Become a Machine Learning Engineer

Machine learning is becoming a fundamental skill as software development is entering a new era. This Nanodegree program prepares you to join this exciting field by providing hands-on experience building models, a thriving community of students, and world-class support from expert mentors and code reviewers.

This Nanodegree program will prepare you for a variety of roles, including Data Scientist and Machine Learning Engineer jobs.

In this Nanodegree program, you’ll learn key skills that prepare you for roles within companies seeking engineers with machine learning experience. You’ll also be ready to introduce machine learning techniques to organizations not yet utilizing machine learning techniques. Data analysts looking to move into roles more focused on machine learning will benefit from this program as well, as will anyone ready to build real-world skills with our hand-on learning approach.

No. This Nanodegree program accepts all applicants regardless of experience and specific background.

You will need to be able to communicate fluently and professionally in written and spoken English. Prior to entering the Machine Learning Nanodegree program, you should also have the following: Intermediate Python programming knowledge, of the sort gained through the Introduction to Programming Nanodegree, other introductory programming courses or programs, or additional real-world software development experience. Including:

• Strings, numbers, and variables
• Statements, operators, and expressions
• Lists, tuples, and dictionaries
• Conditions, loops
• Procedures, objects, modules, and libraries
• Troubleshooting and debugging
• Research & documentation
• Problem solving
• Algorithms and data structures

Intermediate statistical knowledge, of the sort gained through any of Udacity’s introductory statistics courses (listed in our FAQ at the bottom of this page). Including:

• Populations, samples
• Mean, median, mode
• Standard error
• Variation, standard deviations
• Normal distribution
• Precision and accuracy
• Hypothesis testing
• Problem solving
• Confidence Interval, P-values, T-test, Statistical Significance

Intermediate calculus and linear algebra mastery, addressed in the Linear Algebra Refresher Course, including:

• Derivatives
• Integrals
• Series expansions
• Matrix operations through eigenvectors and eigenvalues

Looking to refresh your skills or prepare now? Please refer to the list of helpful resources below.

We have a number of Nanodegree programs and free courses that can help you prepare, including:

• Introduction to Python
• Linear Algebra Refresher Course
• Introduction to Inferential Statistics
• Introduction to Descriptive Statistics
• Data Analyst Nanodegree program

The Machine Learning Nanodegree program is comprised of two (2) Terms of three (3) months each. A Term has fixed start and end dates. To graduate, students must successfully complete a total of seven (7) projects across both terms, each of which affords you the opportunity to apply and demonstrate new skills that you learn in the lessons. Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.

Access to this Nanodegree program runs for the period noted in the Term length section above.

See the Terms of Use and FAQs for other policies around the terms of access to our Nanodegree programs.

Please see the Udacity Nanodegree program FAQs found here for policies on enrollment in our programs.

Many of our graduates continue on to our Artificial Intelligence and Self-Driving Car Engineer Nanodegree programs.

We recommend having Anaconda installed with Python 3 as a minimum. Virtually any 64-bit operating with at least 8GB of RAM will be suitable.