ADVANCEDCodingPythonFundamentalMachine Learning

Foundational Machine Learning

Understand data at its core and master the reasoning behind how and why machine learning works

Start Learning
50+Video Hours
6+Projects
~50Topics
31Lessons

Curriculum

Tools & Technologies

PythonPython
Scikit-learnScikit-learn
Scikit-optimizeScikit-optimize
SciPySciPy
StatsmodelsStatsmodels
MatplotlibMatplotlib
NumPyNumPy
PandasPandas
OptunaOptuna
SHAPSHAP
SeabornSeaborn
LightGBMLightGBM
XGBoostXGBoost

What You'll Learn

✓Understand and apply core machine learning algorithms
✓Clean, explore, and prepare data for modeling
✓Evaluate models using proper metrics and validation
✓Build end-to-end ML pipelines with scikit-learn
✓Explain model predictions with interpretability tools
✓Handle class imbalance, feature engineering, and hyperparameter tuning

Frequently Asked Questions

What prerequisites do I need?

Basic Python programming knowledge and some familiarity with mathematics (linear algebra, statistics) is helpful but not required.

Is this course suitable for beginners?

This course is designed for those with some programming experience who want a deep understanding of machine learning. Complete beginners may want to start with the Machine Learning Applied course first.

Ready to start learning?

50+ video hours, 6+ projects covering ~50 ML topics. From data cleaning to model explainability.

Start Learning