Our 2020 conference may be canceled, but our dedication to the community and educating its members remain as strong as ever. WIA is already planning our August 2021 in-person conference, and we are looking forward to seeing you there.
Although our face-to-face interactions have been restricted, WIA is committed to providing visibility to women making an impact in the analytics space. We are enhancing our online platform in ways that further advance education in analytical research, development, and application.
Upcoming initiatives include our August virtual workshops and, in partnership with Tableau, a free virtual series entitled “Mitigating Bias in Analytics.”
August 2020 Virtual Workshops
In keeping with our mission of supporting education in analytics while safely maintaining social distancing guidelines, we’re excited to announce our August workshops online.
These digital workshops offer cutting-edge content you won’t find anywhere else, brought to you by leaders in the analytics space.
August workshops include:
AI and Marketing Attribution Analysis
Katie Robbert, CEO, Trust Insights
Date: August 6th & 7th, 2020
Time: 10:00 AM – 12:00 PM EDT
In this 4-Hour workshop, Katie Robber, CEO of Trust Insights, will review the different kinds of attribution analysis you can get out of the box and why you’re better off building your own.
In this workshop, you’ll learn the different types of models available out of the box, what goes into building your own model, and how to structure your project for success.
Data Visualization & Storytelling
Ezgi Karaesmen, Ph.D. Student, The Ohio State University
Katie Sasso-Schafer Data Scientist, Columbus Collaboratory
Date: August 10th & 11th, 2020
Time: 8:00 AM – 10:00 AM
In this 4-Hour Intro Data Science in R Workshop, Ezgi Karaesmen and Katie Sasso-Schafer provide a complete crash course on the full data science workflow from cleaning and wrangling to visualization, modeling, and repeatable reporting. These RStudio Certified Tidyverse Instructors will cover the essentials of popular R packages including
- tidymodels, and
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.
Introduction to Data Science in R
Lea Pica, Founder, LeaPica.com
Date: August 13th & 14th, 2020
Time: 1:00 PM – 4:00 PM
In this 6-Hour Data Storytelling Masterclass, Lea Pica discusses audience needs assessment techniques and provides a robust presentation planning framework that covers topics such as:
- What your stakeholders are thinking but aren’t telling you;
- Audience needs assessment + interview strategies; and
- Digitizing and refining your content plan.
Lea will also review neuroscience-backed design principles and share time-saving tricks on how to customize a PowerPoint template with client branding for reuse. She will also introduce her proprietary PICA Protocol™, her prescription for healthy, actionable data stories.
Preprocessing Data for Machine Learning in Python
Sarah Guido, Senior Data Scientist, InVision
Date: August 17th & 18th, 2020
Time: 9:00 AM – 11:00 AM
In this 4-Hour Preprocessing Data for Machine Learning in Python, Sarah Guido teaches the basics of how and when to perform data processing.
Topics covered include:
- 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.
Click here today to learn more or to register for the August Workshops.
Mitigating Bias in Analytics Series
WIA is excited to announce a new series in partnership with Tableau. This free virtual series—Mitigating Bias in Analytics—includes topics on data collection, design, policies and standards, building algorithms, and visualization and interpreting results.
From the financial sector to the healthcare industry, AI has played a revolutionary role in improving quality and reducing costs. As we navigate a post-pandemic world, technological advancements and AI will continue to play a critical role. But almost all big datasets generated by machine learning (ML) are biased, and most ML modelers are unaware of these biases. Data bias exists when data is not representative of the population or includes content that may contain human biases against a group of people.
Biased data produces biased models that can be discriminatory and harmful. Thoroughly evaluating the available data for potential bias should be a key step in modeling. Keeping humans in the loop and being mindful about the truth that is being modeled are ways to design processes that help mitigate bias.
Mitigating Bias in Analytics will address these issues and provide attendees with information on how to address them. The series is free and will be available virtually.
If you have any questions, you can contact our team at email@example.com.