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Data science tutorials you can follow from start to finish.

Python, machine learning and analytics, explained step by step with code we have run ourselves.

Popular: pandas, SQL, XGBoost, TensorFlow, Power BI

Learning paths

Pick a topic and work through it in order.

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Beginner

Python for data analysis

Load, clean and visualize data with pandas, Matplotlib and Plotly.

  1. Install Python and Jupyter
  2. Data manipulation with pandas
  3. Clean and preprocess data
  4. Exploratory data analysis
  5. Interactive charts with Plotly

Beginner to intermediate

Machine learning

From linear regression to the boosting models used on tabular data.

  1. Linear regression
  2. Logistic regression
  3. Decision trees
  4. Random forests
  5. XGBoost vs LightGBM vs CatBoost

Intermediate

Deep learning

Build and train neural networks for images, sequences and text.

  1. Neural networks in Python
  2. Neural networks with TensorFlow
  3. Convolutional neural networks
  4. Recurrent neural networks
  5. NLP with Python

All levels

Tools and workflow

The tools data scientists use to analyze, share and ship work.

  1. Excel for data analysis
  2. SQL for data analysis
  3. GitHub for data science
  4. Power BI dashboards
  5. Docker for data science

Recent tutorials

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Data science by industry

How companies in different fields put data to work.

RetailLogistics and supply chainManufacturingHealthcareInsuranceEducationReal estate

About Pulse Data Hub

We write practical tutorials on Python, machine learning and analytics. Every tutorial is built around code we run before publishing, so you can follow along and get the same results.

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