Anaconda Ecosystem Training in Copenhagen, Denmark

This course is designed to provide participants with a complete understanding of Anaconda — from installation and basic usage to advanced environment and package management. The training focuses on using Anaconda for data science workflows, managing multiple Python environments, and using JupyterLab, Conda, and key tools included in the Anaconda Distribution.

Introduction to Anaconda and Core Usage

Introduction to Anaconda

• What is Anaconda and why use it?
• Key components: Conda, Jupyter, Spyder, Navigator
• Downloading and installing Anaconda
• Navigating the Anaconda Navigator GUI

Using Conda for Package Management

• Understanding Conda vs pip
• Installing and removing packages
• Updating packages and Anaconda itself
• Viewing package information and dependencies

Creating and Managing Environments

• What are Conda environments?
• Creating, activating, and deactivating environments
• Cloning and deleting environments
• Exporting and sharing environment files (.yml)

Introduction to Jupyter Notebook

• Launching Jupyter from Anaconda Navigator or CLI
• Creating and running notebooks
• Markdown, code cells, and notebook shortcuts
• Saving, downloading, and sharing notebooks

Advanced Features and Best Practices

JupyterLab and Project Management

• What is JupyterLab and how is it different?
• Navigating the JupyterLab interface
• Managing files, terminals, and extensions
• Working with notebooks, CSVs, and Python scripts

Advanced Conda Features

• Using channels (default, conda-forge)
• Handling package version conflicts
• Managing multiple Python versions
• Mixing pip and Conda safely

Virtual Environment Best Practices

• Isolating projects and avoiding conflicts
• Using .yml files for reproducibility
• Automating environment setup for teams or students
• Environment troubleshooting tips

Integrating IDEs and Tools

• Using Anaconda with VS Code, PyCharm
• Setting up Python interpreter from Conda environments
• Using Anaconda for machine learning and data science workflows

Final Assessment and Wrap-up:

• Quiz covering Conda commands and environment structure
• Recap, tips, and Q&A session