Machine Learning Fundamentals

Most machine learning courses show you how to use an algorithm for predictive analysis. We teach you how to build, apply, and then optimize your analysis as you expand your Python skills.

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Enrollments close November 26, Cohort launches November 27.
$199 due to claim your seat.

What You'll Learn in
Machine Learning Fundamentals

Master scikit-learn. Build classifiers. Run predictive analysis. This Intensive was built to help you do more with machine learning in 7 weeks than most college students learn in 4 years.

  1. Unit 1

    What is Machine Learning?

    Learn about the types of problems to solve with machine learning.
    Easy
  2. Unit 2

    Regression

    Predict continuous-valued output based on the input value(s).
    Medium
  3. Unit 3

    Classification

    Classify data into different categories.
    Medium
  4. Unit 4

    Unsupervised Learning

    Find patterns and structures in unlabeled data points.
    Medium
  5. Unit 5

    Neural Network Teaser

    Implement a single neuron - the building block of neural networks.
    Medium
  6. Unit 6

    Capstone

    Apply your new knowledge to a complex project reviewed by experts.
    Challenging
Sonny Li, Curriculum Developer

What makes Codecademy Pro Intensive different?

“A team of data scientists, researchers, and educators came together to build the best entry point for the exploration of Machine Learning that’s fun, accessible, and relevant to anyone - not just folks with PhDs in math and science. At the end of this journey, you will have a completely new understanding of machine learning and the world around us.”

—Sonny Li
Curriculum Developer & Former Computer Science Lecturer at Columbia University

Work on Real World Projects

StreetEasy New York Rent Predictor Project Example

Use multiple linear regression to model the relationship between rent, square footage, number of rooms, and more.

Yelp Recommender Capstone Project Example

Use different supervised learning algorithms to predict Yelp users' favorite brunch and dinner spots.

Breast Cancer Classification Nearest Neighbors Project Example

Use several Python libraries to build a K-Nearest Neighbors classifier that is trained to predict whether a cell is malignant or benign.

Code Reviews by Professional Developers

Our team of developers will review your final projects and give you detailed and personalized feedback.

A Codecademy Advisor

Program Details: Machine Learning Fundamentals

Last Day to Enroll

November 26

Start Date

November 27

End Date

January 15

Cost

$199

Time Commitment

While you'll be able to move at your own speed, you should make sure that you generally have at least 10 hours a week to dedicate to the program in order to stay on track.

Eligibility

Basic understanding of Python is required to enroll. The program is available only in English.

Satisfaction Guarantee

We designed a program that we think you'll love. If this Codecademy Pro Intensive isn’t right for you, you can request a full refund within the first week.

Additional Questions?

Visit our Frequently Asked Questions page to find additional information or to contact our support team.

Enroll Now

$199 to claim your seat.

Alex Kuntz, Computer Science Teacher & Former AI Researcher at Northwestern

What will this course teach you?

“This course is the first of its kind on the market. We asked learners to build machine learning models themselves, rather than just applying what’s pre-built. Create complex machine learning models from scratch and use them to discover new truths about the world!”

—Alex Kuntz
Computer Science Teacher & Former AI Researcher at Northwestern

Space is limited. Secure your seat now!

Completing your enrollment takes only a few minutes.

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