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  • Computational Biology

Computational Biology Courses

Computational biology courses can help you learn genetic sequencing, protein structure prediction, and biological data analysis. You can build skills in algorithm development, statistical modeling, and data visualization techniques. Many courses introduce tools like Python, R, and bioinformatics software, that support analyzing complex biological datasets and simulating biological processes.


Popular Computational Biology Courses and Certifications


  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Genomic Data Science

    Skills you'll gain: Bioinformatics, Unix Commands, Biostatistics, Exploratory Data Analysis, Statistical Analysis, Unix, Data Science, Data Management, Statistical Methods, Command-Line Interface, Statistical Hypothesis Testing, Linux Commands, Data Analysis Software, Data Quality, Data Structures, Data Analysis, Computer Science, Molecular Biology, R Programming, Python Programming

    4.5
    Rating, 4.5 out of 5 stars
    ·
    6.8K reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    U

    University of California San Diego

    Biology Meets Programming: Bioinformatics for Beginners

    Skills you'll gain: Bioinformatics, Programming Principles, Molecular, Cellular, and Microbiology, Python Programming, Computational Thinking, Biology

    4.2
    Rating, 4.2 out of 5 stars
    ·
    1.6K reviews

    Beginner · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of California San Diego

    Bioinformatics

    Skills you'll gain: Bioinformatics, Molecular Biology, Dimensionality Reduction, Unsupervised Learning, Data Analysis, Markov Model, Network Analysis, Biochemistry, Biotechnology, Life Sciences, Infectious Diseases, Microbiology, Statistical Analysis, Biology, Algorithms, Data Preprocessing, Machine Learning, Data Analysis Software, Data Mapping, Python Programming

    4.3
    Rating, 4.3 out of 5 stars
    ·
    1.3K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    I

    Icahn School of Medicine at Mount Sinai

    Systems Biology and Biotechnology

    Skills you'll gain: Matlab, Bioinformatics, Quantitative Research, Unsupervised Learning, Data Synthesis, Research, Mathematical Modeling, Molecular Biology, Pharmacology, Science and Research, Cell Biology, Biotechnology, Biomedical Technology, Scientific Methods, Physiology, Differential Equations, Computational Logic, Biochemistry, Network Analysis, Biology

    4.4
    Rating, 4.4 out of 5 stars
    ·
    987 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Preview
    Preview
    U

    University of Washington

    Computational Neuroscience

    Skills you'll gain: Supervised Learning, Network Model, Matlab, Machine Learning Algorithms, Artificial Neural Networks, Neurology, Computer Science, Reinforcement Learning, Computational Thinking, Bioinformatics, Mathematical Modeling, Physiology, Recurrent Neural Networks (RNNs), Biology, Linear Algebra, Statistical Methods, Information Architecture, Differential Equations, Probability Distribution

    4.6
    Rating, 4.6 out of 5 stars
    ·
    1.1K reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Introduction to Genomic Technologies

    Skills you'll gain: Bioinformatics, Data Science, Molecular Biology, Data Analysis, Computer Science, Statistical Analysis, Computational Thinking, Biostatistics, Statistics, Software Engineering, Algorithms, Biology

    4.6
    Rating, 4.6 out of 5 stars
    ·
    4.8K reviews

    Mixed · Course · 1 - 4 Weeks

What brings you to Coursera today?

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Cancer Biology

    Skills you'll gain: Oncology, Medical Imaging, Patient Education And Counseling, Diagnostic Radiology, Radiation Therapy, Molecular Biology, Diagnostic Tests, Clinical Trials, Pain Management, Preventative Care, Treatment Planning, Urology, Patient Treatment, Immunology, Epidemiology, Surgery, Cell Biology, Care Management, Biology, Pathology

    4.8
    Rating, 4.8 out of 5 stars
    ·
    9.9K reviews

    Beginner · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    J

    Johns Hopkins University

    Python for Genomic Data Science

    Skills you'll gain: Bioinformatics, Data Structures, Jupyter, Python Programming, Programming Principles, Object Oriented Programming (OOP), File I/O, Computational Logic, Package and Software Management, Data Manipulation

    4.3
    Rating, 4.3 out of 5 stars
    ·
    1.8K reviews

    Mixed · Course · 1 - 4 Weeks

  • Status: Free Trial
    Free Trial
    U

    University of California San Diego

    Applied Bioinformatics

    Skills you'll gain: Bioinformatics, Diagnostic Tests, Model Evaluation, Molecular Biology, Infectious Diseases, Informatics, Network Analysis, Medical Science and Research, Computational Thinking, Biochemistry, Data Mining, Scientific Visualization, Life Sciences, Tree Maps, Microbiology, Biology, Data Analysis Software, Pharmacology, Science and Research

