Four years ago, we quit our jobs and spent several months learning data science and deep learning. We completed several online courses, read some books, and participated in some Kaggle competitions. We were finally able to make a career transition to data science, but looking back at the journey, we felt “It shouldn’t be this hard!”
While there are various platforms offering data science education, most learners don't feel confident while approaching real-world projects even after completing multiple courses and earning certifications. They find it hard to clear interviews to land their first job, and often require several months of training on the job.
Jovian is the platform we wished we had access to when we started learning. There are three things we focus on: (1) we teach practical skills that students use to build real-world projects, (2) we offer 24x7 support & detailed feedback on every project, (3) students learn together with a community of like-minded learners in a university-like environment. We’ve taken inspiration from courses like fast.ai and mlcourse.ai.
Our 6-month program consists of 7 courses, 14 coding assignments and 4 portfolio projects. Every week, students watch 5-6 hrs video lectures and work on assignments for 15-20 hrs. Students can ask questions and get help 24x7 from our TAs over Slack and Zoom. Every 5 weeks, they complete a unique guided real-world project and publish a blog post. We offer 1:1 resume review, interview practice, and job search support for 12 months. We make money by charging a flat fee for the course, which students can pay up-front or monthly.
One thing we discovered and found surprising is that most of the math used in data science can be explained through code. Many people find math intimidating not because the concepts themselves are tough, but because they aren't used to mathematical symbols and equations.
We look forward to your comments!