Data Careers with Python

A Pro study guide on Data Careers: 28 lessons in 5 parts, 6 hands-on Practical use cases. A Pro plan opens every lesson, practice question and Practical.

What you will learn

• Data engineering - Pipelines, SQL from Python, cleaning with pandas, file formats and storage, Airflow and PySpark. (6 lessons)
• Data analytics - Business questions and KPIs, pandas summaries, SQL for analysis, charts and dashboards. (5 lessons)
• Data science - The workflow, features and splits, scikit-learn models, metrics, overfitting and production. (6 lessons)
• Statistics in Python - Descriptive statistics, distributions, confidence intervals, hypothesis tests, regression and A/B testing. (6 lessons)
• Maths in Python - Vectors, matrices, gradient descent, probability and simulation, least squares and PCA. (5 lessons)

Hands-on Practical use cases

• Daily sales data pipeline
• Monthly revenue report
• Predicting subscriber churn
• A/B test of a checkout page
• Clickstream at scale with PySpark
• House prices with NumPy and statsmodels

All tutorials · Practice quizzes