Intro to Machine Learning Class

Get started with machine learning using python with a hands-on, in-person class with expert instructor Ted Petrou. 

Intro to Machine Learning Class Schedule

Register now for a class in one of the following cities.

Comprehensive hands-on course

Get a comprehensive introduction to machine learning using python with detailed live coding, exercises, and an expert instructor. Walk away with a solid grasp of the fundamentals and a direct path towards mastery.

Trusted Expert

Ted Petrou teaches all classes and has over 1,000 hours of live, in-person instruction experience. He is the author of numerous books including Master Data Analysis with Python and is the creator of the libraries Dexplo and Dexplot. Ted is constantly improving and upgrading the material to ensure it is of the highest quality.

Hands-on Exercises

Watching others code gives the false impression of learning. In reality, learning is demonstrated when you complete tasks yourself. During class, you will be given ample time to complete exercises and projects. Ted is very dedicated during this time to ensure students get the help they need.

Certificate of Completion

You will not be able to master all the fundamentals of basic machine learning in any one-day course. However, upon completion of this course, you will be given a direct path towards continuing your education. Completing this path will earn you a certificate of completion.

Detailed Course Description

Before the course

  • Installation - You will be given detailed instructions on how to install python onto your machine and set up an environment to run all the code during class.
  • Juptyer Notebooks - We will be using the excellent (though still needing improvement) Jupyter Notebook to run most of the code during class. They provide an interactive coding environment to quickly execute code, get feedback, and make notes.
  • Assignment - A short assignment introducing how to use Jupyter Notebooks is expected to be completed. You will also learn how to add and edit notes using Markdown.
  • Private Slack Channel - Upon registration, you be given access to Ted's private slack channel where you can directly communicate him and ask him questions about the course.
  • Master Machine Learning with Python - You will get a digital copy (complete with a PDF and Jupyter Notebooks) of a sample

Day 1

  • The machine learning model - Models are anything that help us represent the real world. You will learn how machine learning models are a subset of mathematical models that learn from data.
  • The scikit-learn estimator - In this class, we will use the excellent scikit-learn library to handle all of our machine learning. scikit-learn uses a generic class of objects called estimators that do all of the machine learning as well as other tasks that learn from data. You will learn how to use an estimator with the three step process - import, instantiate, fit.
  • Linear regression - You will learn how to model data with linear regression, a simple and practical model that is useful starting point before diving into more advanced models. You will learn how the parameters of the model are fit and understand what it means to minimize squared error.
  • Model evaluation and selection - The goal of machine learning is to build a model that is accurate on data that it has yet to encounter. You will learn how to determine how well a model is likely to perform on unseen data by properly evaluating it with techniques such as cross validation. You will also learn how to choose 'better' models by choosing combinations of hyper-parameter values that yield good cross-validated results.
  • Transformers and pipelines - We take a step back to learn how to transform our data before machine learning so that we can build a better model. You will learn about different transformations such as filling in missing values and standardizing features. You will then learn how to combine multiple transformations together in a pipeline.
  • The ColumnTransformer - With the release of scikit-learn version 0.20, the ColumnTransformer was made available to give us a much easier and direct way to applying different transformations to different features of our data. This greatly simplified the workflow and allowed us to build a single object containing all the transformation and machine learning steps.
  • Model persistence - Building a model is great fun, but we need a way to access it in the future. You will learn how to save a model as a file and retrieve it any time you need to make a new prediction.

After the course 

  • Certificate of completion - Upon conclusion of the course, you will be given a direct path towards mastering the fundamentals of machine learning using python. If you go on to complete all the tasks on this path, you will receive a certificate of completion.
  • Continual access to material - You will always have access to the material after the course has completed. Ted upgrades and adds to his material on a regular basis. You will always have immediate access to the latest updates.
  • Continual Slack Access - You will also have access to Slack forever meaning you can interact with Ted along with all of the previous students.

Target Student

The Intro to Machine Learning Class targets those who have little to no machine learning experience, but do understand the fundamentals of programming in Python. If you do not feel comfortable with basic Python, then this course is not for you. Consider taking the Intro to Python Bootcamp (2 days) first which will give you all the skills needed to prepare for this course.

It is also helpful to have experience exploring data using the pandas library. Consider taking the Intro to Data Science Bootcamp (2 days) to acquire these skills.

Interactive Class

Class time is divided into live coding sessions delivered by Ted and hands-on practice exercises and projects that you complete. During the live coding, you are provided an outline of the topics that Ted will cover as a Jupyter Notebook. During this time, you can code right along with Ted, exploring how the commands work, and ask questions.

During student exercises, Ted is always available to provide help directly at your seat. He is constantly seeking out students who may be in need of extra support.

About the Instructor

This course is taught by Ted Petrou, an expert at Python, data exploration and machine learning. Ted has taught hundreds of students Python and data science in live classroom settings. He is an enthusiastic instructor and dedicates his time during student exercises to ensure understanding.

He holds a master's degree in statistics from Rice University and is the author of multiple books, including Exercise Python, Master Data Analysis with Python, and Pandas Cookbook.

Class Notes

Everyone who registers gets a digital copy of the class notes which contain a PDF and many Jupyter Notebooks with detailed explanations of the material. There is more material available than what is possible to be covered in class. You will have permanent access to this material.

Intro to Machine Learning Class Schedule

Register now for a class in one of the following cities.

Former Student Sayantan Mitra

Hear Sayantan's experience taking the bootcamp and then transitioning to a teaching assistant.


Frequently Asked Questions

If you have a more specific question, or just want to chat with Ted, click the chatbox in the corner and he'll answer your question as soon as he can.

Ted began programming 22 years ago by building games on his Texas Instruments graphing calculators and has been programming ever since. 

He has taught over 1,000 hours of live in-person python, data science, and machine learning. He is constantly striving to learn more, refine his material, and produce the absolute best possible class each time he teaches.

Ted's biggest accomplishments in Python have been authoring the Dexplo and Dexplot libraries that are meant as alternatives to pandas and seaborn. Ted has answered over 400 questions on Stack Overflow

You might be thinking to yourself, "Hey, this course is around 80-90% less than other similar courses, there must be something wrong". I would also be seeing red flags at this price point. 

I believe my classes to be the best possible classes for the subjects they cover at any price point. I am having trouble attracting potential customers to my website and due to this very low visibility, I am keeping prices extremely low. I also have close to 0 overhead for my business as I am the only employee.

Yes, you can. Just send me a message by clicking the chatbox below and I'll connect you to a former student who can answer some of your questions. If you prefer, you can also email me directly at [email protected]

There are plans to make a similar course available online for those that want to learn from the comfort of their own home. This current course offered on this page is only for live, in-person classes.

No, not at this time. The course is extremely cheap and the plan is to raise prices once there is more visibility. Once prices are raised closer to the market average, discounts will be given to students or unemployed.

Yes, I am available for corporate training and can customize a syllabus that best suits the needs of your group. Please contact me directly at [email protected] for any corporate training inquiries.

Intro to Machine Learning Class Schedule

Register now for a class in one of the following cities.


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