Deep Learning - Computer Vision for Beginners Using PyTorch

This course offers a comprehensive introduction to PyTorch and deep learning for computer vision, with sections on Python fundamentals for those new to the language or needing a refresher. The curriculum begins with PyTorch basics, followed by instructions on accessing free GPU resources and coding on GPU. Students will explore PyTorch's AutoGrad feature and use it to implement gradient descent. The course covers creating deep learning models and convolutional neural networks (CNNs), and applying these skills to real-world datasets. Additionally, students will learn to use key Python libraries such as NumPy, Pandas, and Matplotlib, and will undertake a mini project to build a hangman game in Python. By the end of the course, participants will be equipped to perform computer vision tasks using deep learning. This course is ideal for software developers, machine learning practitioners, and data scientists. Basic Python knowledge is beneficial but not required.