- $49
Conda Essentials for Data Scientists
Why learn conda?
If you're a Python user, managing the installation of packages and their environments is a key skill.
This is even more important for Data Scientists, who rely on an ecosystem of cutting-edge libraries that can be hard to install and maintain. Without a system for managing it all, you'll end up with fragile or broken environments that make it impossible to get your work done!
Conda is an easy-to-use tool for managing packages, virtual environments, and Python versions that is trusted by millions of Data Scientists.
⚠️ Avoid this with conda ⚠️
Who should take this course?
This is the perfect course for you if:
You've never used a tool to manage your packages or environments
You've used other tools to manage your packages or environments, but you're new to conda
You've used conda, but you haven't yet unlocked its full capabilities
What will you learn?
The difference between conda, Anaconda, and Miniconda
How to install and access conda
How to install, update, and remove packages
How to create, manage, and remove conda environments
Best practices for virtual environments
How to access conda channels
How to configure your channel list
How to use pip with conda
How to speed up package installation
Advanced conda features
And much more!
If these terms are new to you, that's okay! I'll explain everything in the course.
What's included in the course?
33 bite-sized video lessons
Certificate of completion at the end of the course
Lifetime access to everything
Free access to future course updates
Why not use pip instead of conda?
pip is only a package manager, whereas conda manages packages, environments, and Python versions. To match the functionality of conda, you'd need to combine pip with a bunch of other tools (pyenv, virtualenv, virtualenvwrapper, etc.)
conda also has other advantages over pip:
conda always installs pre-compiled binary files, which makes package installation predictably easy.
conda can track non-Python dependencies, which is especially useful for data science packages.
Since not every Python package is available through conda, I also explain how to use pip with conda in the course.
FAQs
What do I need to know before the course?
Nothing! It's okay if you're brand new to managing packages and virtual environments.
Does this course use the command line?
Yes, we will be running conda from the command line using a terminal application. However, you don't need to have any previous command line experience!
If you strongly prefer a visual interface, you can use Anaconda Navigator to manage packages and environments without typing conda commands. Although I don't use Navigator in the course, the conceptual parts of the course will still be relevant to you.
Which terminal application should I use?
Mac and Linux users: My preferred terminal application is Warp, which is free for individuals. (If you use my invite link when signing up, you'll get an exclusive theme.) However, you are welcome to use the default Terminal application instead.
Windows users: You should use Anaconda Prompt, which is included with both Anaconda and Miniconda.
Is this course only for Python users?
Conda is most widely used in the Python ecosystem, but it can also be used with other programming languages such as R, Java, and C/C++.
This course focuses on using conda with Python packages, though if you're using another programming language, most of the course material will still be relevant.
How long is the course?
The video lessons total about 2 hours.
What if I need help during the course?
How do I earn a certificate of completion?
Once you have watched all of the lessons, you can request a certificate of completion.
How long will I have access to the course?
You will have lifetime access to the course.
Do you offer any discounts?
Yes! I offer Purchasing Power Parity discounts (also known as location-based discounts) for all of my paid courses. If you're located in one of the 160+ qualifying countries, you should automatically see a discount code at the top of this page.
I also offer student discounts and hardship-based discounts, regardless of where you live. Please email me at kevin@dataschool.io and I'd be happy to send you the appropriate discount code.
What's your refund policy?
I have another question...
Course Outline
Chapter 2: Getting started with conda
9 minutes
Chapter 3: Managing packages with conda
25 minutes
Chapter 4: Managing environments with conda
20 minutes
Intermission
Chapter 5: Using conda channels
20 minutes
Chapter 6: Using conda and pip together
7 minutes
Chapter 7: Advanced conda features
42 minutes
Conclusion
👋 Welcome to Data School!
My name is Kevin, and I've taught Data Science in Python to over a million students.
My courses explain data science topics in a clear, thorough, and step-by-step manner.
I'd love to teach you, regardless of your educational background or professional experience.
Thanks for joining me! 🙌