Name: Introduction to Time Series [Live-Online]
Start: 2021-07-28T17:30:00-07:00
End: 2021-07-28T19:30:00-07:00

Time series data is everywhere! Working with them is an important part of Data Science.

**You must RSVP on Eventbrite to receive Zoom link and updates on this event**.
https://www.eventbrite.com/e/introduction-to-time-series-live-online-tickets-158308074713

Did you know that avocados can teach you about time series and what they do? To understand how this is possible, just show up for the event!
It is likely that you often encounter graphs of time series analysis. Time series graphs are one of the most common ways data is visualized. There are two major aspects to time series we will cover here. Time series analysis and time series forecasting. If you think predicting the future is a pretty neat super-power, then you’ll want to learn about some modern software techniques that make this possible. This workshop is a perfect gateway for gaining new fundamental perspectives about times series data. Getting a glimpse at what is possible with modern techniques opens the door for you to better understand your world with data. If this sounds like an essential skill, that’s because it is.

Target Audience:

This live online workshop has been designed with the beginner in mind.

If you have learned some Python in our Intro To Python or Intro To Panda’s events, it will be even easier to follow the time series coding walkthrough. Knowing some Python will help, but is not required.

What You Will Learn:

What is a time series?
Where does time series data come from?
What are some practical applications derived from time series data?

Types of forecasting

Investigating an example time series dataset (this may involve avocados)
How to visualize a time series
Running a time series forecast

How to Prepare:

Install Google Chrome (any modern browser should work): https://www.google.com/chrome/browser/desktop/

Sign up for a Google account if you don't already have one (We will be using an online code editor by Google)

Have the Zoom Client for Video Meetings installed well before the webinar begins: https://zoom.us/download

Link to join the workshop will be provided to you once you RSVP.

Instructor:

Connor Slagle

I am a data scientist with a fondness for biotechnology, with degrees in both chemical and environmental engineering. Recent advances in data science are revolutionizing all aspects of contemporary business, from product refinement to customer identification; In no field is this as evident (or as exciting) as in biotechnology.
I’m focused on leveraging these skills to improve targeted, non-invasive drug delivery in oncology. Additionally, I love spreading my understanding of machine learning concepts through evangelism at Galvanize.

To learn more about our Data Science immersive program, visit https://www.galvanize.com/data-science-bootcamp

Connect Before and After The Event

Want to connect with others in tech before the event? Join us in the Galvanize Tech Community Slack to discuss topics in the industry, meet other coders ranging from rookies to veterans of their industry, cheer each other on while learning how to code, and more.

About Galvanize:
Galvanize is the premiere dynamic learning community for technology. With campuses located in booming technology sectors throughout the country, Galvanize provides a community for each of the following:

Education - part-time and full-time training in web development, data science, and data engineering

Workspace - whether you’re a freelancer, startup, or established business, we provide beautiful spaces with a community dedicated to supporting your company’s growth

Networking - events in the tech industry happen constantly on our campuses, ranging from popular Meetups to multi-day international conferences

To learn more about Galvanize, visit https://www.galvanize.com/
Data Science Bootcamp: https://www.galvanize.com/data-science-bootcamp
Software Engineering Bootcamp: https://www.galvanize.com/web-development
Contact Admissions: https://admissions.galvanize.com/

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