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.
Course taught by expert instructors
VP of Data Science, Stealth
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 for a stealth forecasting startup.
Learn and apply skills with real-world projects.
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.
Try these prep courses first
Build a category/store/state-level forecasting model for retail store sales
- 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
- 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
Build a cross-validation setup and train ML models
- Quantifying model performance
- Setting up reliable backtesting frameworks
- Model interpretation
- Applying ML models to forecasting problems
- Compare different metrics (what do they catch and not catch?)
- Build features, analyze your models, and repeat
Combine what you learned in weeks 1+2 to make even better models
- Hierarchical forecasting
- Ensembling 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
Application of Advanced Topics
- Use-cases for time-series models, including causal analysis, labor planning, and understanding demand drivers
- Causal analysis: understand the the effect of business decisions
- Labor planning: using forecasting to properly staff retail stores
- Demand intelligence: interpret your models to understand what drives demand, why some locations succeed (and others don’t), and even help choose new locations
- Building a pipeline to retrain your models
- Looking inside a production pipeline
- Emerging models and tools for efficient and accurate forecasting
A course you'll actually complete. AI-powered learning that drives results.
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.
Each course comes with a certificate for learners to add to their resume.
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.