Description
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...
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.
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.
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.
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?
Syllabus
First Year
- Fundamentals of Biology
- Principles of Chemical Science
- Python for Everybody
- Introduction to Computer Science and Programming using Python (alt)
- College Algebra and Problem Solving
- Pre-calculus
- Calculus 1A: Differentiation
- Calculus 1B: Integration
- Introduction to Probability and Data (with R)
Second Year
- Biochemistry
- Organic Chemistry
- CS 2 - Object Oriented Java
- Calculus 1C: Coordinate Systems & Infinite Series
- Mathematics for Computer Science (Solutions)
- Databases
- Linear Algebra and Essence of Linear Algebra
- Introduction to Linux
- Inferential Statistics (with R)
Third Year
- Proteins' Biology
- Algorithmic Thinking 1
- Algorithmic Thinking 2
- Linear Regression and Modeling (with R)
- Bayesian Statistics (with R)
- Cell Biology
- Differential Equations
- Biostatistics 1
- Biostatistics 2
Fourth Year
- DNA: Biology's Genetic Code
- Data Science
- Molecular Biology
- Bioinformatics 1
- Bioinformatics 2
- Bioinformatics 3
- Bioinformatics 4
- Bioinformatics 5
- Bioinformatics 6
- Bioinformatics 7 (Capstone)
- Evolution
Extra Year
Roadmaps 
Independent
Free 
Paid Certificate 
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TypeRoadmaps
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ProviderIndependent
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PricingFree
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CertificatePaid Certificate
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...
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.
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.
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.
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?
First Year
- Fundamentals of Biology
- Principles of Chemical Science
- Python for Everybody
- Introduction to Computer Science and Programming using Python (alt)
- College Algebra and Problem Solving
- Pre-calculus
- Calculus 1A: Differentiation
- Calculus 1B: Integration
- Introduction to Probability and Data (with R)
Second Year
- Biochemistry
- Organic Chemistry
- CS 2 - Object Oriented Java
- Calculus 1C: Coordinate Systems & Infinite Series
- Mathematics for Computer Science (Solutions)
- Databases
- Linear Algebra and Essence of Linear Algebra
- Introduction to Linux
- Inferential Statistics (with R)
Third Year
- Proteins' Biology
- Algorithmic Thinking 1
- Algorithmic Thinking 2
- Linear Regression and Modeling (with R)
- Bayesian Statistics (with R)
- Cell Biology
- Differential Equations
- Biostatistics 1
- Biostatistics 2
Fourth Year
- DNA: Biology's Genetic Code
- Data Science
- Molecular Biology
- Bioinformatics 1
- Bioinformatics 2
- Bioinformatics 3
- Bioinformatics 4
- Bioinformatics 5
- Bioinformatics 6
- Bioinformatics 7 (Capstone)
- Evolution
