Get Started with Anaconda

Course 11 of 15 in Skill Path: Data Science On-Ramp

Take your first steps using Anaconda Distribution, working with conda, and writing your first Python program.

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About this course

In this entry-level course, we’ll show you when and how to use Anaconda tools. You’ll learn about packages, conda environments, Jupyter Notebooks, integrated development environments (IDEs), and more. We’ll walk you through a Python program (in a notebook and in an IDE) and see what happens when a bug in Python code is identified. Check out the Introduction to Python Programming Learning Path to learn more about using Python.

By the end of this course, you’ll understand:

  • How different parts of the technology stack work together
  • Basic data science concepts and tools
  • How to install Anaconda
  • At least 5 common Python packages and their uses
  • Useful libraries for data science and machine learning
  • How to open and work with a Jupyter notebook or IDE

Questions? Issues? Join our Community page to get help.

 

Curriculum00:47:17

  • Introduction
  • Getting started with Anaconda Distribution
  • What is Python? 00:01:07
  • What are Modules, Packages, and Libraries? 00:02:01
  • Anaconda Distribution versus Miniconda 00:01:33
  • Installation
  • Installing Anaconda (Windows) 00:02:19
  • Installing Anaconda (Mac) 00:02:33
  • Installing Miniconda (Windows) 00:01:32
  • Conda Overview
  • Understanding conda 00:02:24
  • Preview
    Conda Workflow: Creating Environments, Installing Packages, and Launching an IDE 00:04:17
  • Anaconda Navigator Overview 00:04:00
  • Integrated Development Environment (IDE) and Jupyter Notebook
  • What is an IDE? 00:02:04
  • What is Jupyter Notebook and JupyterLab? 00:08:24
  • Hands-on Practice
  • Create a simple Python program in Jupyter 00:02:25
  • Create a simple Python program in Spyder 00:02:15
  • Create a simple Python program in PyCharm 00:02:57
  • Create a simple Python program in VS Code 00:01:40
  • Create a simple Python program in a text editor 00:01:59
  • Accessing Old Revisions 00:01:15
  • Sharing An Environment 00:02:32
  • Notebook Debugging Tools
  • Conda Cheat Sheet
  • End of Course Survey
  • Course Completion

About this course

In this entry-level course, we’ll show you when and how to use Anaconda tools. You’ll learn about packages, conda environments, Jupyter Notebooks, integrated development environments (IDEs), and more. We’ll walk you through a Python program (in a notebook and in an IDE) and see what happens when a bug in Python code is identified. Check out the Introduction to Python Programming Learning Path to learn more about using Python.

By the end of this course, you’ll understand:

  • How different parts of the technology stack work together
  • Basic data science concepts and tools
  • How to install Anaconda
  • At least 5 common Python packages and their uses
  • Useful libraries for data science and machine learning
  • How to open and work with a Jupyter notebook or IDE

Questions? Issues? Join our Community page to get help.

 

Curriculum00:47:17

  • Introduction
  • Getting started with Anaconda Distribution
  • What is Python? 00:01:07
  • What are Modules, Packages, and Libraries? 00:02:01
  • Anaconda Distribution versus Miniconda 00:01:33
  • Installation
  • Installing Anaconda (Windows) 00:02:19
  • Installing Anaconda (Mac) 00:02:33
  • Installing Miniconda (Windows) 00:01:32
  • Conda Overview
  • Understanding conda 00:02:24
  • Preview
    Conda Workflow: Creating Environments, Installing Packages, and Launching an IDE 00:04:17
  • Anaconda Navigator Overview 00:04:00
  • Integrated Development Environment (IDE) and Jupyter Notebook
  • What is an IDE? 00:02:04
  • What is Jupyter Notebook and JupyterLab? 00:08:24
  • Hands-on Practice
  • Create a simple Python program in Jupyter 00:02:25
  • Create a simple Python program in Spyder 00:02:15
  • Create a simple Python program in PyCharm 00:02:57
  • Create a simple Python program in VS Code 00:01:40
  • Create a simple Python program in a text editor 00:01:59
  • Accessing Old Revisions 00:01:15
  • Sharing An Environment 00:02:32
  • Notebook Debugging Tools
  • Conda Cheat Sheet
  • End of Course Survey
  • Course Completion