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.
103credentials
5online degrees
381courses

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Explore the Deep Learning Course Catalog

  • Status: Preview

    University of Illinois Urbana-Champaign

    Skills you'll gain: Generative AI, Deep Learning, Responsible AI, Artificial Intelligence, Machine Learning, Unsupervised Learning, Artificial Neural Networks, AI Product Strategy, Regression Analysis, Business Ethics, Computer Vision, Governance

  • Status: Free Trial

    Skills you'll gain: Large Language Modeling, Generative AI, Data Pipelines, PyTorch (Machine Learning Library), Natural Language Processing, Text Mining, Prompt Engineering, Artificial Intelligence, Deep Learning, Data Processing

  • Skills you'll gain: Tensorflow, Applied Machine Learning, Python Programming, Jupyter, Artificial Neural Networks, Deep Learning, Computer Vision, Machine Learning

  • Status: Free Trial

    Skills you'll gain: Tensorflow, Deep Learning, Keras (Neural Network Library), Distributed Computing, Performance Tuning, NumPy

  • Status: Free Trial

    Skills you'll gain: Deep Learning, Artificial Neural Networks, Image Analysis, Keras (Neural Network Library), Applied Machine Learning, Tensorflow, Computer Vision, Natural Language Processing, Network Architecture, Medical Imaging

  • Status: Preview

    UNSW Sydney (The University of New South Wales)

    Skills you'll gain: Image Analysis, Unsupervised Learning, Geospatial Information and Technology, Computer Vision, Spatial Analysis, Machine Learning, Dimensionality Reduction, Linear Algebra, Deep Learning, Data Validation, Supervised Learning, Probability & Statistics, Artificial Neural Networks

  • Status: Free Trial

    Skills you'll gain: Natural Language Processing, Large Language Modeling, Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Deep Learning, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Cloud API, Feature Engineering

  • Skills you'll gain: Time Series Analysis and Forecasting, Deep Learning, Statistical Analysis, Predictive Modeling, Statistical Methods, Forecasting, Jupyter, Data Cleansing, Applied Machine Learning, Data Transformation, Exploratory Data Analysis, Pandas (Python Package), Unsupervised Learning, Dimensionality Reduction

  • Status: Free Trial

    Skills you'll gain: Reinforcement Learning, Google Cloud Platform, AI Personalization, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Machine Learning Algorithms, Deep Learning, Applied Machine Learning, Artificial Neural Networks, Predictive Modeling, Algorithms, Data Processing

  • Status: Free Trial

    Skills you'll gain: Data Ethics, Applied Machine Learning, Unsupervised Learning, Random Forest Algorithm, Data Analysis, Regression Analysis, Responsible AI, Decision Tree Learning, Machine Learning Algorithms, Data Collection, Deep Learning, Workflow Management, MLOps (Machine Learning Operations), Statistical Analysis, Business Ethics, Compliance Management, Learning Strategies, Test Planning, Goal Setting, Productivity

  • Skills you'll gain: Keras (Neural Network Library), Artificial Neural Networks, Applied Machine Learning, Deep Learning, Python Programming, Performance Tuning, Machine Learning Algorithms, Machine Learning

  • Status: Free Trial

    Skills you'll gain: Dimensionality Reduction, Unsupervised Learning, Deep Learning, Machine Learning Algorithms, Random Forest Algorithm, Feature Engineering, Artificial Neural Networks, Supervised Learning, Statistical Machine Learning, Anomaly Detection, Machine Learning, Classification And Regression Tree (CART)