Python Machine Learning Course Online (Self-Paced)

Self-paced online training with expert support

Learn the fundamentals of machine learning, including regression analysis and classification algorithms, in this practical, hands-on course. Gain the skills needed to solve real-world problems using machine learning, with a focus on Python programming and data science libraries.

$1,895 30 clock hours Start anytime

This Course Includes:

  • 30 hours of project-based training from experts
  • 95 training videos
  • Answers from real instructors
  • 1-on-1 bonus training
  • Retake for free within 1 year
  • Access to class recordings (30 days)
  • Verified digital certificate of completion

This skillset is in high demand, as machine learning algorithms now run the majority of trading on Wall Street and the product recommendations at big companies like Amazon, Spotify, and Netflix.

This course will begin with linear and logistic regression, the most time-tested and reliable tools for approaching a machine learning problem. The course will then progress to algorithms with a very different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. You’ll also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.

The course will be focused on the practical skills needed to solve real-world problems with machine learning. The mathematical foundations for each machine learning algorithm will be explained visually, but there will not be a formal math component. Entering students are expected to be comfortable with writing Python programs, as well as the Numpy and Pandas libraries.

This course does require students to be comfortable with Python and its data science libraries (NumPy and Pandas). If a student has not worked in Python before, we require a student to enroll in our Python for Data Science Bootcamp before taking this course. 

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This course has a prerequisite

This course requires students to be comfortable with Python and its data science libraries (NumPy and Pandas). If a student has not worked in Python before, we require a student to enroll in our Python for Data Science Bootcamp before taking this course.

Video Training Preview

Lesson 1: Basic Regression Analysis
Lesson 2: Supervised Learning Essentials
Lesson 3: K-Nearest Neighbors
Lesson 4: Titanic Survivial Prediction
Lesson 5: Neural Networks

Highly Reviewed by Our Alumni

From our hands-on training style to world-class instructors and custom-crafted curriculum, we deliver results our alumni are proud of.

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