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  • Computational Neuroscience

Computational Neuroscience Courses

Computational neuroscience courses can help you learn neural modeling, data analysis techniques, and the principles of brain connectivity. You can build skills in programming with Python, statistical analysis, and using machine learning algorithms to interpret neural data. Many courses introduce tools like MATLAB and TensorFlow, that support simulating neural networks and analyzing large datasets, enabling you to apply your knowledge in both research and practical applications.

Popular Computational Neuroscience Courses and Certifications


  • J

    Johns Hopkins University

    Principles of fMRI 2

    Skills you'll gain: Magnetic Resonance Imaging, Data Analysis, Correlation Analysis, Image Analysis, Statistical Analysis, Advanced Analytics, Network Analysis, Medical Imaging, Regression Analysis, Psychology, Time Series Analysis and Forecasting, Neurology, Statistical Modeling, Statistical Methods, Statistical Inference, Dimensionality Reduction, Model Evaluation

    4.7
    Rating, 4.7 out of 5 stars
    ·
    249 reviews

    Mixed · Course · 1 - 4 Weeks

  • J

    Johns Hopkins University

    Introduction to Neurohacking In R

    Skills you'll gain: Magnetic Resonance Imaging, Medical Imaging, Image Analysis, Data Manipulation, R (Software), Neurology, R Programming, Radiology, Image Quality, Data Processing, Scientific Visualization, Data Preprocessing, Data Transformation, Histogram, Data Import/Export, File Management, Package and Software Management, Software Installation

    4.6
    Rating, 4.6 out of 5 stars
    ·
    315 reviews

    Intermediate · Course · 1 - 4 Weeks

  • P

    Packt

    Foundations of Deep Learning and Neural Networks

    Skills you'll gain: Artificial Neural Networks, Deep Learning, Convolutional Neural Networks, Image Analysis, Keras (Neural Network Library), Model Training, Tensorflow, Network Architecture, Artificial Intelligence, Model Optimization, Machine Learning, Linear Algebra

    Intermediate · Course · 1 - 3 Months

  • E

    Edureka

    Neural Networks and Computer Vision Foundations

    Skills you'll gain: Computer Vision, Image Analysis, Model Evaluation, Convolutional Neural Networks, Model Optimization, Artificial Neural Networks, Model Training, Machine Learning Methods, PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Transfer Learning, Machine Learning, Recurrent Neural Networks (RNNs), Artificial Intelligence, NumPy, Python Programming, Matplotlib, Data Visualization, Data Science

    Beginner · Course · 1 - 4 Weeks

  • J

    Johns Hopkins University

    Advanced Neural Network Techniques

    Skills you'll gain: Autoencoders, Recurrent Neural Networks (RNNs), Deep Learning, Artificial Neural Networks, Reinforcement Learning, Generative AI, Generative Adversarial Networks (GANs), Generative Model Architectures, Unsupervised Learning, Responsible AI, Data Ethics, Markov Model

    4
    Rating, 4 out of 5 stars
    ·
    7 reviews

    Intermediate · Course · 1 - 3 Months

  • U

    University of Glasgow

    Evolutionary Computation and its Applications

    Skills you'll gain: Model Optimization, Applied Mathematics

    5
    Rating, 5 out of 5 stars
    ·
    32 reviews

    Beginner · Course · 1 - 4 Weeks

  • C

    Coursera

    Design and Build Custom Neural Networks

    Skills you'll gain: Network Architecture, Model Optimization, Artificial Neural Networks, Model Training, Performance Testing, Deep Learning, Vision Transformer (ViT)

    Intermediate · Course · 1 - 4 Weeks

  • J

    Johns Hopkins University

    Introduction to Neural Networks

    Skills you'll gain: Convolutional Neural Networks, Model Optimization, Artificial Neural Networks, Deep Learning, Machine Learning Algorithms, Machine Learning Methods, Model Training, Image Analysis, Machine Learning, Computer Vision, Model Evaluation, Algorithms

    4.2
    Rating, 4.2 out of 5 stars
    ·
    10 reviews

    Intermediate · Course · 1 - 3 Months

  • P

    Packt

    Foundations of Model Optimization and Deep Learning

    Skills you'll gain: Convolutional Neural Networks, Model Optimization, Model Evaluation, Keras (Neural Network Library), Image Analysis, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Computer Vision, Model Training, Dimensionality Reduction, PyTorch (Machine Learning Library), Tensorflow, Machine Learning Methods, Performance Tuning, Artificial Intelligence, Bayesian Statistics

    Intermediate · Course · 1 - 4 Weeks

  • U

    Universidad Austral

    Optimización de Redes Neuronales Profundas

    Skills you'll gain: Model Optimization, Tensorflow, Fine-tuning, Deep Learning, Performance Tuning, Model Training, Model Deployment, Artificial Neural Networks, Machine Learning Methods, Machine Learning Algorithms, Algorithms

    Intermediate · Course · 1 - 4 Weeks

  • S

    Simplilearn

    Deep Learning Frameworks and Neural Networks Simplified

    Skills you'll gain: Recurrent Neural Networks (RNNs), Model Deployment, Keras (Neural Network Library), Deep Learning, Tensorflow, Artificial Neural Networks, Convolutional Neural Networks, Application Frameworks, Model Training, Artificial Intelligence, Data Preprocessing

    Beginner · Course · 1 - 4 Weeks

  • D

    DeepLearning.AI

    Convolutional Neural Networks in TensorFlow

    Skills you'll gain: Convolutional Neural Networks, Transfer Learning, Model Evaluation, Tensorflow, Keras (Neural Network Library), Model Training, Computer Vision, Fine-tuning, Classification Algorithms, Image Analysis, Applied Machine Learning, Deep Learning, Model Optimization, Machine Learning, Data Preprocessing

    4.7
    Rating, 4.7 out of 5 stars
    ·
    8.2K reviews

    Intermediate · Course · 1 - 4 Weeks

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

  • Principles of fMRI 2: Johns Hopkins University
  • Introduction to Neurohacking In R: Johns Hopkins University
  • Foundations of Deep Learning and Neural Networks: Packt
  • Neural Networks and Computer Vision Foundations: Edureka
  • Advanced Neural Network Techniques: Johns Hopkins University
  • Evolutionary Computation and its Applications: University of Glasgow
  • Design and Build Custom Neural Networks: Coursera
  • Introduction to Neural Networks: Johns Hopkins University
  • Foundations of Model Optimization and Deep Learning: Packt
  • Optimización de Redes Neuronales Profundas: Universidad Austral

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