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    • Computational Biology

    Computational Biology Courses Online

    Explore computational biology for analyzing biological data. Learn to apply algorithms and models to study genomes, proteins, and biological systems.

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    Explore the Computational Biology Course Catalog

    • Placeholder
      U

      University of Colorado Boulder

      Engineering Genetic Circuits: Design

      Skills you'll gain: Electrical Engineering, Engineering Design Process, Bioinformatics, Life Sciences, Engineering, Engineering Analysis, Technical Design, Model Based Systems Engineering, Research Design, Scientific Methods, Experimentation, Design Strategies, Technical Standard

      Build toward a degree

      4.7
      Rating, 4.7 out of 5 stars
      ·
      26 reviews

      Beginner · Course · 1 - 3 Months

    • R

      Rice University

      An Introduction to Interactive Programming in Python (Part 2)

      Skills you'll gain: Application Development, Object Oriented Programming (OOP), Event-Driven Programming, Interactive Design, Program Development, Python Programming, Computer Programming, Computer Graphics, Data Structures

      4.9
      Rating, 4.9 out of 5 stars
      ·
      1.2K reviews

      Beginner · Course · 1 - 4 Weeks

    • U

      University of California, Davis

      Big Data, Artificial Intelligence, and Ethics

      Skills you'll gain: Data Ethics, Artificial Intelligence, Research, Natural Language Processing, Big Data, Research Methodologies, Social Sciences, Applied Machine Learning, Text Mining, Analytics, Machine Learning, Data Mining, Algorithms

      4.6
      Rating, 4.6 out of 5 stars
      ·
      587 reviews

      Beginner · Course · 1 - 4 Weeks

    • S

      Stanford University

      Graph Search, Shortest Paths, and Data Structures

      Skills you'll gain: Data Structures, Graph Theory, Algorithms, Network Analysis, Computational Thinking, Network Routing

      4.8
      Rating, 4.8 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free
      Free
      L

      Ludwig-Maximilians-Universität München (LMU)

      Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

      Skills you'll gain: Finite Element Methods, Numerical Analysis, Engineering Analysis, Jupyter, Differential Equations, Applied Mathematics, NumPy, Mathematical Modeling, Computational Thinking, Python Programming, Calculus, Mechanics, Vibrations, Linear Algebra, Simulations

      4.8
      Rating, 4.8 out of 5 stars
      ·
      384 reviews

      Intermediate · Course · 1 - 3 Months

    • U

      University of Colorado Boulder

      Foundations of Data Structures and Algorithms

      Skills you'll gain: Theoretical Computer Science, Algorithms, Graph Theory, Data Structures, Operations Research, Public Key Cryptography Standards (PKCS), Computational Logic, Cryptography, Computational Thinking, Pseudocode, Design Strategies, Combinatorics, Programming Principles, Computer Programming, Computer Science, Encryption, Network Model, Linear Algebra, Data Science, Mathematical Modeling

      Build toward a degree

      4.6
      Rating, 4.6 out of 5 stars
      ·
      748 reviews

      Advanced · Specialization · 3 - 6 Months

    • Placeholder
      U

      University of Toronto

      Plant Bioinformatics

      Skills you'll gain: Bioinformatics, Network Analysis, Data Visualization Software, Exploratory Data Analysis, Data Analysis, Databases

      4.8
      Rating, 4.8 out of 5 stars
      ·
      246 reviews

      Intermediate · Course · 1 - 3 Months

    • Placeholder
      Status: Free
      Free
      T

      The Pennsylvania State University

      Epidemics - the Dynamics of Infectious Diseases

      Skills you'll gain: Infectious Diseases, Epidemiology, Preventative Care, Health Care, Social Sciences, Medical Science and Research, Pharmaceuticals, Socioeconomics, Environmental Issue, Mathematical Modeling, Data Collection

      4.8
      Rating, 4.8 out of 5 stars
      ·
      1.7K reviews

      Mixed · Course · 1 - 3 Months

    • Placeholder
      K

      King Abdullah University of Science and Technology

      Fundamental Skills in Bioinformatics

      Skills you'll gain: Statistical Analysis, Bioinformatics, Unix, Scientific Visualization, Statistical Methods, R Programming, Rmarkdown, Unix Commands, Data Analysis, Data Quality, Statistical Hypothesis Testing, Exploratory Data Analysis, Programming Principles, Pandas (Python Package), Python Programming, NumPy, Data Manipulation, Computer Programming

      4.4
      Rating, 4.4 out of 5 stars
      ·
      59 reviews

      Beginner · Course · 1 - 4 Weeks

    • Placeholder
      U

      University of Michigan

      The Finite Element Method for Problems in Physics

      Skills you'll gain: Finite Element Methods, Engineering Analysis, Numerical Analysis, Mathematical Modeling, Advanced Mathematics, C++ (Programming Language), Object Oriented Programming (OOP)

      4.6
      Rating, 4.6 out of 5 stars
      ·
      551 reviews

      Intermediate · Course · 3 - 6 Months

    • Placeholder
      D

      Duke University

      The Brain and Space

      Skills you'll gain: Spatial Analysis, Human Learning, Image Analysis, Experimentation, Scientific Methods, Physics, Research

