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    • Computational Neuroscience

    Computational Neuroscience Courses Online

    Study computational neuroscience for modeling brain function. Learn to use computational methods to understand neural networks and brain activity.

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    Explore the Computational Neuroscience Course Catalog

    • Status: Preview
      Preview
      S

      Scrimba

      JavaScript Interview Questions for Junior Developers

      Skills you'll gain: Data Validation, Maintainability, Javascript, Computational Thinking, Data Structures, Debugging, Data Integrity, Performance Tuning, Software Technical Review, Web Development, Algorithms

      Intermediate · Course · 1 - 4 Weeks

    • Status: Preview
      Preview
      B

      Ball State University

      Statistical Methods for Data Science

      Skills you'll gain: Statistical Methods, Probability, Data Science, Probability & Statistics, Statistical Analysis, Probability Distribution, Statistical Modeling, Bayesian Statistics, Statistical Inference, Sampling (Statistics), R Programming, Statistical Visualization

      Build toward a degree

      Intermediate · Course · 1 - 3 Months

    • P

      Packt

      Mastering Image Segmentation with PyTorch

      Skills you'll gain: Image Analysis, Applied Machine Learning, Deep Learning, Computer Vision, Artificial Neural Networks, Machine Learning Methods, Data Processing, Performance Tuning, Regression Analysis

      Beginner · Course · 1 - 4 Weeks

    • Status: Preview
      Preview
      S

      Siemens

      응용 전산 유체 역학

      Skills you'll gain: Engineering Analysis, Thermal Management, Simulations, Mechanical Engineering, Hydraulics, Numerical Analysis, Engineering, Mathematical Modeling, Chemical Engineering

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      U

      University of Michigan

      Python Debugging Capstone Project: Fixing and Extending Code

      Skills you'll gain: Data Manipulation, Data Analysis, Python Programming

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Foundations of Neural Networks

      Skills you'll gain: Responsible AI, Data Ethics, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Reinforcement Learning, Generative AI, Debugging, Artificial Intelligence, Unsupervised Learning, Machine Learning, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Applied Machine Learning, Bayesian Statistics, Network Architecture, Linear Algebra, Markov Model

      4
      Rating, 4 out of 5 stars
      ·
      6 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Principles of fMRI 1

      Skills you'll gain: Magnetic Resonance Imaging, Medical Imaging, Radiology, Data Analysis, Research Design, Image Analysis, Neurology, Statistical Analysis, Statistical Modeling, Data Processing, Statistics

      4.6
      Rating, 4.6 out of 5 stars
      ·
      844 reviews

      Beginner · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Principles of fMRI 2

      Skills you'll gain: Magnetic Resonance Imaging, Data Analysis, Correlation Analysis, Analytical Skills, Image Analysis, Statistical Analysis, Advanced Analytics, Network Analysis, Medical Imaging, Regression Analysis, Psychology, Time Series Analysis and Forecasting, Matlab, Neurology, Statistical Modeling, Statistical Methods, Statistical Inference, Design Strategies, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      248 reviews

      Mixed · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Introduction to Neurohacking In R

      Skills you'll gain: Magnetic Resonance Imaging, Medical Imaging, Image Analysis, Data Manipulation, Neurology, R Programming, Radiology, Data Processing, Scientific Visualization, Data Import/Export

      4.6
      Rating, 4.6 out of 5 stars
      ·
      313 reviews

      Intermediate · Course · 1 - 4 Weeks

    • Status: Free Trial
      Free Trial
      P

      Packt

      Foundations of Deep Learning and Neural Networks

      Skills you'll gain: Artificial Neural Networks, Deep Learning, Image Analysis, Keras (Neural Network Library), Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Computer Vision, Artificial Intelligence, Machine Learning, Linear Algebra

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Advanced Neural Network Techniques

      Skills you'll gain: Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Unsupervised Learning, Machine Learning Methods, Data Ethics, Artificial Intelligence, Markov Model, Natural Language Processing

      Intermediate · Course · 1 - 3 Months

    • Status: Free Trial
      Free Trial
      J

      Johns Hopkins University

      Introduction to Neural Networks

      Skills you'll gain: Artificial Neural Networks, Machine Learning Algorithms, Deep Learning, Computer Vision, Image Analysis, Artificial Intelligence and Machine Learning (AI/ML), Applied Machine Learning, Machine Learning, Network Architecture, Linear Algebra, Performance Tuning, Probability & Statistics

      Intermediate · Course · 1 - 3 Months

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

    • JavaScript Interview Questions for Junior Developers: Scrimba
    • Statistical Methods for Data Science: Ball State University
    • Mastering Image Segmentation with PyTorch: Packt
    • 응용 전산 유체 역학: Siemens
    • Python Debugging Capstone Project: Fixing and Extending Code: University of Michigan
    • Foundations of Neural Networks: Johns Hopkins University
    • Principles of fMRI 1: Johns Hopkins University
    • Principles of fMRI 2: Johns Hopkins University
    • Introduction to Neurohacking In R: Johns Hopkins University
    • Foundations of Deep Learning and Neural Networks: Packt

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