Join us for one of our expert-led virtual workshops in August!
- AI and Marketing Attribution Analysis
- Data Visualization & Storytelling
- Introduction to Data Science in R
- Preprocessing Data for Machine Learning in Python
Workshop 1: 4-Hour AI and Marketing Attribution Analysis
Overview: Marketers want to know what’s working and where leads are coming from. There is only so much budget to go around, so prioritizing your digital channels is essential. In this session, Katie will review the different kinds of attribution analysis you can get out of the box and why you’re better off building your own.
- The different types of models available out of the box
- What goes into building your own model
- How to structure your project for success
As CEO of Trust Insights, Katie oversees the growth of the company, manages operations and product commercialization, and sets overall strategy. Her expertise includes strategic planning, marketing operations management, organizational behavior, and market research.
Date: August 6th & 7th, 2020
Time: 10:00 AM - 12:00 PM EDT
Workshop 2: 4-Hour Intro Data Science in R Workshop
Overview: Are you sick and tired of manually manipulating data in excel? Are you interested in learning one of the most popular FREE (i.e., open source) data science programming languages out there? WIA's Introduction to R workshop will provide a complete crash course on the full data science workflow from cleaning and wrangling to visualization, modeling, and repeatable reporting. Two RStudio Certified Tidyverse Instructors will cover the essentials of popular R packages including ggplot2, tidyr, dplyr, tidymodels, and rmarkdown, . Code will be made available to attendees via RStudio Cloud prior to and following this hands-on-keyboard session, allowing beginner level users to dive right in and revisit materials after training. No programming experience is required for the workshop, however interested attendees are encouraged to explore the online book "R for Data Science" which can be found at https://r4ds.had.co.nz/
Ezgi Karaesmen is a PhD candidate at the Ohio State University College of Pharmacy. She is a genomic data scientist with cancer biology background. Currently, she works with large genomic and clinical datasets in the context of bone marrow transplants. Broadly, she is interested in associations of germline genetic variants with survival events of leukemia patients following their transplant.
Katie Sasso-Schafer, Ph.D. is a Data Scientist at the Columbus Collaboratory. Katie received her Ph.D. from The Ohio State University with a focus on Experimental and Quantitative (minor) Psychology. During her Ph.D. program she worked as a graduate research associate at the Nationwide Insurance Center for Advanced Customer Insights, using experimental methods and statistical analyses to optimize customer outreach and develop novel risk assessment strategies. At the Columbus Collaboratory, Katie works on a variety of data science projects across several industries. She also enjoys leading Use Case Discovery Workshops and managing project progress across the team. Outside of work, Katie is an avid R user and co-organizer of R-Ladies Columbus meet up.
Date: August 10th & 11th, 2020
Time: 8:00 AM - 10:00 AM
Workshop 3: 6-Hour Data Visualization and Storytelling Masterclass
PHASE I: CONCEPTUALIZE
When you are able to connect with your audience in a way they understand, they will be much more receptive to your message. Doing so requires thoughtful research into the deep desires of your audience. We'll discuss audience needs assessment techniques and a robust presentation planning framework that works.
- What your stakeholders are thinking but aren't telling you
- Audience needs assessment + interview strategies
- Transforming statements to insights
- Creating recommendations that get acted upon
- A proven influential presentation planning framework
- Content brainstorming techniques
- Digitizing and refining your content plan
PHASE II: VISUALIZE SLIDES + DATA SECTION I: SLIDE DESIGN
The most important, innovative, or valuable ideas can be lost if they're communicated poorly. By learning to think like a graphic and data designer, you'll be able to present your information in a clear and compelling way. We'll review neuroscience-backed design principles, how to work with imagery, and how to avoid the most common visual pitfalls.
You'll learn time-saving tricks on how to customize a PowerPoint template with client branding for reuse, quick formatting tricks for basic charts, and my best keyboard shortcuts to get things out the door fast.
SECTION II: THE PICA PROTOCOL PRESCRIPTION
Students are introduced to Lea's proprietary PICA Protocol™, my prescription for healthy, actionable data stories. It includes the anatomy of a healthy data viz, a full framework for visualizing analytical narrative, as well as alternatives for avoiding the most common data visualization mistakes.
- Alternative strategies to death by bullet points
- White space, typeface, color, imagery, and other design fundamentals
- Time-saving Powerpoint productivity tricks
- Common data visualization violations
- Creative animation techniques
- Lea's proprietary Chart Detox Checklist
Date: August 13th & 14th, 2020
Time: 1:00 PM - 4:00 PM
Workshop 4: 4-Hour Preprocessing Data for Machine Learning in Python
Overview: Getting your data ready for modeling is the essential first step in the machine learning process. In this workshop, you'll learn the basics of how and when to perform data processing. You'll learn: how to perform basic techniques such as dealing with missing data and incorrect data types, how to standardize your data so that it's in the right form for modeling, the benefits of creating new features to leverage the information in your dataset, and the process for selecting the best features to improve your model fit.
Sarah is a Senior Data Scientist at InVision where she studies user collaboration through data. She is an accomplished conference speaker and O'Reilly Media author, and enjoys making data science as accessible as possible to a broad audience. Sarah attended graduate school at the University of Michigan's School of Information.
Date: August 17th & 18th, 2020
Time: 9:00 AM - 11:00 AM