Deep Learning

Deep Learning is a subset of machine learning that uses artificial neural networks with multiple layers - also known as deep neural networks - to model and understand complex patterns and relationships in datasets. Coursera's deep learning catalogue teaches you the underlying principles and methods of deep learning. You'll learn how to build and deploy deep neural networks, utilise various techniques for training and optimising deep learning models, and understand their applications across various industries including healthcare, finance, and autonomous vehicles. You'll further grasp the concepts of Convolutional Networks, Recurrent Networks, and Generative Adversarial Networks, preparing you for various roles in the field of AI and data science.
86credentials
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379courses

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Explore the Deep Learning Course Catalog

  • Status: New
    Status: Free Trial

    Skills you'll gain: Deep Learning, PyTorch (Machine Learning Library), Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Tensorflow, Large Language Modeling, Machine Learning, Python Programming, Algorithms, Network Architecture, Data Processing

  • Status: Free Trial

    University of Illinois Urbana-Champaign

    Skills you'll gain: Deep Learning, Generative Model Architectures, Applied Machine Learning, Machine Learning Methods, Image Analysis, Graph Theory, Tensorflow, Artificial Neural Networks, PyTorch (Machine Learning Library), Health Informatics, Predictive Modeling, Unsupervised Learning, Natural Language Processing, Data Synthesis, Python Programming

  • Status: Free Trial

    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

  • Skills you'll gain: Exploratory Data Analysis, Regression Analysis, Predictive Modeling, Applied Machine Learning, Data Manipulation, Data Analysis, Random Forest Algorithm, Machine Learning, Decision Tree Learning, Machine Learning Algorithms, Data Visualization Software, Artificial Neural Networks, Deep Learning, Statistical Methods, Python Programming

  • Status: Free Trial

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

  • Status: Preview

    Skills you'll gain: PyTorch (Machine Learning Library), Machine Learning Methods, Reinforcement Learning, Deep Learning, Image Analysis, Applied Machine Learning, Natural Language Processing, Machine Learning, Artificial Neural Networks, Supervised Learning, Unsupervised Learning, Python Programming, Computer Vision, Medical Imaging

  • Status: Preview

    Skills you'll gain: Deep Learning, Generative Model Architectures, Image Analysis, Artificial Neural Networks, Artificial Intelligence and Machine Learning (AI/ML), Computer Vision, Network Architecture, Natural Language Processing, Machine Learning Algorithms, Time Series Analysis and Forecasting

  • Skills you'll gain: PyTorch (Machine Learning Library), Image Analysis, Computer Vision, Applied Machine Learning, Deep Learning

  • Skills you'll gain: Text Mining, Data Cleansing, PyTorch (Machine Learning Library), Data Manipulation, Data Processing, Performance Tuning, Deep Learning, Natural Language Processing, Machine Learning

  • Skills you'll gain: Exploratory Data Analysis, Deep Learning, Plot (Graphics), Artificial Neural Networks, Matplotlib, Data Cleansing, Data Analysis, Tensorflow, Natural Language Processing, Data Processing, Data Manipulation, Python Programming, Machine Learning

  • Coursera Project Network

    Skills you'll gain: PyTorch (Machine Learning Library), Heat Maps, Image Analysis, Deep Learning, Artificial Neural Networks, Computer Vision

  • Status: Free Trial

    Skills you'll gain: Tensorflow, Generative Model Architectures, Deep Learning, Image Analysis, Bayesian Statistics, Artificial Neural Networks, Machine Learning, Unsupervised Learning, Probability & Statistics, Dimensionality Reduction