You don’t have to be a computer scientist to launch your career in the emerging field of machine learning.
Apply for our free 10-week machine learning intensive at the following colleges and universities:
- Mills College, Oakland, CA (Spring 2019)
- Agnes Scott College, Decatur, GA (Summer 2019)
- Bay Path University, Longmeadow, MA (Summer 2019)
- Heidelberg University, Tiffin, OH (Summer 2019)
- Scripps College, Claremont, CA (Summer 2019)
Prerequisites: Two semesters of college-level computer science or data science and college level applied statistics
"We project that by 2020 the number of positions for data and analytics talent in the United States will increase by 364,000."
Study by IBM, Burning Glass and the Business-Higher Education Forum
As machine learning (ML) becomes a powerful tool across industries — from healthcare and retail to investment banking and insurance — there is a growing need for a workforce that understands how to apply ML strategically and use ML models to collaborate with data scientists and engineers for maximum business impact. The 10-week machine learning intensive gives students the strong computer science foundation they need to work with large datasets and solve real-world problems.
In this machine learning intensive for college credit, you will learn:
To investigate, clean, analyze, and visualize data
To understand different machine learning models and diagnose modeling issues so that you can adjust input data accordingly
To discern when machine learning is the “right” solution for a given data or business problem
To deepen your coding skills in SQL and Python
To gain understanding of the ethical use of AI and how to identify bias
To learn how to scale machine learning through cloud computing
Frequently Asked Questions
Who is the ideal candidate for this ML intensive?The ideal candidate is a college student or recent graduate with college-level computer science coursework who is genuinely interested in working with data and analytical problem-solving. All college majors are welcome!
What costs will be covered?In the first year, Google will cover the cost of tuition, room and board for all students who are accepted into the ML intensive. Students will need to pay their travel expenses to the college campus where they will be enrolled. Should they choose not to live on campus, they will also have to pay for their living expenses. Students will also be expected to bring a laptop computer.
Who are your instructors?Our instruction teams include Google machine learning engineers, alongside college faculty from the host institutions and teaching assistants to coach students through our project-based curriculum.
When is the deadline to apply and when will I be notified about admission?The spring application deadline is November 18, 2018. You will be notified of our admission decision on December 14, 2018. The summer application deadline is February 17, 2019. You will be notified of our admission decision on March 15, 2019.
What are the dates of the ML intensive?The Spring ML intensive at Mills College will run from February 12 - April 26 (with a one-week spring break March 25-29). The Summer ML intensive will run from May 28 - August 2.
How many credits can I earn by taking this ML intensive?The ML intensive, which runs from 9a-5p daily (with an hour break for lunch), is being offered by the host institutions for 9 credit hours. Please consult your college registrar for the applicability of these credit hours to your course of study and for the procedures involved to transfer them.
What kind of job placement services does the ML intensive provide?Working in conjunction with college placement offices at the host institutions, we will provide opportunities for students to network with teams at Google, as well as Google business partners.
What makes this ML intensive unique?
- Hands-on, applied, cohort-based approach
- Content developed by Google, delivered by an instruction team that brings together college faculty and industry experts
- A boot camp environment where you can also receive college credit
- Industry connections to assist you in your job search
- Non-technical skill development in program management, operations, self-presentation, and leadership
- Case Study approach for exposure to more complex, industry-driven scenarios that expose students to multiple features and approaches and different domains