AI and Machine Learning is a New Frontier

Put Computer Vision on YOUR Resume

Are you ready to take your machine learning skills to the next level? Do you want to learn how to train a neural network on images? Do you want to write your own computer vision project from start to finish? Do you want to learn skills that will help you tackle other complex projects?

Develop a Valuable Skillset

This course will take you from the theory of machine learning and computer vision to the practice of developing your own python code for a computer vision project. The skills you develop will prepare you to tackle other exciting machine learning projects. Your final project in this course will be a machine learning pipeline that recognizes human faces in an image or live video stream and classifies them by emotion.

Course curriculum

Click on the dropdown menus to see the details for each course section

    1. Course Overview

    2. Tutorial: NumPy and PyTorch

    3. Assignment: NumPy Arrays

    4. Assignment: PyTorch Tensors

    5. Quiz: NumPy and PyTorch Assignments

    1. Theory: Images as Data

    2. Reading: Images as Data

    3. Tutorial: opencv and mediapy

    4. Assignment: Working with Images

    5. Quiz: Images as Data

    6. Theory: Image Convolution

    7. Reading: Image Convolution

    8. Tutorial: Operations for Convolution

    9. Assignment: Convolution

    10. Quiz: Convolution

    11. Theory: Kernels

    12. Reading: Kernels

    13. Tutorial: Pretrained Object Detection

    14. Assignment: Pretrained Face Detection

    15. Quiz: Kernels

    1. Theory: Forward Propagation of Neural Nets

    2. Reading: Forward Propagation of Neural Nets

    3. Tutorial: Torch Modules

    4. Assignment: Creating a Neural Net

    5. Quiz: Forward Propagation

    6. Theory: Backpropagation of Neural Nets

    7. Reading: Backpropagation of Neural Nets

    8. Theory: Training a Neural Net

    9. Reading: Training a Neural Net

    10. Tutorial: Training a Neural Net Pt. 1

    11. Tutorial: Training a Neural Net Pt. 2

    12. Assignment: Training a Neural Net

    13. Quiz: Training a Neural Net

    1. Theory: Convolutional Neural Networks

    2. Reading: Convolutional Neural Networks

    3. Tutorial: Torch Convolution

    4. Assignment: Training a CNN

    5. Tutorial: Image Augmentation

    6. Quiz: Convolutional Neural Nets

    7. Theory: Object Detection

    8. Reading: Object Detection

    9. Quiz: Object Detection

    10. Theory: Model Pipeline

    11. Reading: Model Pipeline

    12. Tutorial: Saving/Uploading Torch Models

    1. Emotion Classification

    2. YOLO Face Detection (optional)

    3. Model Pipeline

    4. Live Webcam (optional)

    5. Thank You!

About this course

  • Free
  • 50 lessons
  • 4 hours of video content

Built to Help You Succeed

  • Animated video lectures on machine learning and computer vision theory, accompanied by pdf files with detailed notes

  • Coding instruction videos, assignments, checkers, and answer keys to make sure your code is correct

  • Quizzes to ensure that you are ready to move on to the next part of the course

  • Guidance to help you be successful with the final project

  • Build a final project that you can add to your portfolio

Sign Up Today!

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This course launched on June 1 2023. Save 80% by enrolling now.

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Instructor: Cason Wight

[email protected]

Cason is a data scientist working in advertising technology. Cason has a Master's in Statistics from BYU, where he published research in Markov models, generalized linear models, and FFT-based convolution.