Machine Learning Forecasting Bootcamp
Empower your team with state-of-the-art skills to discover hidden patterns in your data and craft powerful forecasts that drive business decisions
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An innovative curriculum provides your team with state-of-the-art machine learning skills actually used in practice
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Build hands-on machine learning forecasting skills via in person classroom or live virtual experience
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Jumpstart your team's ML forecasting journey using Python - no previous Python experience required
What professionals have to say
Bring the same high-quality training experiences of national conferences to your team.
Training delivered in person or live virtual - whichever works best.
“Very good course as an intro to machine learning. I feel that with what I learned today I can put these skills into practice at work.”
— David Green, EMWD
“Fantastic intro ML course that’s presented in an engaging way. The content was easy to understand and the labs were easy to follow along. I’ve left the course wanting to dive deeper into the topic.”
— Jessica Liu, O-I Glass
“MIND BLOWN…not by the difficulty of the class, but by how EASY Dave makes machine learning within the reach of aspiring Data Scientists.
Easily the highlight of this year’s conference for me. I feel empowered to bring this material back to the job, put it to use, and teach it to others.”
— Chet Phelps, Health Solutions
“Best training and instructor I’ve had. Organized, clear, good pace, helpful examples, and an engaging and fun instructor.”
— Alex Kurtz, Sourceability
“I am so glad to have started the conference in Dave’s class. He set a wonderful tone for what is yet to come. I hope my other courses measure up!”
— Christina Mitchell, Naphcare
“Great class! Engaging instructor. Wish I would have had more time this week to attend his other sessions.”
— Matthew Royalt, Southern Star Central Gas Pipeline
ML Forecasting Bootcamp Curriculum
3 days. 12 hands-on labs.
Bootcamp can be taught with Jupyter Notebook or Python in Excel.
Is your team new to Python? No worries!
I will provide a free crash course to your team.
Introduction to Machine Learning - Days 1 & 2
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What is Machine Learning?
Data Analyst, Teacher
Why Decision Trees?
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Course Datasets
Exploratory Data Analysis (EDA)
Hands-on Lab #1
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Classification Tree Intuition
Overfitting Intuition
Gini Impurity
Split Quality
Splitting Categorical Data
Splitting Numeric Data
Classification Trees with Python
Hands-On Lab #2
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Under/Overfitting
The Bias-Variance Tradeoff
Supervising the Data
Model Tuning
Classification Tree Pruning
Measuring Awesomeness
Splitting the Dataset
Modeling Tuning with Python
Hands-On Lab #3
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Feature Engineering Intuition
Data Leakage
Decision Boundaries
Engineering Numeric Features
Engineering Categorical Features
Engineering Date-Time Features
Missing Data
Hands-On Lab #4
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Regression Tree Fundamentals
Numeric Feature MSE
Categorical Feature MSE
Feature Evaluation
Tuning Regression Trees
Imputation with Regression Trees
Hands-On Lab #5
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Bad, Tree! Bad!
Ensembles
Bagging
Feature Randomization
Random Forests with Python
Hands-On Lab #6
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Feature Importance
Tuning Random Forests
Model Testing
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Additional Resources
Wanna Kaggle?
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What is Forecasting?
What is a Time Series?
Time Series Characteristics
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Our First Dataset
Naive Forecasting Models
Moving Average Forecasting Models
Hands-On Lab #1
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Is Your Model “Good”?
Splitting Time Series Data
Model Bias
Mean Absolute Error (MAE)
Validating Simple Forecasting Models
Hands-On Lab #2
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Time Series for Machine Learning
What Are Lags?
Creating Lagged Features
Training an ML Forecasting Model
Making Predictions
Validating Predictions
Hands-On Lab #3
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Endogenous vs. Exogenous Features
Endogenous Features
Exogenous Features
Exogenous Features Are Everywhere
Hands-On Lab #4
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Are Your Features Good?
Permutation Feature Importance
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The Problem with Regression Forests
Predicting Changes
Differencing Example
Using Differences
Evaluating Differencing Models
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Continue Your Learning
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Time Series Forecasting - Day 3
Because ROI is generated after training.
I’ve had the privilege of successfully training 1,000+ professionals, and one this has always been true.
Learning the hands-on skills is the easy part. It’s after the training when ROI is generated.
This is why all of my training engagements include:
PDFs of all course slides, including notes.
Access to Zoom recording for 6 months.
Access to the Virtual Dave AI tutor for 6 months.
NOTE - I also offer coaching services for teams serious about generating ROI fast.
FAQs
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Yes! Check out my ML Forecasting Consulting offering.
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Yes! The bootcamp can be delivered virtually or in-person with your team.
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Yes! The Bootcamp can be split across 6 half-days over back-to-back weeks.
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Yes, the Bootcamp can be customized to use your organization’s data for an additional charge.
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While the courses do include mathematics, it is at a level accessible to a broad audience. For example, no knowledge of calculus or statistics is required.
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Yes, fundamental Python skills are required for the Bootcamp.
Not to worry, though. I will provide your team with a free crash course to teach them what they need to know.
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The Bootcamp can be taught using Python in Excel with some modifications.
Book a free discovery call to discuss the available options.
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The Bootcamp is offered only as a live team training at this time.