Data and AI

Learn Machine Learning

3 plans — 19 lessons

Through practical lessons and AI guidance, you’ll build your skills step by step. By the end, you’ll be able to write real code, solve everyday problems, and build practical projects.

Beginner Path14-day sprint
14-day sprint

Go from complete beginner to confident in Machine Learning in 14 days

Through practical lessons and AI guidance, you’ll build your skills step by step. By the end, you’ll be able to write real code, solve everyday problems, and build practical projects.

  • Machine learning concepts and terminology
  • Data prep and feature engineering
  • Supervised models and training
  • +3 more topics
Start plan
Intermediate Path21-day sprint
21-day sprint

Go from the basics to real-world Machine Learning skills in 21 days

Through practical lessons and AI guidance, you’ll build your skills step by step. By the end, you’ll be able to solve real-world tasks, work more efficiently, and build stronger projects.

  • Feature engineering and selection
  • Model evaluation and cross-validation
  • Ensemble methods: bagging and boosting
  • +4 more topics
Start plan
Advanced Path30-day sprint
30-day sprint

Go from advanced to expert in Machine Learning in 30 days

Through practical lessons and AI guidance, you’ll build your skills step by step. By the end, you’ll be able to solve complex problems, optimize your work, and build advanced real-world solutions.

  • Deep learning foundations with PyTorch
  • CNNs and transfer learning
  • NLP and transformer models
  • +3 more topics
Start plan

What You'll Learn

01Foundation

Machine learning concepts and terminology

Understand models, features, labels, and datasets.

conceptsmodelsbasics
02Foundation

Data prep and feature engineering

Prepare data and create useful features.

featurespreprocessingdata
03Core

Supervised models and training

Train models like regression and classification.

trainingsupervisedmodels
04Core

Evaluation and validation

Measure accuracy and avoid data leakage.

evaluationvalidationmetrics
05Core

Overfitting and model tuning

Tune hyperparameters and reduce overfitting.

tuningoverfittingoptimization
06Challenge

Mini project: predictive model

Build a simple predictive model end-to-end.

projectpredictionpractice

Build models that actually work

14 days of supervised learning, feature engineering, and model evaluation — end with a real predictive model.

Start learning

Kavka's ML plan skips the hype and focuses on the fundamentals. I finally understand how to evaluate a model.

— Alex N., ML engineer

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