Data Science Bootcamp

Empower your team with state-of-the-art skills to discover hidden patterns in your data

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

  • Build hands-on data science skills via in person classroom or live virtual experience

  • Jumpstart your team's advanced analytics journey using Python - no previous Python experience required

Answering the call for advanced analytics

Is data science shaping the future of your organization?

While data has always been used in business, things have changed. Functions like HR, Product Management, Customer Service, etc., are embracing advanced analytics to drive better business outcomes.

Do you want your team to be a part of this data-driven future?

It’s hard to avoid all the social media posts, magazine articles, or news clips trumpeting how data science is permanently changing the way organizations operate – and changing the expectations of organizations.

Data science for ANY team - regardless of role/background

Imagine a team of Product Managers that could answer the following question with data, "What feature usage(s) are highly predictive of a sticky customer?" How much value would they bring to their organization?

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

Data Science Bootcamp

The Data Science Bootcamp empowers your team with skills such as random forest predictive models and k-means clustering, enabling them to discover new insights.

If your team is new to Python, I offer free online tutorials that cover everything they need to know before the bootcamp.

This training focuses on practical data science skills, so your team can hit the ground running and deliver insights quickly.

Clients often bundle additional courses (see below) to enhance their team’s capabilities.

The outcome?

Your team will possess the knowledge and hands-on skills to utilize data science to uncover hidden patterns in your data, including crafting predictive models and conducting cluster analyses.

  • A well-defined set of skills for real-world data science insights

  • Your team will build real-world skills via 12 hands-on labs

  • Courses can be taught using Python in Excel if that works better for your team

  • Courses can be taught in-person or virtually. Choose what works best.

  • Taught by Dave Langer, globally recognized data science instructor

  • Bundle additional courses to expand your teams capabilities

Machine Learning Bootcamp Curriculum

3 days. 12 hands-on labs.

Bootcamp can be taught with Python in Excel.

  • 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?

The following is the 3-day curriculum. The curriculum can be expanded by bundling additional courses (see below).

My free online tutorials are available for teams new to Python.

Introduction to Machine Learning - Days 1 & 2

  • Course Expectations

    What is Cluster Analysis?

    Cluster Analysis Use Cases

    The Challenge of Clustering Data

  • The Iris Dataset

    The Hand-Written Digits Dataset

    The Heart Dataset

  • Hierarchical, Partitional, and Overlapping Clustering

    Prototype Clusters

    Density-Based Clusters

  • Introducing K-Means

    The K-Means Algorithm

    Euclidian Distance

    The Problem with Outliers

    Data Standardization

    K-Means Caveats

    Hands-On Lab #1

  • Evaluating Clusters

    Cluster Cohesion

    Evaluating Cohesion with the Elbow Method

    The Silhouette Coefficient

    Evaluating Clusters using the Silhouette Score

    Hands-on Lab #2

  • Introducing DBSCAN

    The DBSCAN Algorithm

    DBSCAN Caveats

  • Considerations for Optimizing DBSCAN

    Calculating min_samples

    Choosing the eps Value

    Introducing Nearest Neighbors

    Evaluating eps with the Elbow Method

    DBSCAN vs K-Means

    Hands-On Lab #3

  • Introducing Dimensionality Reduction

    Principal Component Analysis (PCA)

    PCA Concepts

    Hands-On Lab #4

  • The Problem with Categories

    Encoding Categorical Data

    Factor Analysis of Mixed Data (FAMD)

  • Supervised Learning Resources

    Cluster Analysis Resources

Cluster Analysis - Day 3

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.

Because ROI is generated after training.

NOTE - I also offer coaching services for teams serious about generating ROI fast.

Course Add-Ons

Expand your team’s capabilities by bundling additional courses into your bootcamp.

Courses can be taught using Python in Excel.

  • Time Series Forecasting

    This 1-day hands-on course teaches how to apply machine learning models to build better forecasts. ML forecasting models are state-of-the-art because of their ability to incorporate the complexities of modern businesses better than traditional forecasting techniques.

  • Text Mining

    This 1-day hands-on course is an introduction to the tools an techniques of transforming text data into a form suitable for analytics. Examples include clustering documents and sentiment analysis. Topics include tokenization, stemming, lemmatization, TF-IDF, and cosine similarity.

  • Visual Data Analysis

    This 1-day hands-on course teaches how to use data visualizations the way Data Analysts/Scientists do - to get to the “why” of what’s happening. This course focuses on topics useful to any team, including Distribution Analysis, Correlation Analysis, Multivariate Analysis, and Time Series Analysis..

FAQs

  • Yes! Check out my Data Science 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.

  • 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.

  • All the courses use Python as the programming language. My free Python Crash Course is available for teams new to Python.

  • The Bootcamp can be taught using Python in Excel with some modifications.

    Book a free discovery call to discuss the available options.

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