2 Weeks
·Cohort-based Course
Get hands-on experience with modern forecasting tools & learn from case studies of the toughest forecasting challenges in the industry
Hosted by
Tim Januschowski and Jan Gasthaus
2 decades of joint experience in forecasting at Amazon & AWS, Zalando, Meta
This course is popular
4 people enrolled last week.
Course overview
Learn how to use time series machine learning techniques for predicting future outcomes to optimize business processes.
The course features practical lessons heavily that we derived from two decades of working on some of the world's hardest forecasting problems at Amazon retail, Zalando and for AWS and its customers. You'll pick up the necessary theory, get hands-on example and learn about the tricks of the forecasting trade.
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Data Scientists who want to go beyond standard ML/AI problems and solve forecasting related business problems
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Business analysts with familiarity in machine learning in industry settings who want to uplevel themselves in a top ML application domain
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Economists and Applied Scientists who want to apply industry-proven modern forecasting techniques
Modern Forecasting in Practice
Rob Hyndman
Ralf Herbrich
Alex Smola
Director Pricing Platform, Zalando
is the Director of Pricing Platform at Zalando SE, where he leads the organization responsible for setting prices for the Zalando wholesale business. This involves forecasting of demand heavily. Prior to Zalando, Tim led the time series science organization for Amazon Web Services’ AI division. His teams built multiple AI services for AWS such as SageMaker, Forecast, Lookout for Metrics, and DevOps Guru, top-tier scientific publications, patents, and open source. Tim is a director at the International Institute of Forecasters, serves as a reviewer for the major ML venues, lectures at TU Munich, and advises start-ups such as WhyLabs.
Software Engineer, Meta
is a software engineer at Meta. Before that, he was principal machine learning scientist at Amazon, where he worked on some of the largest time series prediction problems on the planet. As part of AWS AI Labs, he helped create the technology behind AWS services such as Sagemaker, Amazon Forecast, and Amazon DevOps Guru, and co-created the open-source deep learning forecasting library GluonTS. Before building services for AWS, he worked on a wide range of forecasting and time series analysis problems across Amazon’s businesses, including the massive-scale retail demand forecasting problem, AWS capacity planning, workforce planning, price forecasting, and anomaly detection for cloud resources. Jan holds a Ph.D. in Machine Learning from UCL, has co-authored over 30 scientific articles on time series modeling, served as area chair and reviewer for NeurIPS and other major ML conferences, and has given numerous keynotes, lectures, and tutorials on forecasting.
Cohort October 2023
$750 USD
Dates
Oct 9—20, 2023
Application Deadline
Oct 4, 2023
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Session 1: Should Your Business Problem Be Solved With Forecasting?
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Session 2: Forecasting Solutions Using a Small Set of Time Series
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Session 3: Forecasting Solutions With a Large Set of Time Series
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Session 4: Forecasting Solutions With Dependency Structures
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Session 5: What Best Practices Help You Avoid Common Pitfalls in Production?
12:00pm - 2:00pm EST
We have 5 full sessions each 2h, starting on Monday 9 October, 12pm EST (6pm CET).
Sessions will consist of an engaging mix of presentations, activities and notebooks.
Our main sessions will be on:
October 9, 11, 16, 18 & 20 from 12:00pm to 2:00pm EST.
Additional activities will be scheduled closer to the cohort start date.
1 hour per week
We'll have office hours and a deep dive (in the past with Max Mergenthaler, Nixtla) as well as guest speakers. Past guest speakers have included Slawek Smyl (winner of the M4 competition; Walmart, Meta, Uber, Microsoft) and Sean Taylor (creator of Prophet; Lyft, Meta).
Boyd Biersteker
Eva Giannatou
Leonidas Tsaprounis
Active hands-on learning
This course builds on live workshops and hands-on projects
Interactive
You’ll be interacting with other learners through breakout rooms and peer exchange
Learn with a cohort of peers
Join a community of like-minded people who want to learn and grow alongside you
Cohort October 2023
$750 USD
Dates
Oct 9—20, 2023
Application Deadline
Oct 4, 2023