      4.7
      Rating, 4.7 out of 5 stars
      ·
      651 reviews

      Beginner · Course · 1 - 3 Months

    • Placeholder
      U

      University of California, Davis

      Computational Social Science Methods

      Skills you'll gain: Social Sciences, Network Analysis, Data Science, Machine Learning, Computational Thinking, Economics, Policy, and Social Studies, Artificial Intelligence, Data Analysis, Sociology, Data Mining, Simulations, Big Data, Scientific Methods

      4.7
      Rating, 4.7 out of 5 stars
      ·
      342 reviews

      Beginner · Course · 1 - 4 Weeks

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    In summary, here are 10 of our most popular computational biology courses

    • Engineering Genetic Circuits: Design: University of Colorado Boulder
    • An Introduction to Interactive Programming in Python (Part 2): Rice University
    • Big Data, Artificial Intelligence, and Ethics: University of California, Davis
    • Graph Search, Shortest Paths, and Data Structures: Stanford University
    • Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python: Ludwig-Maximilians-Universität München (LMU)
    • Foundations of Data Structures and Algorithms: University of Colorado Boulder
    • Plant Bioinformatics: University of Toronto
    • Epidemics - the Dynamics of Infectious Diseases: The Pennsylvania State University
    • Fundamental Skills in Bioinformatics: King Abdullah University of Science and Technology
    • The Finite Element Method for Problems in Physics: University of Michigan

    Skills you can learn in Algorithms

    Graphs (22)
    Mathematical Optimization (21)
    Computer Program (20)
    Data Structure (19)
    Problem Solving (19)
    Algebra (12)
    Computer Vision (10)
    Discrete Mathematics (10)
    Graph Theory (10)
    Image Processing (10)
    Linear Algebra (10)
    Reinforcement Learning (10)

    Frequently Asked Questions about Computational Biology

    Computational Biology is a multidisciplinary approach to applying data-scientific methods, processes, or theories to the study of biological systems. The field includes foundations in Mathematics, Statistics, Chemistry, Genetics, Genomics, Computer Science, Evolution, and related disciplines.

    An example of Computational Biology is performing experiments that produce data—building sequences of molecules, for instance—and then using methods such as machine learning to analyze the data.

    When mastered, Computational Biology enables successful learners to bring drug discovery and disease prevention expertise to Biotechnology, Pharmaceuticals, and other essential fields.‎

    As Data Science roles pertaining to Biology become increasingly in-demand, learners exploring Computational Biology can find opportunities in commercial, academic, and government domains. The positions learners can look forward to include Computer and Information Research Scientist, Computational Biology Professor, Software and Instrumentation Test Engineer, Bioinformatics Scientist, and related roles.

    Some industries in which Computational Biology learners will find exciting opportunities include Medical Device and Equipment, Research and Testing, Agricultural Chemicals, Pharmaceuticals, National Institutes of Health, and more.‎

    Courses in Computational Biology offered through Coursera explore various methods for extracting data from biological experiments. Learners discover how algorithms, data structures, and other computational methods can help them analyze DNA sequencing data. The basics in biological systems are covered so learners have a foundational understanding of DNA, genomics, and DNA sequencing. Hands-on learning of data science tools is available in many courses as well, where learners use Python, R Programming, and more to analyze real genomes and DNA sequencing datasets.‎

    Computational biology sits at the intersection of machine learning and life science, so if you possess skills in computer science and any of the various disciplines of biology, you’re ready to start learning computational biology. Having a working understanding of biology, pharmacology, and genetics can help you gain a foothold in learning computational biology, and the deeper your knowledge of those fields, the better off you’ll be in your studies. You can also benefit from a background in coding and computer programming, especially if you have experience using discrete mathematics for research and data analysis. An understanding of statistics can also give you an advantage in studying computational biology because you can apply the principles of statistics and data analysis to problem-solving within scientific disciplines.‎

    Since computational biology—also known as bioinformatics—is a scientific discipline that relies on the analysis of large amounts of data, people with analytical natures or backgrounds in statistics are well-suited for careers in this area. Individuals who are passionate about life science and want to apply technology to studying its various fields will enjoy jobs in computational biology. Computer programmers who have an interest in biology or genetics can combine their skills in building data structures with their passion for bioinformatics. Whether you want to work in academic research or for a medical corporation, you can put your scientific and computational knowledge to work in a career in computational biology.‎

    Computational biology might be the right field for you if you’re interested in biology and genetics beyond family trees and the insights from DNA test kits ordered online. If you have the desire to help develop the next revolutionary prescription or a passion to use data to help solve scientific issues, learning computational biology could be a good fit for you. You can take the skills in data analysis and computer programming that you learn studying computational biology to conduct research that helps lead to scientific breakthroughs. From pharmaceutical studies to academic research, learning computational biology offers rewarding opportunities for those who want to combine computer skills with scientific exploration.‎

    Online Computational Biology courses offer a convenient and flexible way to enhance your knowledge or learn new Computational Biology skills. Choose from a wide range of Computational Biology courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in Computational Biology, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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