Artificial Neural Networks

Artificial Neural Networks (ANN) are computing systems inspired by biological neural networks that are the backbone of artificial intelligence (AI) and machine learning. Coursera's ANN skill catalogue teaches you the fundamentals and applications of these complex systems. You'll learn about the architecture of ANN, including layers, nodes, activation functions, and backpropagation. You'll understand how to train ANN for tasks such as pattern recognition, prediction, and decision making. Further, you will explore various types of neural networks like Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Deep Neural Networks (DNN). This knowledge will equip you to develop cutting-edge AI applications in various fields such as computer vision, natural language processing, and robotics.
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Explore the Neural Networks Course Catalog

  • Status: Preview

    Skills you'll gain: Computer Vision, Keras (Neural Network Library), Image Analysis, Deep Learning, Artificial Neural Networks, Tensorflow, Dimensionality Reduction, Visualization (Computer Graphics), Applied Machine Learning, Network Architecture, Algorithms

  • Status: Preview

    Skills you'll gain: Deep Learning, Supervised Learning, Artificial Neural Networks, Artificial Intelligence, Computer Vision, Machine Learning, Performance Tuning, Machine Learning Algorithms, Python Programming, NumPy, Linear Algebra, Algorithms

  • Status: Free Trial

    Skills you'll gain: Random Forest Algorithm, Decision Tree Learning, Deep Learning, Applied Machine Learning, Artificial Neural Networks, Machine Learning Algorithms, Supervised Learning, Computer Vision, Regression Analysis, Natural Language Processing

  • Status: Preview

    Skills you'll gain: Deep Learning, Natural Language Processing, Tensorflow, PyTorch (Machine Learning Library), Generative Model Architectures, Applied Machine Learning, Artificial Neural Networks

  • Skills you'll gain: Keras (Neural Network Library), Tensorflow, Image Analysis, Artificial Neural Networks, Deep Learning, Machine Learning Methods, Computer Vision, Machine Learning

  • Status: Preview

    Skills you'll gain: Deep Learning, Natural Language Processing, Tensorflow, PyTorch (Machine Learning Library), Artificial Neural Networks, Applied Machine Learning, Machine Learning Methods, Time Series Analysis and Forecasting, Algorithms

  • Status: Preview

    Skills you'll gain: Deep Learning, Artificial Neural Networks, Artificial Intelligence, NumPy, Computer Vision, Machine Learning, Supervised Learning, Linear Algebra, Calculus

  • Skills you'll gain: Deep Learning, Data Processing, Artificial Neural Networks, Feature Engineering, Python Programming, Network Architecture, Machine Learning Algorithms, NumPy, Pandas (Python Package), Regression Analysis, Supervised Learning, Performance Tuning

  • Status: Free Trial

    Illinois Tech

    Skills you'll gain: Deep Learning, Generative AI, Image Analysis, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), PyTorch (Machine Learning Library), Network Architecture, Tensorflow, Computer Vision, Natural Language Processing, Machine Learning, Performance Tuning

  • Skills you'll gain: Artificial Neural Networks, Data Visualization, Exploratory Data Analysis, Data Presentation, Applied Machine Learning, Machine Learning Methods, Predictive Modeling, Deep Learning, Classification And Regression Tree (CART), Data Analysis, Predictive Analytics, Machine Learning Algorithms, Machine Learning, Statistical Analysis, Feature Engineering, Python Programming

  • Skills you'll gain: Tensorflow, Data Collection, Image Analysis, Artificial Neural Networks, Deep Learning, Computer Vision, Google Cloud Platform, Cloud Computing, Scientific Visualization

  • Status: New
    Status: Free Trial

    Skills you'll gain: Large Language Modeling, Natural Language Processing, PyTorch (Machine Learning Library), Artificial Neural Networks, Tensorflow, Artificial Intelligence and Machine Learning (AI/ML), Deep Learning, Machine Learning