Approachable Data Science: An Introduction

Details

This course is now a joint event between the ACM and Women in Data Science (https://www.meetup.com/Women-in-Data-Science-ATX/).

To complement our more advanced topics, we will be starting an introductory course to help those in our group who want to get started in building machine learning models. This will be a six part course covered in 1-1.5 hour workshops. Each session will take the form of part instructor led training and part hands-on exercises. We will cover how you start and organize a project, exploring the data, preparing the data, building the model, evaluating the model and publishing the model so others can use your work. We will plan to have a session every 2 weeks. At the end of this course if you attend at least 75% of the sessions then you will receive a certificate for the course from the ACM in the final session. I will announce the location once I get a sense of the size of the group. This course is at no cost to you and you do not need to be a member to attend.

Course Description:
Interested in Data Science but don't have a computer science or math background? We are taking the intimidation out of this subject. This workshop will help you understand the building blocks of a data science project, introduce steps to take before getting started, and will familiarize you with tools to create classifiers and predictors.
Approachable Data Science will give you simple approaches to going beyond tools like Microsoft Excel by walking you through a typical project involving data science. This will include strategies around structuring a project for success, using tools to simplify implementation, and how to clearly share results with your team.
For example, one of the models we will build addresses a problem that many businesses face- Churn. We will use billing data to train a model to see if we can predict customers that will terminate. This real world example provides space to explore the data involved and build a machine learning model with a data science toolkit. Then you will evaluate your results and learn how to share them with others.

Suggested Experience Level:
You do not need a programming background for this class. You should however be comfortable with basic data manipulation in spreadsheets and you should be familiar with basic descriptive statistics concepts. For example, you should know how to get the sum, mean, minimum and maximum from a set of numbers. We will be using machine learning workbench called KNIME which is free to download and will not require code to use.

What to bring:
You should bring your own laptop (either Windows/Mac) so you can use the software to run the exercises we provide. Show up prepared to build a real machine learning model!

Developed by Blacklight Solutions:
Blacklight Solutions works with businesses to unlock the power of the data they own, generate, or collect in their business. Blacklight Solutions enables businesses to create products with their owned data that expands customer engagement and increases revenue. In turn we help our clients put cutting edge experiences in front of their customers that generate insights and increase transparency.

The Instructor:
Chance Coble has been helping people get value from their data for over 20 years. He has been recruited to lead predictive analytics solutions at some of the most successful organizations in the world. He has been selected by the United States government and other governments around the world to implement cutting edge solutions in machine learning and artificial intelligence. Mr. Coble is currently President and CEO of Blacklight Solutions where he spends his days finding practical approaches for small and mid-sized organizations to execute on and benefit from their analytics and AI strategies. He holds a B.S. in Computer Science from the University of Texas at Austin and an MS in Biomedical Informatics from the University of Texas at Houston.