Analytics Edge Programme Part II
| Date | 05 Jul - 09 Aug 2022 |
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| Facilitator: |
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| Location | Self-paced fully virtual training course, only the "meet the expert hour" sessions are live via MS Teams |
Further Information
Learning goals
- Gain the digital analytics insights you need to help you arrive at better business outcomes.
- Creating a problem statement and addressing its data, models, decision points and value chains needed to solve it.
- Find out how to tactically navigate the common pitfalls that cause ML / AI project failures.
- Learn how a common fungible framework can be used to execute analytics projects and provide clear guidance on when to intervene.
- Each participant’s experiences will be transformed into a workbook.
Requirements
- Part I of the Analytics Edge Programme is required.
- Exclusively for executives and senior managers eager to expand their knowledge and capabilities of modern analytics methods.
- Participants must be fluent in English.
- No coding required.
Dates
5 July – 9 August 2022
Maximum six weeks, at your own pace, including "meet the experts' hour" sessions hosted by Swiss Re.
Expert hours will take place at 16:00 CEST | 10:00 EST on the following days:
Tuesday, 5 July 2022
Tuesday, 12 July 2022
Tuesday, 19 July 2022
Tuesday, 26 July 2022
Tuesday, 2 August 2022
Tuesday, 9 August 2022
Disclaimer
The event may be photographed, videotaped, filmed and /or digitally recorded. You consent to Swiss Re's use, free of charge, of any memorialization of the event in which you may appear for any Swiss Re publication or promotional purpose.
Further Information
Agenda
Module 1: Capacity Planning
Robust Optimization
Conduct capacity planning in the face of uncertainty with robust optimization.
Module 2: Jury Selection
Bias Detection
Leverage optimal feature selection and optimal classification trees to detect racial bias in jury selection.
Module 3: Real Estate Pricing
Intuition-Guided Model Building
Predict housing prices by using a tree-based model with linear regression leaves.
Module 4: Structuring Data to Predict Stroke
Natural Language Processing and Outcome Prediction
Leverage natural language processing to build a model to identify and predict stroke.
All Modules contain
- A video introduction between Dimitris and Jordan.
Professor Dimitris Bertsimas; Boeing Leaders for Global Operations Professor of Management at Massachusetts Institute of Technology, author of numerous publications, including Analytics Edge.Feature an actual live analytics tool. Its story of each tool from idea to production is delivered across the common accessible framework of data, models, decisions, and value chain.
Jordan Levine is a lecturer at the Massachusetts Institute of Technology (MIT) and a partner at Dynamic Ideas, an organization committed to spreading powerful ideas in the areas of analytics, operations research, and their applications. He focuses his energy on translating complex data and analytics topics to business audiences.
- An actual live analytics tool. Its story of each tool from idea to production is delivered across the common accessible framework of data, models, decisions, and value chain.
- A series of common failure modes that analytics leaders will be equipped to navigate.