Skip to content
Switch branches/tags


Failed to load latest commit information.
Latest commit message
Commit time
Aug 8, 2021
Aug 14, 2017

Open Source Society logo

Open Source Society University

🔬 Path to a free self-taught education in Bioinformatics!

Open Source Society University - Bioinformatics



This is a solid path for those of you who want to complete a Bioinformatics course on your own time, for free, with courses from the best universities in the World.

In our curriculum, we give preference to MOOC (Massive Open Online Course) style courses because these courses were created with our style of learning in mind.

To become a bioinformatician, you have to learn quite a lot of science, so be ready for subjects like; Biology, Chemistry, etc...

Motivation & Preparation

Here are two interesting links that can make all the difference in your journey.

The first one is a motivational video that shows a guy that went through the "MIT Challenge", which consists of learning the entire 4-year MIT curriculum for Computer Science in 1 year.

The second link is a MOOC that will teach you learning techniques used by experts in art, music, literature, math, science, sports, and many other disciplines. These are fundamental abilities to succeed in our journey.

Are you ready to get started?


1st Year

Code Course Duration Effort
BIO 1311 Introduction to Biology 12 weeks 7-14 Hours/Week
CHEM 1311 Principles of Chemistry 15 Weeks 4-6 Hours/Week
COMP 1311a CS 1 - Python 1 5 Weeks 6 Hours/Week
COMP 1311b CS 1 - Python 2 4 Weeks 6 Hours/Week
COMP 1311c CS 1 - Principles of Computing 1 4 Weeks 6 Hours/Week
COMP 1311d CS 1 - Principles of Computing 2 4 Weeks 6 Hours/Week
MATH 1311 College Algebra and Problem Solving 4 Weeks 6 Hours/Week
MATH 1312 Pre-calculus 4 Weeks 6 Hours/Week
MATH 1313 Calculus 1 - Functions 3 Weeks 8 Hours/Week
MATH 1314 Calculus 2 - Differentiation 3 Weeks 8 Hours/Week
MATH 1315 Introduction to Probability and Data (with R) 5 Weeks 6 Hours/Week

2nd Year

Code Course Duration Effort
BIO 2311 Biochemistry 15 Weeks 4-6 Hours/Week
CHEM 2311 Organic Chemistry 15 Weeks 4-6 Hours/Week
COMP 2311 CS 2 - Object Oriented Java 6 Weeks 4-6 Hours/Week
MATH 2311 Calculus 3 - Integration 4 Weeks 8 Hours/Week
MATH 2312 Mathematics for CS 13 Weeks 6 Hours/Week
COMP 2312 Introduction to Databases 10 Weeks 8-12 Hours/Week
MATH 2313 Linear Algebra 15 Weeks 8 Hours/Week
COMP 2313 Introduction to Linux 8 Weeks 5-7 Hours/Week
MATH 2314 Inferential Statistics (with R) 5 Weeks 6 Hours/Week

3rd Year

Code Course Duration Effort
BIO 3311 Proteins' Biology 5 Weeks 4-6 Hours/Week
COMP 3311a Algorithmic Thinking 1 4 Weeks 6 Hours/Week
COMP 3311b Algorithmic Thinking 2 4 Weeks 6 Hours/Week
MATH 3311 Linear Regression and Modeling (with R) 4 Weeks 6 Hours/Week
MATH 3312 Bayesian Statistics (with R) 5 Weeks 6 Hours/Week
BIO 3312 Cell Biology - Weeks - Hours/Week
MATH 3313 Differential Equations 7 Weeks 8-10 Hours/Week
BIO 3313a Biostatistics 1 4 Weeks 3-5 Hours/Week
BIO 3313b Biostatistics 2 4 Weeks 3-5 Hours/Week

4th Year

Code Course Duration Effort
BIO 4311 DNA: Biology's Genetic Code 6 Weeks 4-6 Hours/Week
COMP 4311 Data Science 13 Week 10 Hours/Week
BIO 4312a Molecular Biology 16 Weeks 4-8 Hours/Week
BIO 4312d Bioinformatics 1 4 Weeks 4-10 Hours/Week
COMP 4312a Bioinformatics 2 4 Week 6 Hours/Week
COMP 4312b Bioinformatics 3 4 Week 6 Hours/Week
COMP 4312c Bioinformatics 4 4 Week 6 Hours/Week
COMP 4312d Bioinformatics 5 4 Week 6 Hours/Week
COMP 4312e Bioinformatics 6 4 Week 6 Hours/Week
COMP 4312f Bioinformatics 7 (Capstone) 3 Week 3-4 Hours/Week
BIO 4313 Evolution 11 Weeks 4-6 Hours/Week

Extra Year

Code Course Duration Effort
COMP 5311 Introduction to Machine Learning 10 Weeks 6 Hours/Week
COMP 5312 Deep Learning 8 Weeks 6 Hours/Week
Extension Genomic Data Science Specialization 32 Week 6 Hours/Week

Will continue with Master's in Bioinformatics

keep learning

How to use this guide

Order of the classes

This guide was developed to be consumed in a linear approach. What does this mean? That you should complete one course at a time.

