Overview
This hands-on specialization dives in quickly, so you can start training models and gain practical deep learning skills. You don’t need to be an expert programmer or have prior deep learning experience to quickly gain valuable career skills for this rapidly growing area.
Deep learning empowers engineers and scientists to tackle complex problems in computer vision that were previously challenging to solve, such as building autonomous systems like self-driving cars. As companies increasingly adopt computer vision technologies, professionals with deep learning skills are in high demand. Acquiring these skills will give you a competitive advantage in a rapidly changing technological landscape.
By the end of this specialization, you will be able to:
Train image classification and object detection models Train specialized models to detect anomalies Evaluate model performance using more than just prediction accuracy Interpret model behavior by investigating prediction errors Improve model performance by tuning important parameters Use AI-assisted labeling to automatically label thousands of images Generate synthetic images to for training using data-augmentation
For the duration of the specialization, you will have free access to MATLAB, software used by top employers worldwide. The courses draw on the applications using MATLAB, so you spend less time coding and more time applying deep learning concepts.
Syllabus
Course 1: Introduction to Deep Learning for Computer Vision
- Offered by MathWorks. Starting with zero deep learning knowledge, this foundational course will guide you to effectively train cutting-edge ... Enroll for free.
Course 2: Deep Learning for Object Detection
- Offered by MathWorks. Detecting and locating objects is one of the most common uses of deep learning for computer vision. Applications ... Enroll for free.
Course 3: Advanced Deep Learning Techniques for Computer Vision
- Offered by MathWorks. Visual inspection and medical imaging are two applications that aim to find anything unusual in images. In this ... Enroll for free.
- Offered by MathWorks. Starting with zero deep learning knowledge, this foundational course will guide you to effectively train cutting-edge ... Enroll for free.
Course 2: Deep Learning for Object Detection
- Offered by MathWorks. Detecting and locating objects is one of the most common uses of deep learning for computer vision. Applications ... Enroll for free.
Course 3: Advanced Deep Learning Techniques for Computer Vision
- Offered by MathWorks. Visual inspection and medical imaging are two applications that aim to find anything unusual in images. In this ... Enroll for free.
Courses
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Starting with zero deep learning knowledge, this foundational course will guide you to effectively train cutting-edge models for image classification purposes. From analyzing medical images to recognizing traffic signs, classification is important for many applications. Classification models also serve as the backbone for more complicated object detection models. Through hands-on projects, you will train and evaluate models to classify street signs and identify the letters of American Sign Language. By completing this course, you will develop a strong foundation in deep learning for image analysis and will be equipped with the skills to tackle real-world computer vision challenges. By the end of this course, you will be able to: • Explain how deep learning networks find image features and make predictions • Retrain common models like GoogLeNet and ResNet for specific applications • Investigate model behavior to identify errors and determine potential fixes • Improve model performance by tuning hyperparameters • Complete the entire deep learning workflow in a final project For the duration of the course, you will have free access to MATLAB, software used by top employers worldwide. The courses draw on the applications using MATLAB, so you spend less time coding and more time applying deep learning concepts.
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Detecting and locating objects is one of the most common uses of deep learning for computer vision. Applications include helping autonomous systems navigate complex environments, locating medical conditions like tumors, and identifying ready-to-harvest crops in agriculture. In the course projects, you will apply detection models to real-world scenarios and train a model to detect various parking signs. Completing this course will give you the skills to train detection models for your application. By the end of this course, you will be able to: • Explain how deep learning networks locate and classify objects in images • Retrain popular YOLO deep learning models for your application • Use a variety of metrics to evaluate prediction results • Visualize results to gain insights into model performance • Improve model performance by adjusting important model parameters • Analyze labeled images to identify and fix potential shortcomings in your data For the duration of the course, you will have free access to MATLAB, software used by top employers worldwide. The courses draw on the applications using MATLAB, so you spend less time coding and more time applying deep learning concepts.
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Visual inspection and medical imaging are two applications that aim to find anything unusual in images. In this course, you’ll train and calibrate specialized models known as anomaly detectors to identify defects. You’ll also use advanced techniques to overcome common data challenges with deep learning. AI-assisted labeling is a technique to auto-label images, saving time and money when you have tens of thousands of images. If you have too few images, you’ll generate synthetic training images using data augmentation for situations where acquiring more data is expensive or impossible. By the end of this course, you will be able to: • Train anomaly detection models • Generate synthetic training images using data augmentation • Use AI-assisted annotation to label images and video files • Import models from 3rd party tools like PyTorch • Describe approaches to using your model outside of MATLAB For the duration of the course, you will have free access to MATLAB, software used by top employers worldwide. The courses draw on the applications using MATLAB, so you spend less time coding and more time applying deep learning concepts.
Taught by
Amanda Wang, Brandon Armstrong, Matt Rich, Megan Thompson and Mehdi Alemi