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

  • An innovative curriculum provides your team with state-of-the-art machine learning skills actually used in practice

  • Build hands-on machine learning forecasting skills via in person classroom or live virtual experience

  • Jumpstart your team's ML forecasting journey using Python - no previous Python experience required

Book a free Discovery Call

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 provide free online tutorials for your team.

Introduction to Machine Learning - Days 1 & 2

  • What is Machine Learning?

    Data Analyst, Teacher

    Why Decision Trees?

  • Course Datasets

    Exploratory Data Analysis (EDA)

    Hands-on Lab #1

  • Classification Tree Intuition

    Overfitting Intuition

    Gini Impurity

    Split Quality

    Splitting Categorical Data

    Splitting Numeric Data

    Classification Trees with Python

    Hands-On Lab #2

  • 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

  • Feature Engineering Intuition

    Data Leakage

    Decision Boundaries

    Engineering Numeric Features

    Engineering Categorical Features

    Engineering Date-Time Features

    Missing Data

    Hands-On Lab #4

  • Regression Tree Fundamentals

    Numeric Feature MSE

    Categorical Feature MSE

    Feature Evaluation

    Tuning Regression Trees

    Imputation with Regression Trees

    Hands-On Lab #5

  • Bad, Tree! Bad!

    Ensembles

    Bagging

    Feature Randomization

    Random Forests with Python

    Hands-On Lab #6

  • Feature Importance

    Tuning Random Forests

    Model Testing

  • Additional Resources

    Wanna Kaggle?

  • What is Forecasting?

    What is a Time Series?

    Time Series Characteristics

  • Our First Dataset

    Naive Forecasting Models

    Moving Average Forecasting Models

    Hands-On Lab #1

  • Is Your Model “Good”?

    Splitting Time Series Data

    Model Bias

    Mean Absolute Error (MAE)

    Validating Simple Forecasting Models

    Hands-On Lab #2

  • Time Series for Machine Learning

    What Are Lags?

    Creating Lagged Features

    Training an ML Forecasting Model

    Making Predictions

    Validating Predictions

    Hands-On Lab #3

  • Endogenous vs. Exogenous Features

    Endogenous Features

    Exogenous Features

    Exogenous Features Are Everywhere

    Hands-On Lab #4

  • Are Your Features Good?

    Permutation Feature Importance

  • The Problem with Regression Forests

    Predicting Changes

    Differencing Example

    Using Differences

    Evaluating Differencing Models

  • Continue Your Learning

Time Series Forecasting - Day 3

More Than Just “One and Done” Training

The ML Forecasting Bootcamp equips your team with the skills necessary for powerful forecasting.

However, the real magic comes from applying these skills in the real world.

This is why my ML Forecasting Bootcamp includes weekly office hours with your team after the training.

Nothing cements these skills like applying them to your business.

FAQs

  • Yes! Check out my ML Forecasting Consulting offering.

  • Yes! The bootcamp can be delivered virtually or in-person with your team.

  • Yes! The Bootcamp can be split across 6 half-days over back-to-back weeks.

  • Yes, the Bootcamp can be customized to use your organization’s data for an additional charge.

  • I’ve trained over 1,000 professionals in machine learning, and nothing beats a hands-on project at work to cement the skills built during training.

    This is why the Bootcamp pricing includes weekly office hours to help your team apply what they’ve learned.

  • 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.

  • Yes, fundamental skills with Python are required for the Bootcamp.

    Not to worry, though. I will provide your team with free online tutorials to teach them what they need to know.

  • The Bootcamp can be taught using Python in Excel.

  • The Bootcamp is offered only as a live team training at this time.