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The language used throughout the course, in both instruction and assessments.
The language used throughout the course, in both instruction and assessments.
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.‎