OSSU

2026-05-01

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I just completed the core material of the OSSU Computer Science curriculum.

My Background

Prior to starting OSSU, I already had an associate degree in computer science from a local community college, and 2 years of software development experience.

One of the reasons I decided to pursue this curriculum was because I didn’t finish my undergrad. I was already working full time writing software, and I never felt the need to continue my studies in traditional education. Why finish my undergrad if I was already gaining experience doing the job I intended to do coming out of college?

My Journey

It took me five years to complete all the courses, but realistically I could’ve done it in two years like the curriculum suggests. But I had taken many breaks between courses. I would only take one course at a time, and do most of my studies on the weekend.

Timeline

Here is a timeline of the 30 courses I took:

Notable Events

Some notable events that occurred during my five year journey with OSSU:

Best Courses

The Nand2Tetris course changed my life. It instilled confidence in me and provided a grass roots framework to reason about topics in the field of computer science. You literally build a computer in this course. It’s such a simple and elegant idea.

The Machine Learning specialization is a great example of what a high quality course looks like. It’s less project focused, but Andrew Ng does a great job breaking down machine learning concepts from first principles. The cadence is: practical example, underlying algorithm, implement in code, and a jupyter notebook to test your intuition.

Takeaways

After OSSU, I now have a solid foundation to reason about ideas in computer science from first principles.

In a traditional school setting, I was easily bored and distracted. I always thought I was a bad student, but OSSU was a perfect self-paced medium for me to grasp the material of a subject and actually learn! Which makes me think of all the other people who struggle to learn in those types of settings too, and if only they could opt for a track like OSSU instead.

The curriculum maintainers put a lot of thought into what courses to feature and it is amongst the best free material accessible to anyone in the world.

After taking all these courses and reading all these books, it’s made me realize that these are actually great on-ramps into researching topics more deeply and coming up with ideas for projects to work on.

I’ve built a habit to make learning a part of my routine going forward.

Coursework

Coursework is a very efficient way for people to learn concepts at the beginning parts of breaking into a new field. – Andrew Ng

https://www.youtube.com/watch?v=0jspaMLxBig (57:00)

It’s easy to get discouraged doing a whole slew of courses, but Andrew Ng lays it out perfectly:

Education

I often say that pre-AGI education is useful. Post-AGI education is fun. In a similar way, people go to the gym today. We don’t need their physical strength to manipulate heavy objects because we have machines that do that. They still go to the gym. Why do they go to the gym? Because it’s fun, it’s healthy, and you look hot when you have a six-pack. It’s attractive for people to do that in a very deep, psychological, evolutionary sense for humanity. Education will play out in the same way. You’ll go to school like you go to the gym. – Andrej Karpathy

https://www.youtube.com/watch?v=lXUZvyajciY (2:08:34)

I treat learning like going to the gym and exercise. Why do people go to the gym still? We have machines that do heavy lifting for us today.

This curriculum really made me consider the future of education. Especially in a world of AI tools that help students research and reason about new topics.

For Those Thinking About Taking OSSU

It’s not merely for career training or professional development. It’s for those who want a proper, well-rounded grounding in concepts fundamental to all computing disciplines, and for those who have the discipline, will, and (most importantly!) good habits to obtain this education largely on their own, but with support from a worldwide community of fellow learners.

It’s sort of redundant, but it’s true. Don’t go into this with the expectation of becoming certified or progressing your career. It’s so much more than that.

Go into it with the intention of learning and reasoning about computer science from first principles.

It’s about building a habit to learn, and discovering how you as an individual can learn effectively.

On a more practical note, if you’re rougher on math than programming like I was, Discrete Mathematics for Computer Science helped me immensely.

What’s Next

I’m burned out with courses, especially after a full year of back-to-back courses every weekend. I’m going to spend a good chunk of time working on a backlog of projects I’ve been accumulating over this period.

When I’m ready to get back into it, I plan to pick back up with these courses: Deep Learning and Neural Networks: Zero to Hero.

I’d also like to revisit Discrete Mathematics for Computer Science and more algorithms.

My schedule will likely consist of reading and courses during the week (after work), and weekends dedicated to projects.