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    • Pytorch

    PyTorch Courses Online

    Master PyTorch for deep learning. Learn to build and train neural networks using PyTorch for various AI applications.

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    Explore the PyTorch Course Catalog

    • G

      Google Cloud

      How Google does Machine Learning en Español

      Skills you'll gain: Google Cloud Platform, MLOps (Machine Learning Operations), Data Strategy, Machine Learning, Data Ethics, Cloud Computing, Tensorflow, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Management, Deep Learning

      4.6
      Rating, 4.6 out of 5 stars
      ·
      243 reviews

      Intermediate · Course · 1 - 3 Months

    • D

      DeepLearning.AI

      Convolutional Neural Networks

      Skills you'll gain: Computer Vision, Image Analysis, Deep Learning, Artificial Neural Networks, Tensorflow, Applied Machine Learning, PyTorch (Machine Learning Library), Artificial Intelligence, Data Processing, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      42K reviews

      Intermediate · Course · 1 - 4 Weeks

    • M

      MathWorks

      MathWorks Computer Vision Engineer

      Skills you'll gain: Computer Vision, Image Analysis, Anomaly Detection, Deep Learning, Applied Machine Learning, Artificial Neural Networks, Matlab, Application Deployment, PyTorch (Machine Learning Library), Machine Learning, Motion Graphics, Data Visualization, Automation, Data Mapping, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning Methods, Spatial Data Analysis, Predictive Modeling, Visualization (Computer Graphics), Data Synthesis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      300 reviews

      Beginner · Professional Certificate · 3 - 6 Months

    • D

      DeepLearning.AI

      Build Basic Generative Adversarial Networks (GANs)

      Skills you'll gain: Generative AI, PyTorch (Machine Learning Library), Image Analysis, Deep Learning, Artificial Neural Networks, Applied Machine Learning, Data Ethics, Computer Vision, Artificial Intelligence, Unsupervised Learning

      4.7
      Rating, 4.7 out of 5 stars
      ·
      2K reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Custom and Distributed Training with TensorFlow

      Skills you'll gain: Tensorflow, Deep Learning, Distributed Computing, Performance Tuning, Machine Learning Methods

      4.8
      Rating, 4.8 out of 5 stars
      ·
      433 reviews

      Intermediate · Course · 1 - 4 Weeks

    • M

      Microsoft

      Create Machine Learning Models in Microsoft Azure

      Skills you'll gain: Unsupervised Learning, Scikit Learn (Machine Learning Library), PyTorch (Machine Learning Library), Exploratory Data Analysis, Deep Learning, Microsoft Azure, Data Visualization, Applied Machine Learning, Regression Analysis, Predictive Modeling, Data Analysis, Image Analysis, Pandas (Python Package), Artificial Intelligence and Machine Learning (AI/ML), Data Science, MLOps (Machine Learning Operations), Machine Learning, Supervised Learning, Tensorflow, NumPy

      4.5
      Rating, 4.5 out of 5 stars
      ·
      292 reviews

      Intermediate · Course · 1 - 4 Weeks

    • D

      DeepLearning.AI

      Generative Deep Learning with TensorFlow

      Skills you'll gain: Generative AI, Tensorflow, Image Analysis, Deep Learning, Keras (Neural Network Library), Artificial Neural Networks, Computer Graphics, Unsupervised Learning

      4.9
      Rating, 4.9 out of 5 stars
      ·
      305 reviews

      Intermediate · Course · 1 - 4 Weeks

    • M

      Microsoft

      Perform data science with Azure Databricks

      Skills you'll gain: PySpark, Databricks, Apache Spark, MLOps (Machine Learning Operations), Microsoft Azure, Big Data, Scikit Learn (Machine Learning Library), Deep Learning, Data Transformation, Machine Learning, Distributed Computing, Feature Engineering, Exploratory Data Analysis

      3.2
      Rating, 3.2 out of 5 stars
      ·
      74 reviews

      Intermediate · Course · 1 - 3 Months

    • M

      Microsoft

      Foundations of AI and Machine Learning

      Skills you'll gain: Data Management, Artificial Intelligence and Machine Learning (AI/ML), Infrastructure Architecture, Cloud Infrastructure, MLOps (Machine Learning Operations), Application Deployment, Data Processing, Data Cleansing, Artificial Intelligence, Data Security, Application Frameworks, PyTorch (Machine Learning Library), Machine Learning, Tensorflow, Data Pipelines, Scikit Learn (Machine Learning Library), Scalability

