Data Science Fundamentals: Intro to Python (Seattle 9.10-9.14) – Paid

Interested in learning more data science? One of the fundamental skills you need to start your journey is programming in Python. This class is intended to further develop your skills as a programmer and prepare you to explore data science.

In this one-week course, you’ll learn how to program in Python, and we will cover the foundational skills you need to learn to solve Data Science problems in Python.

This workshop is for people who are analysts, product managers, statisticians, business managers, and anyone else with past exposure to programming, though not necessarily in Python. It is taught by Galvanize’s data science instructors and supported by the broader community.

What You’ll Learn / Takeaway:
Whether you’ve programmed in other languages or explored the basics of Python, this class will teach you foundational Python skills. Here’s what you’ll learn:

Environment Setup: Anaconda, Using the Command Line
Fundamentals of Python Programming: Data Structures and Control Flow
Higher Level Programming: Classes and Objects
Useful tools and Libraries: Collections, Itertools, Numpy

Who Should Take this Class?
For those of you interested in learning to program in Python, so you may be better prepared for self-study in data science, this course will help you get up to speed.

Those of you who are interested in gaining the skills required for admittance to the Seattle Data Science Immersive. This course is designed to help you meet that bar.

Prerequisites:
We do not recommend joining the first day of class with no exposure to Python, it is important to have at least a moderate amount of exposure before joining this intense one week class. We would like you to have some comfort with the following concepts:

– Starting python from a command line.
– Arithmetic in python.
– if statements.
– for loops.
– Basic data types like integers, floats, strings, and booleans.

If you have exposure to these concepts in Python, and/or a solid background in programming in another language, you have the necessary skills to serve as a foundation for this class. If you would like any guidance as to recommended resources for covering these topics, please email [email protected], the Seattle campus Admissions Advisor.

Setup (please have this in advance)

• Bring your non-windows laptop and power cable (dual-booting in Ubuntu or another Linux based system is OK).
• Install Anaconda with Python version 3.6 on your machine: http://docs.continuum.io/anaconda/install.html
• Install a text editor: http://www.atom.io
• If you have trouble with installation, please schedule some time with an instructor to help before the first day of class (do this via Slack once you are registered, or by emailing [email protected] for a connection).

Course Philosophy:
The Galvanize data science instructors believe that, since code is the major way data scientists develop and communicate thier ideas, data scientists should aspire to be good programmers. This course is designed with this goal in mind.

– We will pay close attention to clear and clean code and good program design throughout.
– We will write functions and classes to modularize our ideas and strive to keep our programs self-explanatory and readable.
– We will treat testing as a primary and fundamental skill. From day one we will write automated tests for our code, and use tests as a primary motivator for code cleanliness and good design.

Class Schedule
Monday – Friday, 8:30 am – 5:00 pm

Day 1: September 10

Day 2: September 11

Day 3: September 12

Day 4: September 13

Day 5: September 14

Register and pay here: http://www.eventbrite.com/e/data-science-fundamentals-intro-to-python-seattle-910-914-tickets-47089162954

Tuition Credit:

100% of workshop payment can be used as a tuition credit for our Data Science Immersive. This part-time course is intended to help prepare candidates who already have the necessary statistics background for our admissions process. Tuition credit can be applied to any Data Science Immersive cohort that an applicant is accepted to with a start date within 1 year of the completion of the Python part-time course.

For questions about this part-time course and our Data Science Immersive program, please email our Admissions Advisor, Lauren Lark at [email protected].