Build job-ready skills with 28 mini-projects and 3 capstones and an advanced specialization project that suits your career goals.
Launch your machine learning career in just 9 months part-time.
Build job-ready skills with 28 mini-projects and 3 capstones and an advanced specialization project that suits your career goals.
Work 1-on-1 with an expert mentor, industry career coach and student advisor when you need guidance from course start to new job.
Through one of our partnerships with reputable universities, earn a certificate of completion that proves your skills.
Through our university partnerships, build university-backed skills and earn a certificate that proves your mastery of core ML and AI skills.
Named one of the top 10 public universities in the nation for over a decade by U.S. News & World Report
Ranked #3 among top public universities by Forbes
Has served lifelong learners for over 60 years
UCSD Extended Studies alumni status upon completion
Constituent institution of the University System of Maryland
#1 largest public university
75 years supporting the educational needs of adult learners
University of Massachusetts Global is a private, nonprofit affiliate of the University of Massachusetts system
13,000+ students study with UMass Global each year
Nearly 90% of students balance their education with work
56% of students balance their education with parenting
$152K
Annual Median Advertised Salary of a Machine Learning Engineer in the US with 0-3 years minimum experience required.
Source: Lightcast; Oct 2022 - Sep 2023
In this machine learning and AI bootcamp, you will learn:
Linear and logistical regression, anomaly detection, cleaning and transforming data
Large language models
Generative AI
Plus, you’ll learn the tools and languages machine learning engineers use:
In just 9 months, you'll learn to master big data to solve big business problems and transform your career.
Learn from expert-curated content, then apply those skills through projects that mimic the work you’ll do in the real world.
Develop skills in linear and logistical regression, anomaly detection, cleaning and transforming data
Design a machine/deep learning system, build a prototype and deploy a running application that can be accessed via API or web service — no other bootcamp does this
Build a unique portfolio of projects that set you apart from others, so you can land the job you want
We’ll teach you the most in-demand machine learning models and algorithms you’ll need to know to succeed as an MLE. For each model, you will learn how it works conceptually first, then the applied mathematics necessary to implement it, and finally you will get experience training and testing the models. We’ll walk you through the best practices for predictive optimization, like hyperparameter tuning, and how to evaluate your performance. You’ll learn how to pick the right model for the challenge you are facing, and critically, how to implement and deploy these models at scale.
Algorithms for both supervised and unsupervised learning
Gauging model performance using a variety of cross-validation metrics
Using AutoML to generate baseline models
Model selection and hyperparameter tuning
Bias in models and model drift
Deep learning techniques like convolutional, and recurrent neural networks, and generative adversarial networks
Recommendation systems
Tools: Scikit-Learn, Tensorflow, Pandas, AutoML systems, AWS
Design a machine/deep learning system, build a prototype and deploy a running application that can be accessed via API or web service — no other bootcamp does this.
Complete the multi-phase capstone with the support of your mentor:
Phase One: Build a working prototype. Develop your project proposal, collect your data, wrangle and explore data, and create a machine learning or deep learning prototype.
Phase Two: Deploy your prototype. Create a deployment architecture, run your code end-to-end with testing, and deploy your application to production.
Aditya Bahl
Capstone project: Building an end-to-end production machine learning pipeline to track sentiment of financial news headlines
Katie He
Capstone project: Using a machine learning model to bring black-and-white TV shows to life
Maybe you’ve tried using online tutorials, low-cost courses, or online forums to boost your machine learning skills. The most effective learning happens when humans connect with other humans.
We've honed a human-centric approach ensuring you'll have support throughout your learning journey.
Build software engineering skills faster with an expert in your corner. Your mentor will keep you accountable and give you an insider's view.
Get prepared for the job search. Your career coach will help you gain confidence and know-how to land the role.
Stay on track and achieve your goals. Your student advisor has your back and will keep you on track to graduation.
You’ve got a built-in community — students who, just like you, are betting big on themselves.
Machine Learning Engineering & AI Bootcamp students come from a variety of professional backgrounds.
Prerequisites and course requirements
Proficiency in object-oriented programming (Python, Java, or JavaScript)
The syllabus, mentorship details and further information are available on the university bootcamp pages.