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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 provide free online tutorials for 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
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.
📌 P.S. - Don’t forget to ask me about pricing for small teams.
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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      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. 
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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 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. 
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      The Bootcamp can be taught using Python in Excel. 
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      The Bootcamp is offered only as a live team training at this time. 
