Who is the course designed for?
We built the course for professional software engineers who want to pick up ML. The typical applicant has 5+ years of software engineering experience, though applicants from other disciplines (e.g. data scientists, hardware engineers, researchers) are also welcome.
What are the outcomes from the course?
The majority of students 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.
We'll launch you into the equivalent of Low Earth Orbit by accelerating you through the thickest layers of the machine learning atmosphere. After completing our course, the possibilities are endless.
Why is the course worth my time and money?
We carefully examined the AI/ML field and distilled the essential knowledge required to be a productive contributor. Our curriculum will guide you in the most time-efficient manner to a foundational knowledge of machine learning. Other paid courses and free resources do not provide a straight path to productivity or a community of like-minded peers for you to immerse with.
Alumni of our program often report that the highest density of value comes from (a) skipping the inefficiencies of self-study, (b) working intimately with like-minded peers, and (c) receiving on-demand help from knowledgable instructors.
What if I have some ML experience?
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.
Will my employer pay the tuition?
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.
Are there math prerequisites?
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.
How are the 2 and 4-week programs different?
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.
How do I get started?
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 (e.g., fees and availability), 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.