    4.4
    Rating, 4.4 out of 5 stars
    ·
    66 reviews

    Beginner · Specialization · 1 - 3 Months

  • Status: Preview
    Preview
    B

    Birla Institute of Technology & Science, Pilani

    Introduction to Bioinformatics

    Skills you'll gain: Bioinformatics, Biotechnology, Data Management, Biostatistics, Data Mining, Applied Machine Learning, Unsupervised Learning, R Programming, Scientific Visualization, Data Preprocessing, Correlation Analysis, Chemical and Biomedical Engineering, Dimensionality Reduction, Computational Thinking, Markov Model, Algorithms

    3.7
    Rating, 3.7 out of 5 stars
    ·
    6 reviews

    Beginner · Course · 1 - 3 Months

  • Status: Free Trial
    Free Trial
    U

    University of Colorado Boulder

    Engineering Genetic Circuits

    Skills you'll gain: Biological Engineering, Markov Model, Molecular Biology, Biotechnology, Bioinformatics, Simulation and Simulation Software, Mathematical Modeling, Engineering Analysis, Mathematical Software, Electrical Engineering, Engineering Design Process, Simulations, Biochemistry, Computational Thinking, Failure Analysis, Differential Equations, Cell Biology, Hazard Analysis, Technical Design, Chemical Engineering

    Build toward a degree

    4.5
    Rating, 4.5 out of 5 stars
    ·
    33 reviews

    Intermediate · Specialization · 3 - 6 Months

  • Status: Free Trial
    Free Trial
    U

    University of Toronto

    Bioinformatic Methods I

    Skills you'll gain: Biostatistics, Life Sciences, Data Analysis

    4.7
    Rating, 4.7 out of 5 stars
    ·
    1.8K reviews

    Beginner · Course · 1 - 3 Months

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

  • Genomic Data Science: Johns Hopkins University
  • Biology Meets Programming: Bioinformatics for Beginners: University of California San Diego
  • Bioinformatics: University of California San Diego
  • Systems Biology and Biotechnology: Icahn School of Medicine at Mount Sinai
  • Computational Neuroscience: University of Washington
  • Introduction to Genomic Technologies: Johns Hopkins University
  • Cancer Biology: Johns Hopkins University
  • Python for Genomic Data Science: Johns Hopkins University
  • Applied Bioinformatics: University of California San Diego
  • Introduction to Bioinformatics: Birla Institute of Technology & Science, Pilani

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 an interdisciplinary field that combines biology, computer science, and mathematics to analyze and interpret biological data. This area is crucial for advancing our understanding of complex biological systems, such as genetic sequences, protein structures, and ecological interactions. By leveraging computational techniques, researchers can make significant discoveries in areas like genomics, drug development, and personalized medicine, ultimately leading to improved health outcomes and innovative solutions to biological challenges.‎

Careers in computational biology are diverse and can be found in various sectors, including healthcare, pharmaceuticals, and academia. Some potential job titles include bioinformatics analyst, computational biologist, data scientist, and research scientist. These roles often involve analyzing large datasets, developing algorithms, and collaborating with biologists to interpret findings. As the demand for data-driven insights in biology continues to grow, opportunities in this field are expanding, making it an exciting career choice.‎

To succeed in computational biology, you will need a blend of skills from both biological sciences and computational methods. Key skills include programming languages such as Python or R, statistical analysis, data visualization, and an understanding of biological concepts. Familiarity with machine learning techniques and experience with databases can also be beneficial. Building a solid foundation in these areas will empower you to tackle complex biological questions and contribute to innovative research.‎

There are several excellent online courses available for those interested in computational biology. Notable options include the Introduction to Computational Statistics for Data Scientists Specialization, which covers essential statistical methods, and the Cancer Biology Specialization, focusing on the intersection of biology and computational techniques in cancer research. These courses provide valuable knowledge and skills that can enhance your understanding and capabilities in this field.‎

Yes. You can start learning computational biology on Coursera for free in two ways:

  1. Preview the first module of many computational biology courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in computational biology, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

To learn computational biology, start by identifying your current knowledge level and the specific areas you want to explore. Begin with foundational courses in biology and programming, then gradually progress to more specialized topics. Engage with online resources, participate in forums, and collaborate with peers to enhance your understanding. Practical experience through projects or internships can also be invaluable in applying what you've learned and gaining real-world insights.‎

Computational biology courses typically cover a range of topics, including bioinformatics, genomics, systems biology, and data analysis techniques. You may also encounter subjects like algorithm design, statistical modeling, and machine learning applications in biology. These topics equip learners with the knowledge needed to analyze biological data effectively and contribute to research and innovation in the field.‎

For training and upskilling employees in computational biology, courses like the Biology Everywhere Specialization can provide a comprehensive overview of biological concepts and their computational applications. Additionally, the Systems Biology and Biotechnology Specialization offers insights into the integration of biological data and computational methods, making it suitable for workforce development in this rapidly evolving field.‎

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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