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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

    • C

      Coursera Project Network

      Detecting COVID-19 with Chest X-Ray using PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Image Analysis, Deep Learning, Artificial Neural Networks, Machine Learning Methods, Medical Imaging, Computer Vision, X-Ray Computed Tomography

      4.5
      Rating, 4.5 out of 5 stars
      ·
      338 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • P

      Packt

      Advanced PyTorch Techniques and Applications

      Skills you'll gain: PyTorch (Machine Learning Library), Natural Language Processing, Generative AI, Deep Learning, Unsupervised Learning, Text Mining, Supervised Learning, Image Analysis, Machine Learning, Google Cloud Platform, Application Deployment, Flask (Web Framework)

      4.9
      Rating, 4.9 out of 5 stars
      ·
      8 reviews

      Intermediate · Course · 1 - 3 Months

    • I

      IBM

      Generative AI: Foundation Models and Platforms

      Skills you'll gain: Generative AI, OpenAI, Large Language Modeling, Prompt Engineering, IBM Cloud, Google Cloud Platform, Artificial Intelligence, Artificial Neural Networks, Deep Learning, Natural Language Processing, Application Development

      4.7
      Rating, 4.7 out of 5 stars
      ·
      204 reviews

      Beginner · Course · 1 - 4 Weeks

    • I

      IBM

      Generative AI for Data Scientists

      Skills you'll gain: Prompt Engineering, Generative AI, ChatGPT, Exploratory Data Analysis, Data Ethics, OpenAI, Feature Engineering, Predictive Modeling, Large Language Modeling, Artificial Intelligence, Data Storytelling, Program Development, Data Modeling, Data Presentation, Predictive Analytics, Data Synthesis, Data Analysis, Data Cleansing, Data Visualization Software, Image Analysis

      4.7
      Rating, 4.7 out of 5 stars
      ·
      6.8K reviews

      Intermediate · Specialization · 1 - 3 Months

    • Status: AI skills
      AI skills
      U

      University of Pennsylvania

      AI and Machine Learning Essentials with Python

      Skills you'll gain: Statistical Machine Learning, PyTorch (Machine Learning Library), Probability, Probability & Statistics, Sampling (Statistics), Deep Learning, Probability Distribution, Python Programming, Supervised Learning, Statistics, Machine Learning, Regression Analysis, Data Processing, Agentic systems, Data Science, Artificial Intelligence, Artificial Neural Networks, Algorithms, Computer Vision, Theoretical Computer Science

      4.6
      Rating, 4.6 out of 5 stars
      ·
      24 reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      Imperial College London

      TensorFlow 2 for Deep Learning

      Skills you'll gain: Tensorflow, Generative AI, Data Pipelines, Keras (Neural Network Library), Deep Learning, Image Analysis, Computer Programming, Bayesian Statistics, Supervised Learning, Natural Language Processing, Data Processing, Computer Vision, Machine Learning Methods, Artificial Neural Networks, Machine Learning, Unsupervised Learning, Probability & Statistics, Time Series Analysis and Forecasting, Jupyter, Dimensionality Reduction

      4.8
      Rating, 4.8 out of 5 stars
      ·
      709 reviews

      Intermediate · Specialization · 3 - 6 Months

    • I

      IBM

      Introduction to Computer Vision and Image Processing

      Skills you'll gain: Computer Vision, Image Analysis, Artificial Neural Networks, IBM Cloud, Keras (Neural Network Library), Cloud Applications, Deep Learning, Tensorflow, Visualization (Computer Graphics), PyTorch (Machine Learning Library), Artificial Intelligence and Machine Learning (AI/ML), Computer Programming, Application Deployment, Augmented Reality, Machine Learning, Data Processing

      4.3
      Rating, 4.3 out of 5 stars
      ·
      1.4K reviews

      Beginner · Course · 1 - 3 Months

    • I

      IBM

      Introduction to Deep Learning & Neural Networks with Keras

      Skills you'll gain: Keras (Neural Network Library), Deep Learning, Unsupervised Learning, Artificial Neural Networks, PyTorch (Machine Learning Library), Tensorflow, Image Analysis, Computer Vision, Natural Language Processing, Machine Learning Algorithms

      4.7
      Rating, 4.7 out of 5 stars
      ·
      1.8K reviews

      Intermediate · Course · 1 - 3 Months

    • C

      Coursera Project Network

      Pneumonia Classification using PyTorch

      Skills you'll gain: PyTorch (Machine Learning Library), Medical Imaging, Radiology, Image Analysis, X-Ray Computed Tomography, Computer Vision

      4.4
      Rating, 4.4 out of 5 stars
      ·
      11 reviews

      Intermediate · Guided Project · Less Than 2 Hours

    • D

      DeepLearning.AI

      Probability & Statistics for Machine Learning & Data Science

      Skills you'll gain: Descriptive Statistics, Bayesian Statistics, Statistical Hypothesis Testing, Probability & Statistics, Sampling (Statistics), Probability Distribution, Probability, Statistical Inference, A/B Testing, Statistical Analysis, Statistical Machine Learning, Data Science, Exploratory Data Analysis, Statistical Visualization

      4.6
      Rating, 4.6 out of 5 stars
      ·
      564 reviews

      Intermediate · Course · 1 - 4 Weeks

    • E

      Edureka

      PySpark for Data Science

      Skills you'll gain: PySpark, Apache Spark, Unsupervised Learning, Data Pipelines, Apache Hadoop, Data Processing, Real Time Data, Big Data, Data Visualization, Distributed Computing, Natural Language Processing, Pandas (Python Package), Data Manipulation, Feature Engineering, Machine Learning, Machine Learning Algorithms, SQL, Data Transformation, Supervised Learning, Text Mining

      2.9
      Rating, 2.9 out of 5 stars
      ·
      9 reviews

      Intermediate · Specialization · 3 - 6 Months

    • Status: Free
      Free
      I

      IBM

      Machine Learning with Apache Spark

      Skills you'll gain: Apache Spark, Machine Learning, Generative AI, PySpark, Applied Machine Learning, Supervised Learning, Apache Hadoop, Data Pipelines, Unsupervised Learning, Data Processing, Extract, Transform, Load, Predictive Modeling, Classification And Regression Tree (CART), Data Transformation, Regression Analysis

      4.5
      Rating, 4.5 out of 5 stars
      ·
      99 reviews

      Intermediate · Course · 1 - 4 Weeks

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

    • Detecting COVID-19 with Chest X-Ray using PyTorch: Coursera Project Network
    • Advanced PyTorch Techniques and Applications: Packt
    • Generative AI: Foundation Models and Platforms: IBM
    • Generative AI for Data Scientists: IBM
    • AI and Machine Learning Essentials with Python: University of Pennsylvania
    • TensorFlow 2 for Deep Learning: Imperial College London
    • Introduction to Computer Vision and Image Processing: IBM
    • Introduction to Deep Learning & Neural Networks with Keras: IBM
    • Pneumonia Classification using PyTorch : Coursera Project Network
    • Probability & Statistics for Machine Learning & Data Science: DeepLearning.AI

    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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