Frequently Asked Questions

We built the course for professional software engineers who want to pick up ML. The typical applicant has several years of software engineering experience, though applicants from other disciplines (e.g. data scientists, hardware engineers, researchers) are also welcome.

The majority of alumni return to their engineering jobs with a newfound capacity to contribute to AI/ML initiatives at their company. Others go on to work at AI companies in SWE roles, and in some cases, continue their studies to recruit for dedicated machine learning roles.

Our goal is to launch you into the equivalent of Low Earth Orbit by accelerating you through the thickest layers of the machine learning atmosphere. As the spaceflight adage goes, "if you can get your ship into orbit, you're halfway to anywhere." After completing our course, the possibilities are endless.

The program fee is $6,800 USD. We offer flexible financing via Klarna (subject to a soft credit check), which offers payments as low as $320/mo.

We've carefully distilled the essential AI/ML knowledge needed to become a productive contributor. Our focused curriculum provides the most efficient path to machine learning competency, unlike other resources that often lack structure and industry applicability.

Our alumni consistently highlight four key benefits: (1) avoiding the common pitfalls of self-study, (2) collaborating with ambitious peers, (3) accessing expert instructor support, and (4) building real-world projects that go beyond typical sandbox assignments.

Most likely, yes. About half of our students receive some assistance from their employer to cover the cost of the course. We recommend proceeding with your application; we can help you through the process to receive reimbursement.

Great! The students who succeed wildly in our course are curious tinkerers that have done some self-study. While no prior experience with ML is required to join, you will enjoy pushing the boundaries of our curriculum if you have prior experience.

Yes, however, we have prepared resources for you to get up to speed on the math necessary to succeed in the course. We will share 10-20 hours of materials for you to complete prior to beginning the course which will help you build the necessary foundation. Prior experience with linear algebra, calculus, and statistics is a huge plus.

The only difference is the form factor: the 4-week program is an elongated version of the 2-week program. All of the curriculum content is the same. The 4-week program is built to accomodate learners who prefer interstitial downtime or are unable to commit to the intense 2-week schedule.

To get started, you can apply here. After we review your application, we'll invite you to schedule an interview. In the interview, we (a) explore your background and goals, (b) share more details about the program, and (c) answer any questions you may have.

If you want to get a feel for our curriculum and instructors, we recommend checking out our ML Primer Webinar.