Thank you for sticking with it! We're excited for you to start.
You’ve passed your Prep Post Assessment - great work! Remember, you also need to complete your paperwork and get financially cleared in order to begin the program. Please contact [email protected] if you're uncertain about start dates or anything else related to getting started.
In the meantime, we highly recommend that you work through the following content on Environment Set-Up as that will get you ready to hit the ground running on Day 1.
- Getting Started with Data Science - Introduction
- Problems Data Science can Solve
- The Data Science Process
- Data Privacy and Ethics
- Setting up a Professional Data Science Environment - Introduction
- Setting up a Professional Data Science Environment - MacOS Installation
- Setting up a Professional Data Science Environment - Windows Installation
- Setting up a Professional Data Science Environment - Configuring Git and Anaconda
- Running Jupyter Notebooks Locally
- PEP8
- Getting Started with Data Science - Recap
- Bash and Git - Introduction
- The Bash Shell
- Short Video: Bash
- Git Version Control 101
- Setting up a SSH Token for a GitHub Account
- Getting Started with Git
- Git Practice
- .gitignore
- Collaborating with Git Branches
- Git Resources
- Bash and Git - Recap
Once you have finished the topics above, below are supplemental resources that you can explore if you have additional time or could use some more practice before your first day.
You are not required to utilize any of these resources, and in general if you have limited time we recommend reviewing the course you’ve just completed and material above rather than additional readings or practice.
- Python Essentials and Python Loops and Functions: The free Python course on Kaggle covers a lot of the same material we covered in the Python part of the prep, if you want additional practice
- Data Visualization: The Matplotlib website has a useful tutorials page, and Kaggle offers a free data visualization course that gets into more depth than what we cover
- Pandas: Pandas is a library for data manipulation that we used in some brief examples in the prep but didn't introduce in depth. We'll be using it a lot in the program, so you might want to look at the user guide on the pandas website or Kaggle's free pandas course
- Overview: This blog post has a good introduction to the statistics concepts you'll need to know as a data scientist
- Probability: Brilliant offers free intro to probability lessons
- Statistics: If you're interested in working through a complete free statistics course, Khan Academy offers one that we recommend
The topics below were not introduced in the Prep and will be covered in the main course, but some students prefer to study in advance if they have not been exposed to these topics previously.
- Overview: This blog post has a good introduction to the linear algebra concepts you'll need to know as a data scientist
- The Essence of Linear Algebra: This YouTube playlist from 3Blue1Brown has great visual explanations of the geometric concepts behind linear algebra
- Introduction: Brilliant offers free multivariable calculus lessons
- The Essence of Calculus: Similar to the linear algebra playlist linked above, this YouTube playlist from 3Blue1Brown shows the geometric intuition behind calculus concepts
- Calculus: If you're interested in working through a complete free calculus course, Khan Academy offers one that we recommend
- Command Line Course: OpenClassrooms offers a free short course on the command line that is designed for beginners
- Command Line Game: If you would rather learn by playing a game, this terminal game from MIT is a good choice
- SQL Course: Both OpenClassrooms and Khan Academy offer intro to SQL courses
We hope you have enjoyed your first experience with the technical topics and curriculum tools we use at Flatiron School. We're excited to see you on your first day!