      4.6
      Rating, 4.6 out of 5 stars
      ·
      101 reviews

      Intermediate · Course · 1 - 3 Months

    • S

      Stanford University

      Probabilistic Graphical Models

      Skills you'll gain: Bayesian Network, Applied Machine Learning, Graph Theory, Machine Learning Algorithms, Probability Distribution, Statistical Modeling, Bayesian Statistics, Markov Model, Decision Support Systems, Machine Learning, Probability & Statistics, Network Analysis, Statistical Inference, Sampling (Statistics), Statistical Methods, Natural Language Processing, Algorithms, Computational Thinking

      4.6
      Rating, 4.6 out of 5 stars
      ·
      1.5K reviews

      Advanced · Specialization · 3 - 6 Months

    • I

      IBM

      Building Generative AI-Powered Applications with Python

      Skills you'll gain: Generative AI, Large Language Modeling, Web Applications, IBM Cloud, Python Programming, OpenAI, Serverless Computing, Cloud Applications, Front-End Web Development, Prompt Engineering, Application Development, Flask (Web Framework), Artificial Intelligence, Natural Language Processing, Back-End Web Development

      4.7
      Rating, 4.7 out of 5 stars
      ·
      162 reviews

      Intermediate · Course · 1 - 3 Months

    • P

      Packt

      Building and Training Neural Networks with PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Artificial Neural Networks, Image Analysis, Deep Learning, Computer Vision, Classification And Regression Tree (CART), Predictive Modeling, Applied Machine Learning, Artificial Intelligence and Machine Learning (AI/ML), Data Processing, Algorithms

      4.9
      Rating, 4.9 out of 5 stars
      ·
      8 reviews

      Intermediate · Course · 1 - 3 Months

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    In summary, here are 10 of our most popular pytorch courses

    • How Google does Machine Learning en Español: Google Cloud
    • Convolutional Neural Networks: DeepLearning.AI
    • MathWorks Computer Vision Engineer: MathWorks
    • Build Basic Generative Adversarial Networks (GANs): DeepLearning.AI
    • Custom and Distributed Training with TensorFlow: DeepLearning.AI
    • Create Machine Learning Models in Microsoft Azure: Microsoft
    • Generative Deep Learning with TensorFlow: DeepLearning.AI
    • Perform data science with Azure Databricks: Microsoft
    • Foundations of AI and Machine Learning: Microsoft
    • Probabilistic Graphical Models: Stanford University

    Frequently Asked Questions about Pytorch

    PyTorch is a deep learning framework that doubles as a fast, flexible deep learning research platform. This Python package is based on Torch, an open-source Lua-based machine learning package. It delivers tensor computation similar to NumPy, but with more powerful GPU acceleration. It also speeds up the process from prototyping to production. It was first introduced in 2017 by the Facebook Artificial Intelligence Research team, and it's become popular among amateurs and professionals alike, largely because of its intuitive approach and easy-to-understand modular process that makes it easier to build and experiment with deep learning architectures.‎

    If you're passionate about deep learning and want simple-to-understand code, PyTorch is a good framework to learn. It works with Python instead of creating friction. Additionally, it's simple to get started using with a long list of optimizers and easy techniques for loading data. If you're interested in creating applications like natural language processing, computer vision, or anything in the AI field, PyTorch is a strong contender. Because it offers a simple interface and powerful API, plus the ability to implement it on Windows and Linux, PyTorch provides higher productivity for developers.‎

    If you're an aspiring machine learning engineer, data scientist, computer engineer, data analyst, or computational chemist, gaining a solid foundation in PyTorch puts you on the path to your chosen career. Researchers rely heavily on PyTorch, using it to create dynamic graphs, and it has steadily become the chosen framework featured at machine learning conferences. Learning about PyTorch and becoming proficient in using it is useful for a variety of career options. It's also essential for students and anyone dabbling in machine learning on their own.‎

    Online courses provide a mix of classroom learning and hands-on experience to give you a firm grasp of the fundamentals like linear regression, artificial neural networks, and data science, while also honing your skills. Taking online courses on Coursera exposes you to a mix of PyTorch subjects ranging from beginner-level courses and Guided Projects to Professional Certificate programs provided by industry leaders like IBM. By opting for online PyTorch classes, you have greater flexibility to go at your own pace, making it easier to fit your courses around your busy life.‎

    Online PyTorch courses offer a convenient and flexible way to enhance your knowledge or learn new PyTorch skills. Choose from a wide range of PyTorch courses offered by top universities and industry leaders tailored to various skill levels.‎

    When looking to enhance your workforce's skills in PyTorch, it's crucial to select a course that aligns with their current abilities and learning objectives. Our Skills Dashboard is an invaluable tool for identifying skill gaps and choosing the most appropriate course for effective upskilling. For a comprehensive understanding of how our courses can benefit your employees, explore the enterprise solutions we offer. Discover more about our tailored programs at Coursera for Business here.‎

    This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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