MathWorks
Deep Learning for Computer Vision Specialization
MathWorks

Deep Learning for Computer Vision Specialization

Advance Your Engineering Career with AI Skills. Learn practical deep learning techniques for computer vision

Taught in English

Amanda  Wang
Mehdi Alemi
Matt Rich

Instructors: Amanda Wang

Included with Coursera Plus

Specialization - 3 course series

Get in-depth knowledge of a subject

Beginner level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Apply the full deep learning workflow to real-world projects like detecting parking signs

  • Retrain common classification and detection models like ResNet and YOLO

  • Train and calibrate specialized models known as anomaly detectors

  • Generate synthetic training images and use AI-assisted auto-labeling to save time and money

Details to know

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Recently updated!

January 2024

Specialization - 3 course series

Get in-depth knowledge of a subject

Beginner level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Advance your subject-matter expertise

  • Learn in-demand skills from university and industry experts
  • Master a subject or tool with hands-on projects
  • Develop a deep understanding of key concepts
  • Earn a career certificate from MathWorks
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Specialization - 3 course series

What you'll learn

  • Develop a strong foundation in deep learning for image analysis

  • Retrain common models like GoogLeNet and ResNet for specific applications

  • Investigate model behavior to identify errors, determine potential fixes, and improve model performance

  • Complete a real-world project to practice the entire deep learning workflow

Skills you'll gain

Category: Artificial Intelligence (AI)
Category: Computer Vision
Category: Deep Learning
Category: Matlab
Category: image classification

What you'll learn

  • Retrain popular YOLO deep learning models for your applications

  • Visualize results to gain insights into model performance

  • Evaluate detection models by examining both class and location accuracy.

  • Analyze labeled images to identify and fix potential data shortcomings

Skills you'll gain

Category: Computer Vision
Category: Object Detection
Category: Deep Learning
Category: Matlab

What you'll learn

  • Train and calibrate specialized models known as anomaly detectors

  • Generate synthetic training images for situations where acquiring more data is expensive or impossible

  • Use AI-assisted auto-labeling to save time and money

  • Import models from 3rd party tools like PyTorch and export your model outside of MATLAB

Skills you'll gain

Category: Anomaly Detection
Category: Artificial Intelligence (AI)
Category: Computer Vision
Category: Deep Learning
Category: Matlab

Instructors

Amanda  Wang
MathWorks
10 Courses32,524 learners

Offered by

MathWorks

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