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.
102credentials
6online degrees
378courses

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Explore the Deep Learning Course Catalog

  • Status: Preview

    Skills you'll gain: Image Analysis, Generative AI, Deep Learning, Computer Vision, Applied Machine Learning

  • Status: Preview

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

  • Status: New

    Skills you'll gain: Generative AI, Responsible AI, Google Cloud Platform, Unstructured Data, Artificial Intelligence and Machine Learning (AI/ML), Artificial Intelligence, Data Ethics, Large Language Modeling, Deep Learning, Data-Driven Decision-Making, Machine Learning

  • Status: Preview

    Skills you'll gain: Image Analysis, Generative Model Architectures, Deep Learning, Computer Vision, Applied Machine Learning

  • Status: Preview

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Generative AI, Applied Machine Learning, Machine Learning Methods, Deep Learning, Natural Language Processing, Artificial Neural Networks

  • Status: Free Trial

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

  • Status: Free Trial

    Skills you'll gain: Generative AI, Image Analysis, Generative Model Architectures, Deep Learning, Applied Machine Learning, Computer Vision

  • Skills you'll gain: Tensorflow, Google Cloud Platform, Keras (Neural Network Library), Data Pipelines, Data Processing, Data Cleansing, Data Transformation, Deep Learning, Scalability, Application Deployment, Artificial Neural Networks, Machine Learning

  • University of Colorado Boulder

    Skills you'll gain: Unsupervised Learning, Data Mining, Supervised Learning, Deep Learning, Machine Learning Algorithms, Statistical Modeling, Applied Machine Learning, Anomaly Detection, Probability, Statistical Inference, Statistical Hypothesis Testing, Service Level, Dimensionality Reduction, Data Warehousing, Data Pipelines, Data Processing, Performance Testing, Bash (Scripting Language), Data Science, Statistical Methods

  • Skills you'll gain: Keras (Neural Network Library), Tensorflow, Generative Model Architectures, Deep Learning, Natural Language Processing, Machine Learning Methods

  • Illinois Institute of Technology

    Skills you'll gain: Database Design, Statistical Analysis, Time Series Analysis and Forecasting, Relational Databases, Database Application, Database Management, Data Analysis, NoSQL, Database Systems, Database Theory, Machine Learning Algorithms, Databases, SQL, Big Data, Deep Learning, Bayesian Statistics, Statistical Inference, Technical Communication, Regression Analysis, Data Validation

  • Universidad de los Andes

    Skills you'll gain: Real-Time Operating Systems, Semantic Web, LangChain, Unsupervised Learning, Cloud-Native Computing, Continuous Deployment, Reinforcement Learning, Supervised Learning, Deep Learning, Cost Estimation, Computer Vision, MLOps (Machine Learning Operations), Biomedical Engineering, Artificial Intelligence, Natural Language Processing, Game Theory, Data Ethics, Linear Algebra, Machine Learning Methods, Prompt Engineering

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