The courses are already in the order that you should complete them. Just start the first course, Introduction to Biology, when you done with it, start the next one.

If the course is not open, do it with the archived resources or wait until next class is open.

How to track and show your progress

  1. Create an account in Trello.
  2. Copy this board to your personal account. See how to copy a board here.

Now that you have a copy of our official board, you just need to pass the cards to the Doing column or Done column as you progress in your study.

We also have labels to help you have more control through the process. The meaning of each of these labels is:

  • Main Curriculum: cards with that label represent courses that are listed in our curriculum.
  • Extra Courses: cards with that label represent courses that was added by the student.
  • Doing: cards with that label represent courses the student is current doing.
  • Done: cards with that label represent courses finished by the student. Those cards should also have the link for at least one project/article built with the knowledge acquired in such course.
  • Section: cards with that label represent the section that we have in our curriculum. Those cards with the Section label are only to help the organization of the Done column. You should put the Course's cards below its respective Section's card.
  • Extra Sections: cards with that label represent sections that was added by the student.

The intention of this board is to provide for our students a way to track their progress, and also the ability to show their progress through a public page for friends, family, employers, etc. You can change the status of your board to be public or private.

Should I take all courses?

Yes! The intention is to conclude all the courses listed here! Also we highly encourage you to complete more by reading papers and attending research projects after your coursework is done.

Duration of the course

It may take longer to complete all of the classes compared to a regular Bioinformatics course, but we can guarantee you that your reward will be proportional to your motivation/dedication!

You must focus on your habit, and forget about goals. Try to invest 1 ~ 2 hours every day studying this curriculum. If you do this, inevitably you'll finish this curriculum.

See more about "Commit to a process, not a goal" here.

Project Based

Here in OSS University, you do not need to take exams, because we are focused on real projects!

In order to show for everyone that you successfully finished a course, you should create a real project or write papers and publish them about your focus with Bioinformatics.

"What does it mean?"

After finish a course, you should think about a real world problem that you can solve using the acquired knowledge in the course. You don't need to create a big project, but you must create something to validate and consolidate your knowledge, and also to show to the world that you are capable to create something useful with the concepts that you learned.

Put the OSSU-Bioinformatics badge in the README of your repository! Open Source Society University - Bioinformatics

  • Markdown: [![Open Source Society University - Bioinformatics ](](
  • HTML: <a href=""><img alt="Open Source Society University - Bioinformatics" src=""></a>

You can create this project alone or with other students!

Be creative!

This is a crucial part of your journey through all those courses.

You need to have in mind that what you are able to create with the concepts that you learned will be your certificate and this is what really matters!

In order to show that you really learned those things, you need to be creative!

Here are some tips about how you can do that:

  • Articles: create blog posts to synthesize/summarize what you learned.
  • GitHub repository: keep your course's files organized in a GH repository, so in that way other students can use it to study with your annotations.

Cooperative work

We love cooperative work! Use our channels to communicate with other fellows to combine and create new projects!

Which programming languages should I use?

List of skills:

  • C/C++
  • Unix System
  • Python/Perl
  • R
  • Algorithms

These skills mentioned above are the very essential tool set that bioinformatician and computational biologist depends on.

The important thing for each course is to internalize the core concepts and to be able to use them with whatever tool (programming language) that you wish.

Content Policy

You must share only files that you are allowed to! Do NOT disrespect the code of conduct that you signed in the beginning of some courses.

Be creative in order to show your progress! 😄

Stay tuned

Watch this repository for futures improvements and general information.


The only things that you need to know are how to use Git and GitHub. Here are some resources to learn about them:

Note: Just pick one of the courses below to learn the basics. You will learn a lot more once you get started!

How to collaborate

You can open an issue and give us your suggestions as to how we can improve this guide, or what we can do to improve the learning experience.

You can also fork this project and send a pull request to fix any mistakes that you have found.

TODO: If you want to suggest a new resource, send a pull request adding such resource to the extras section.

The extras section is a place where all of us will be able to submit interesting additional articles, books, courses and specializations, keeping our curriculum as immutable and concise as possible.

Let's do it together! =)

Code of conduct

OSSU's code of conduct.


We have a Discord server! This should be your first stop to talk with other OSSU students. Why don't you introduce yourself right now?

Subscribe to our newsletter

You can also interact through GitHub issues.

Add Open Source Society University to your Linkedin and join our Facebook group!




🔬 Path to a free self-taught education in Bioinformatics!



No releases published


No packages published