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Forecasting with Machine Learning

Time-series forecasting is one of the longest-standing applications of machine learning, and is one of the most prevalent techniques used across all of industry (if not the most prevalent). And yet, during the recent ML boom, forecasting has been somewhat left behind. The goal of this course is to marry the latest-and-greatest of the field of ML with the existing, classical statistical techniques. In particular, the focus of this course is the practical applications of these techniques, and how they supercharge applications such as causal analysis, demand intelligence, and labor planning.

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Mark Tenenholtz
VP of Data Science, Predelo
US$ 400
or included with membership
3 weeks
Space is limited

Course taught by expert instructors

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Mark Tenenholtz

VP of Data Science, Predelo

Mark got his start in forecasting while working for Kroger/84.51 in targeted marketing before moving to their central forecasting team. There, he built forecasting models at scale for the largest grocer in the U.S. While there, he became a Kaggle Competitions Master, including a solo gold medal in a forecasting competition. Now, he is the VP of Data Science at Predelo.

The course

Learn and apply skills with real-world projects.

Who is it for?
  • Data scientists who have a background in forecasting, but want to catch up with the state-of-the-art.

  • New and experienced data scientists/ML practitioners who want to get their start in forecasting.

  • Anyone across the data stack (data scientists + engineers) who want to better understand the forecasting models needed to power downstream applications.

  • Intermediate knowledge of Python, including Pandas and NumPy.

  • Basic fundamentals of machine learning.

Not ready?

Try these prep courses first

  • End-to-end overview of forecasting problems
  • Making the most of Pandas for time-series data
  • Finding signal in time-series data
  • Overview of modeling approaches, from univariate to global
Build a category/store/state-level forecasting model for retail store sales
  • Explore the data at the item level
  • Discover the pros and cons of different types of models at different levels
  • Decompose retail sales into components
  • Quantifying model performance
  • Setting up reliable backtesting frameworks
  • Model interpretation
  • Applying ML models to forecasting problems
Build a cross-validation setup and train ML models
  • Compare different metrics (what do they catch and not catch?)
  • Build features, analyze your models, and repeat
  • Hierarchical forecasting
  • Ensembling models
  • Use-cases for time-series models, including causal analysis, labor planning, and understanding demand drivers
  • Causal analysis: understand the the effect of business decisions
Combine what you learned in weeks 1+2 to make even better models
  • Create optimized ensembles for your high-level and low-level models
  • Decompose your high-level models into low-level predictions, aggregate your low-level models to high-level predictions, and reconcile the two for great performance
  • Compare the robustness of ensembles to individual models over multiple time periods
  • Advanced application topics

A course you'll actually complete. AI-powered learning that drives results.

AI-powered learning

Transform your learning programs with personalized learning. Real-time feedback, hints at just the right moment, and the support for learners when they need it, driving 15x engagement.

Live courses by leading experts

Our instructors are renowned experts in AI, data, engineering, product, and business. Deep dive through always-current live sessions and round-the-clock support.

Practice on the cutting edge

Accelerate your learning with projects that mirror the work done at industry-leading tech companies. Put your skills to the test and start applying them today.

Flexible schedule for busy professionals

We know you’re busy, so we made it flexible. Attend live events or review the materials at your own pace. Our course team and global community will support you every step of the way.


Completion certificates

Each course comes with a certificate for learners to add to their resume.

Best-in-class outcomes

15-20x engagement compared to async courses

Support & accountability

You are never alone, we provide support throughout the course.

Get reimbursed by your company

More than half of learners get their Courses and Memberships reimbursed by their company.

Hundreds of companies have dedicated L&D and education budgets that have covered the costs.


Frequently Asked Questions

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