learning fundamentals are necessary for understanding how predictive models are trained and evaluated.

Use neural networks to solve complex machine learning problems.

important

Why it matters: Deep learning powers many modern computer vision, language, and generative AI systems.

Deploy, monitor, maintain, and operate machine learning systems.

important

Why it matters: Production AI systems require reliable methods for deploying, monitoring, and maintaining models.

~70 hours

Build the programming and mathematical foundation required for machine learning.

Skills

PythonStatistics

Milestone: Use Python to analyze datasets and implement basic mathematical concepts.

~90 hours

Learn supervised learning, unsupervised learning, model evaluation, and feature engineering.

Skills

Machine Learning

Milestone: Train, evaluate, and explain a machine learning model.

~100 hours

Move from models to production AI systems using deep learning and deployment practices.

Skills

Deep LearningMLOps

Milestone: Build and deploy an AI-powered application.

See which skills you already have, what you should learn next, and how much time it could take based on your situation.