J Beightol Bio

J Beightol

Data Science Immersive Instructor, General Assembly

Austin

J Beightol is a Data Scientist specializing in Natural Language Processing. His first exposure to the field came while working at a financial consulting firm where he helped banks scrape twitter data to gauge customer sentiment. He completed the Data Science Immersive class in D.C. and worked independently with the French Embassy analyzing visa data and suggesting strategies to boost foreign student visa applications. Currently J is collaborating with Milkshake Tech in Brooklyn to build a website recommendation engine when he isn’t teaching students at General Assembly or playing board games. He received a BA in History with a minor in Economics from Davidson College.

In recognition of his exemplary service in the classroom, J has been selected as a member of General Assembly's Distinguished Faculty program.

J Beightol

Upcoming Courses

Previously (30)

Data

Data Science Immersive

Jumpstart an in-demand career as a data scientist, data analyst, or business intelligence analyst. Build fluency in essential skills through this 12-week, full-time program.

10 Times

Data

Intro to Data Science

This class will define what data science is, review some of the main tools used by data scientists today, and discuss how they can be implemented in real world work.

7 Times

Data

Free Introduction to Data Science

This workshop will define what data science is, review some of the main tools used by data scientists today, and discuss how they can be implemented in real world work.

5 Times

Data

Intro to Python

In this hands-on introductory workshop, we’ll learn about Python programming and how to write your first script.

3 Times

Data

Free Introduction to Python

In this hands-on introductory workshop, we’ll learn about Python programming and how to write your first script.

3 Times

Data

Introduction to Data Science

This class will define what data science is, review some of the main tools used by data scientists today, and discuss how they can be implemented in real world work.

2 Times

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