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Course Outline

Introduction

  • Overview of Dask features and advantages
  • Parallel computing in Python

Getting Started

  • Installing Dask
  • Dask libraries, components, and APIs
  • Best practices and tips

Scaling NumPy, SciPy, and Pandas

  • Dask arrays examples and use cases
  • Chunks and blocked algorithms
  • Overlapping computations
  • SciPy stats and LinearOperator
  • Numpy slicing and assignment
  • DataFrames and Pandas

Dask Internals and Graphical UI

  • Supported interfaces
  • Scheduler and diagnostics
  • Analyzing performance
  • Graph computation

Optimizing and Deploying Dask

  • Setting up adaptive deployments
  • Connecting to remote data
  • Debugging parallel programs
  • Deploying Dask clusters
  • Working with GPUs
  • Deploying Dask on cloud environments

Troubleshooting

Summary and Next Steps

Requirements

  • Experience with data analysis
  • Python programming experience

Audience

  • Data scientists
  • Software engineers
 14 Hours

Need help picking the right course?

Testimonials (2)

Examples/exercices perfectly adapted to our domain

Luc - CS Group
Course - Scaling Data Analysis with Python and Dask

The fact of having more practical exercises using more similar data to what we use in our projects (satellite images in raster format)

Matthieu - CS Group
Course - Scaling Data Analysis with Python and Dask

Upcoming Courses

Scaling Data Analysis with Python and Dask

2025-11-24 09:30
14 hours
Regus Marina Casablanca

Scaling Data Analysis with Python and Dask

2025-12-08 09:30
14 hours
The Spot

Scaling Data Analysis with Python and Dask

2025-12-22 09:30
14 hours
7AY Rabat

Scaling Data Analysis with Python and Dask

2026-01-05 09:30
14 hours
Regus - Mahaj Hay Ryad

Scaling Data Analysis with Python and Dask

2026-01-19 09:30
14 hours
Regus Marina Casablanca

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