MathWorks
MathWorks Computer Vision Engineer Professional Certificate
4,717 enrolled
MathWorks

MathWorks Computer Vision Engineer Professional Certificate

Advance your career with computer vision skills. Learn and apply the computer vision skills needed to effectively address real-world challenges experienced across many industries.

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Earn a career credential that demonstrates your expertise

(64 reviews)

Beginner level
No prior experience required
Flexible schedule
2 months at 10 hours a week
Earn a career credential
Share your expertise with employers
Earn a career credential that demonstrates your expertise

(64 reviews)

Beginner level
No prior experience required
Flexible schedule
2 months at 10 hours a week
Earn a career credential
Share your expertise with employers

Overview

  • Automatically extract information from images

  • Detect and track objects in images and videos

  • Apply the full deep-learning workflow to computer vision challenges

  • Export models to common formats like Tensorflow or PyTorch

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English
68 practice exercises

Professional Certificate - 9 course series

What you'll learn

  • Perform analysis on a variety of common image datatypes & recognize their strengths and limitations

  • Detect objects and regions of interest using intensity-based & color-based image segmentation

  • Improve image contrast using a variety of modern algorithms for different use-cases, such as low light or fog

  • Complete a project where you analyze Antarctic ice melt in satellite images

Skills you'll gain

Category: Image Analysis
Category: Histogram
Category: Matlab
Category: Data Processing
Category: Data Transformation
Category: Data Import/Export
Category: Color Theory
Category: Data Manipulation
Category: Data Storage
Category: Metadata Management
Category: Computer Vision

What you'll learn

  • Use segmentation to detect and analyze regions of interest in images & video

  • Apply spatial filters and morphological operators to improve segmentation & remove noise

  • Segment & analyze 3D images, such as MRI images of a brain

  • Use interactive tools to quickly test a variety of segmentation approaches & automatically generate code for reuse

Skills you'll gain

Category: Image Analysis
Category: Data Processing
Category: Unsupervised Learning
Category: Computer Vision
Category: Spatial Analysis

What you'll learn

  • Apply image processing algorithms to large sets of images & verify your algorithms generalize to new images

  • Apply image processing algorithms to video files

  • Analyze your image & video processing results, including calculating statistics like average area & identifying outliers

  • Complete a specialization-level project where you will detect cars in a noisy video

Skills you'll gain

Category: Image Analysis
Category: Automation
Category: Matlab
Category: Machine Learning
Category: Data Storage Technologies
Category: Algorithms
Category: Computer Vision
Category: Anomaly Detection
Category: Data Store

What you'll learn

  • Use common algorithms for feature detection, extraction, & matching

  • Perform image registration by identifying control points & estimating geometric transformations

  • Complete a final project where you stitch together images from NASA’s Mars Curiosity Rover

  • Combine images with image stitching to create panorama images

Skills you'll gain

Category: Matlab
Category: Computer Vision
Category: Algorithms
Category: Linear Algebra
Category: Data Validation
Category: Geospatial Information and Technology
Category: Image Analysis

What you'll learn

  • Prepare data and create features for classifying images

  • Train & evaluate models to classify images using

  • Train & evaluate object detection machine learning models

  • Customize model training for different applications using cost matrices

Skills you'll gain

Category: Computer Vision
Category: Machine Learning
Category: Image Analysis
Category: Feature Engineering
Category: Applied Machine Learning
Category: Supervised Learning
Category: Data Validation
Category: Classification And Regression Tree (CART)
Category: Performance Tuning

What you'll learn

  • Use pre-trained deep neural networks like YOLO to perform object detection

  • Use optical flow to detect motion & moving objects

  • Perform multi-object tracking to count, track, & determine the direction of objects

Skills you'll gain

Category: Computer Vision
Category: Simulations
Category: Machine Learning Algorithms
Category: Deep Learning
Category: Anomaly Detection
Category: Medical Imaging
Category: Image Analysis

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: Deep Learning
Category: Artificial Neural Networks
Category: Image Analysis
Category: Applied Machine Learning
Category: Performance Tuning
Category: Data Validation
Category: Computer Vision
Category: Matlab
Category: Exploratory Data Analysis

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: Deep Learning
Category: Image Analysis
Category: Computer Vision
Category: Matlab
Category: Data Collection
Category: Tensorflow
Category: Keras (Neural Network Library)
Category: Visualization (Computer Graphics)
Category: Data Processing
Category: PyTorch (Machine Learning Library)
Category: Applied Machine Learning
Category: Data Validation

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: Deep Learning
Category: Computer Vision
Category: Medical Imaging
Category: Matlab
Category: Anomaly Detection
Category: Data Synthesis
Category: Performance Tuning
Category: Interoperability
Category: PyTorch (Machine Learning Library)
Category: Image Analysis

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Sam Jones
MathWorks
3 Courses40,032 learners
Amanda Wang
MathWorks
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Isaac Bruss
MathWorks
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Megan Thompson
MathWorks
9 Courses36,127 learners
Mehdi Alemi
MathWorks
4 Courses5,811 learners
Matt Rich
MathWorks
13 Courses61,521 learners
Brandon Armstrong
MathWorks
17 Courses93,191 learners

Offered by

MathWorks

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Frequently asked questions

¹ Median salary and job opening data are sourced from Lightcast™ Job Postings Report. Content Creator, Machine Learning Engineer and Salesforce Development Representative (1/1/2024 - 12/31/2024) All other job roles (8/1/2024 - 8/1/2025)