Skills your team will gain
Selected machine learning and deep learning concepts and algorithms.
The ability to create machine learning and deep learning algorithms in Python using its libraries.
The ability to create pipelines for solving real‑life problems.
Tools and metrics for evaluating machine learning models.
Guidance on how to manage data science projects and how they differ from software development ones.
Machine learning basics
- Data science ideas
- The programming environment: Python or R and its data science libraries, Jupyter Notebook
- Data exploration and preprocessing
Machine learning techniques
- Feature engineering
- Linear regression, logistic regression
- Reducing dimensionality
Random forests, managing the data science process
- Random forest, XGBoost, !!LightGBM
- Organizing teamwork
- Managing and tracking experiments