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Course Description

Software is constantly evolving, so data scientists need a way to update the software they are using without breaking things that already work. Conda is an open source, cross-platform tool for managing packages and working environments for many different programming languages. This course explains how to use its core features to manage your software so that you and your colleagues can reproduce your working environments reliably with minimum effort.

  1. 1

    Installing Packages

    Free

    This chapter shows you how to install, update and remove packages using conda.

  2. Utilizing Channels

    In this chapter you will learn how to search and install packages from various channels with Conda.

  3. Working with Environments

    This chapter shows you how work with Conda environments.

  4. Case Study on Using Environments

    This chapter shows you how to easily manage projects using environments.

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David Mertz
David Mertz

Senior Data Science Trainer at Anaconda Inc.

David served as Director and committee chairs for the PSF. He wrote the widely read column, Python books, and gave keynotes at PyCon-India, PyCon-UK, PyCon-ZA, PyCon Belarus, PyCon Cuba, and PyData SF. Before Anaconda, David worked for D. E. Shaw Research to build the world's fastest supercomputer for performing molecular dynamics. He is pleased Python has become the default high-level language for most scientific computing projects.

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Collaborators
  • Albert DeFusco

    Albert DeFusco

  • Dhavide Aruliah

    Dhavide Aruliah

  • Sumedh Panchadhar

    Sumedh Panchadhar

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