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VetsinTech Python Fundamentals for Data Science by DraftKings!

May 2 @ 5:00 PM - May 26 @ 7:00 PM PDT

May 2nd Start (4 wk Course; M, T, W, Th)5-7 PM Pacific

Calling all veterans interested in a career in data management or information management skills…

VetsinTech is excited to offer FULL SCHOLARSHIPS for Python Fundamentals for Data Analytics exclusively for past and present military service members, veterans, and spouses!

Registration Instructions:

  1. Verify your Eligibility status with ID.me at the following link: https://vetsintech.co/idme
  2. Attend virtual orientation (via zoom) you will receive an invite for. Orientation is a week before class starts.
  3. Submit Resume online at the following link: vetsintech.co/submit-resume/

Important Disclaimer Regarding Class Format:

Please be prepared to have cameras on during class, and to be interacting in the video chat/Slack. If you have a second monitor, we recommend using it so that you can be watching the instructor on one screen and completing activities on the other.

You will learn the basics of programming by building simple applications for managing data. More specifically you will get hands-on experience creating data models using the object-oriented programming techniques used most often in data science courses.

**If you have already taken VetsinTech Python Fundamentals before, you will not be able to take it again**

CURRICULUM OVERVIEW

  • Introduction to Python & Python libraries
  • Working with data types in Python
  • Writing simple functions to manipulate input values
  • Introduction to Functional Programming
  • Introduction to Object-Oriented Programming
  • Process data from Excel, PDF, CSV, JSON, and more
  • Basic web scraping
  • Regular expressions https://www.dataquest.io/blog/regex-cheatsheet/

Schedule for the class

5-7 PM Pacific | 6-8 PM Mountain | 7-9 PM Central | 8-10 PM Eastern

Virtual Orientation: Thursday, Apr 28th at 9 am PDT. You will receive a calendar invite as the class roster is finalized closer to the date.

Week 1: May 2, 3, 4, 5

Week 2: May 9. 10, 11, 12

Week 3: May 16, 17, 18, 19

Week 4: May 23, 24, 25, 26