Python Machine Learning Course Online (Self-Paced)
IDLNG

Self-paced online training with expert support

Gain a strong foundation in machine learning as you explore key concepts like regression, classification, and clustering using Python. You'll work with real datasets and libraries such as scikit-learn and pandas to develop practical skills for data analysis and predictive modeling. This self-paced format lets you progress on your own schedule.

$1,895 30 clock hours Live Support Start anytime

This course includes

  • 30 hours of project-based training from experts
  • Answers from real instructors
  • Access to class recordings (30 days)
  • Verified digital certificate of completion
  • Learn at an accredited institution

This course is self-paced. For live online or in-person instruction, take the Python Machine Learning Bootcamp.

This skill set is in high demand, as machine learning algorithms now power most trading on Wall Street and drive product recommendations at major companies like Amazon, Spotify, and Netflix.

The course begins with linear and logistic regression, two of the most proven and reliable approaches to tackling machine learning problems. You’ll then advance to algorithms with different theoretical foundations, including k-nearest neighbors, decision trees, and random forests. Along the way, you’ll explore key statistical concepts such as bias, variance, and overfitting. You’ll also learn how to measure model accuracy and gain practical tips for selecting the most effective features and algorithms.

Focused on practical, real-world problem-solving, the course explains the mathematical foundations of each algorithm visually, without a formal math requirement. Students should already be comfortable writing Python programs and working with NumPy and Pandas.

If you are new to Python, we require completing our Python for Data Science Bootcamp before enrolling in 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 the student to enroll in our Python for Data Science Bootcamp before taking this course.

Take this class as part of a certificate program and save:

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