Workshop | Introduction to Data Analysis for Aspiring Data Scientists: Part 2

Join us for a three part learning series: Introduction to Data Analysis for Aspiring Data Scientists. This is the second of three (maybe four, depending on what you all think!) online workshops for anyone and everyone interested in learning about data analysis. No previous programming experience required.

Part 2: Data Analysis with pandas

Abstract: This workshop is on pandas, a powerful open-source Python package for data analysis and manipulation. In this workshop, you will learn how to read data, compute summary statistics, check data distributions, conduct basic data cleaning and transformation, and plot simple visualizations. We will be using data released by the Johns Hopkins Center for Systems Science and Engineering (CSSE) Novel Coronavirus (COVID-19) (https://github.com/CSSEGISandData/COVID-19). Prior basic Python experience is recommended.

Who should attend this workshop: Anyone and everyone, CS students and even non-technical folks are welcome to join. Please note, prior basic Python experience is recommended.

What you need: Although no prep work is required, we do recommend basic python knowledge and signing up for community edition before this workshop. Watch Part 1 to learn about Python: https://www.meetup.com/data-ai-online/events/269814565/ Sign up for Community Edition here: https://databricks.com/try-databricks

LINK TO JOIN: https://databricks.zoom.us/j/286715147

Agenda: 10AM PDT - 11AM PDT (GMT-8)

10:00AM - 10:50AM - Workshop led by Conor Murphy
10:50AM - 11:00AM - Q&A

• Watch Part 1: https://www.youtube.com/watch?v=HBVQAlv8MRQ
• RSVP for Part 3 April 22nd: https://www.meetup.com/data-ai-online/events/269838467/
• Sign up for Community Edition: https://databricks.com/try-databricks
• Link to access notebooks: https://github.com/databricks/tech-talks

Instructor: Conor Murphy is a Data Science Consultant at Databricks. He transitioned to the tech sector after spending four years leveraging data for more impactful humanitarian interventions in developing countries with a focus on business development. He managed a multi-million dollar portfolio of grants for The Rotary Foundation focusing on developing and analyzing impact measurements in economic development initiatives, evaluating program participation and translating academic research into institution policies.

He has held a variety of positions including a faculty role for Galvanize's Data Science graduate program, principal data scientist and consultant for a number of startups and a data scientist and educator at Databricks. Outside of data, Conor is an avid skydiver who's always looking for geeky ways to quantify his time in freefall.

TA: Chengyin Eng is a Data Science Consultant at Databricks where she implements data science solutions and delivers machine learning trainings to cross-functional clients. She received her M.S. in Computer Science from University of Massachusetts, Amherst. Prior to that, she completed her B.A. in Environmental Studies and Statistics at Mount Holyoke College and spent her college years applying statistical modeling techniques to tree research. Thereafter, she worked in the life insurance industry and provided pro-bono data science service to NGOs. Outside of data science, Chengyin enjoys reading, photography, and leafing through outdoor markets for food and craft.

TA: Amir Issaei is a Senior Data Science Consultant at Databricks, where he educates customers on how to leverage the company’s Unified Analytics Platform in machine learning (ML) projects. He also helps customers implement ML solutions and use advanced analytics to solve business problems. Previously, he worked in the Operations Research Department at American Airlines, where he supported the Customer Planning, Airport, and Customer Analytics Groups. He holds an MS in mathematics from the University of Waterloo and a BE in physics from the University of British Columbia.