What do you think are the top ten, key and practical data analytics methods in that are in use in the business world today?
On Wednesday, July 29th Victor Lo (Fidelity Investments) provided a comprehensive overview of those topics that he feels are proving to be these essential methods. He organized his 'top ten' list into three major categories: descriptive, predictive and prescriptive analytics. In addition, he contended that the topics in this list are those that might not necessarily be covered in many statistics programs. He then provided an informed and authoritative presentation of the major features that describe the following approaches below.
Each of these topics in turn will presented as individual 3 hour online tutorial sessions, (date and instructor noted below.)
- October 7, 2020 - "Jim Harner Leads First Session Loaded with Methods and Examples Describing Data Science Workflows"
- October 21, 2020 - "Second Data Science Tutorial Focuses on Data Visualization Led by Lee Wilkinson"
- November 4, 2020 - "Predictive Analytic Tools Featured as Part of Third Data Science Tutorial"
- November 18, 2020 - "Causal Inference and Uplift Modeling Take Center Stage in Data Science Tutorial"
- December 2, 2020 - Ming Li: "Deep Learning" (see event page)
- Winter 2021: "Prescriptive Analytics and Optimization"
- Winter 2021: "Unstructured Data Analysis"
- Winter 2021: "Social Sciences and Data Science Ethics"
- Winter 2021: "Domain Knowledge and Application Areas"
- Winter 2021: "Analytical Consulting, Communication and Soft Skills"
Through various snippets and examples into the viability and practicality of these approaches during his presentation, Victor effectively paved the way for NISS to unveil a new series of tutorials that will tackle each of these approaches in turn. Three hour tutorial type sessions will delve deeper into each of these topics and provide practical and useful Information about each.
At the overview session, there were approximately 120 attendees who had plenty of questions regarding the use or the implications of one type of analysis or another. Lingzhou Xue, Assistant Director of NISS served as moderator of this overview event.
Use the links above to access more information about each of the planned tutorials in this series.
NISS is interested in sharing knowledge. To this end, these tutorials have been geared to provide practical information that you can use tomorrow. Examples, projects and code sharing are a part of these sessions wherever possible.
Participants require a working knowledge of probability distributions, statistical inference, statistical modeling and time series analysis as a prerequisite. Students who do not have this foundation or have not reviewed this material within the past couple of years will struggle with the concepts and methods that build on this foundation.
Registrations options: $35 for single Data Science Essentials tutorial sessions, $250 for all 10 Essential Data Science for Business tutorial sessions. Can attend the live session? Post Session Access to tutorial materials and recording can be obtained for $35 after the event is over. NISS Affiliates, (https://www.niss.org/affiliates-list), please send an email to email@example.com.
Recording of the Overview Session
Slides Used by the Speaker
Victor Lo, (Fidelity Investments)