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Learn Data Science

A practical learning path to become a data scientist, covering statistics, data analysis, visualization, and machine learning with real-world projects.

7 matières à étudier

01Débutant

Statistics & Probability

Learn descriptive and inferential statistics, probability distributions, hypothesis testing, and Bayesian thinking.

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02Débutant

Python & Data Wrangling

Master Python with Pandas for data cleaning, transformation, merging, and handling missing data.

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03Débutant

Data Visualization

Create compelling visualizations with Matplotlib, Seaborn, and Plotly. Learn storytelling with data.

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04Intermédiaire

SQL for Data Analysis

Write complex SQL queries, window functions, CTEs, and optimize queries for large datasets.

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05Intermédiaire

Machine Learning Fundamentals

Apply supervised and unsupervised learning algorithms using scikit-learn for classification, regression, and clustering.

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06Avancé

Feature Engineering & Model Selection

Learn feature creation, selection, cross-validation, hyperparameter tuning, and model evaluation metrics.

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07Avancé

Data Science Projects & Communication

Build end-to-end projects, create dashboards, write reports, and present findings to stakeholders.

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Prêt à commencer ?

Créez des cours personnalisés avec l'IA, des leçons interactives et un suivi de progression.

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