Introduction to Computer Vision and Image Processing by IBM via Coursera: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Self study	Mode of Delivery Video and Text Based

Course overview

The Introduction to Computer Vision and Image Processing by Coursera is the last course in IBM Applied AI Professional Certificate. This Specialization comprises six courses devoted to Computer Vision and its numerous applications across sectors. The certification course takes approximately 15 hours to complete, while the teaching medium is English.

Many industries such as robotics, face detection, and augmented reality employ computer vision and the vast implementations make IIntroduction to Computer Vision and Image Processing course very exciting. The course curriculum will furnish you with essential skills, including OpenCV, Watson, AI, and more.

Furthermore, the Introduction to Computer Vision and Image Processing certification course is offered by IBM (International Business Machines Corporation), a multinational consultancy and technology company headquartered in Armonk, New York.

The Introduction to Computer Vision and Image Processing programme is a beginner-level course with flexible deadlines. Enjoy a comfortable learning experience with this exciting course in AI and Machine Learning, and get a completion certificate from Coursera.

Course and certificate fees

The fees for the course Introduction to Computer Vision and Image Processing is -

Head	Amount
Certificate fees	Rs. 2,480

certificate availability

Yes

certificate providing authority

Coursera

certificate fees

₹2,480

Who it is for

Ai developer

Eligibility criteria

The Introduction to Computer Vision and Image Processing online course by Coursera requires some fundamental knowledge of python (programming language). No prior Computer Vision or Machine Learning experience is required for this course.

What you will learn

Knowledge of artificial intelligence

Upon successful completion of all the modules in the IIntroduction to Computer Vision and Image Processing certification course, you will have:

Computer Vision modelling
Using Watson AI, OpenCV, python for processing images
Interaction with image classification models
Creation of your own computer vision web app and deploying it to the Cloud
Building, training, and testing you own custom image classifiers

The syllabus

Module 1: Introduction to Computer Vision

Videos

Introduction to Computer Vision
Applications of Computer Vision
Recent Research in Computer Vision
Brainstorming Your Own Applications

Readings

Course Overview
Articles

Assignments

Practice Assessment
Graded Quiz: Overview of Computer Vision and its Applications

Plugin

Computer Vision in Action

Module 2: Image Processing with OpenCV and Pillow

Videos

What is a Digital Image
Manipulating Images
Manipulating Images One Pixel At a Time
Pixel Transformations
Geometric Operations
Spatial Operations in Image Processing

Assignments

Practice Assessment
Graded Quiz: Image Processing

App Items

Image processing with Pillow
Image processing with OpenCV
Basic Image Manipulation with Pillow
Basic Image Manipulation OpenCV
Histograms and Intensity Transformations
Geometric Transformations with Pillow
Geometric Transformations with OpenCV
Spatial Filtering Pillow
Spatial Filtering OpenCV

Module 3: Machine Learning Image Classification

Videos

Introduction to Image Classification
Image Classification with KNN
Linear Classifiers
Logistic Regression Training: Gradient Descent
Mini-Batch Gradient Descent
SoftMax and Multi-Class Classification
Support Vector Machines
Image Features

Assignments

Practice Assessment
Graded Quiz: Image Classification

App Items

Obtain IBM Cloud Feature Code and Activate Trial Account
Label your Data and Perform Image Classification with KNN
Logistic Regression With Mini-Batch Gradient Descent
Hand-written Digits Image Classification with Softmax
Support Vector Machines vs Vanilla Linear Classifier
Image Classification with SVM and CV Studio

Plugins

Set up Computer Vision learning environment
Getting started with CV Studio!

Module 4: Neural Networks and Deep Learning for Image Classification

Videos

Neural Networks
Fully Connected Neural Network Architecture
Convolutional Networks
CNN Architectures

Assignments

Practice Assessment
Graded Quiz: Neural Networks

App Items

Simple Neural Network for XOR
Neural Network Rectified Linear Unit (ReLU) vs Sigmoid
Training A Neural Network with Momentum
Convolutional Neural Network
Data Augmentation
Use CNN for "Hotdog, Not Hotdog" Classifier and Deploy Model with CV Studio

Plugins

Deploying a Model

Module 5: Object Detection

Videos

Object Detection
Object Detection with Haar Cascade Classifier

Readings

Object Detection with Deep Learning

Assignments

Practice Assessment
Graded Quiz: Object Detection

App Items

Car Detection with Haar Classifiers
Object Detection with Faster R- CNN
Object Detection using Pre-trained Models CV Studio

Module 6: Project Case: Not Quite a Self-Driving Car - Traffic Sign Classification

Peer Review

Task 5: Peer Reviewed Assignment

App Item

Task 1: Gather and Upload Your Data

Plugins

Project Overview
Task 2: Train Your Classifier
Task 3: Deploy Your Model
Task 4: Test Your Classifier

Admission details

To apply for the Introduction to Computer Vision with Watson and OpenCV programme by Coursera:

Step 1. Open https://www.coursera.org/.

Step 2. Search for “Introduction to Computer Vision with Watson and OpenCV” and click on the course information page.

Step3. Click on the ‘Enrol for free’ option provided to you on the page.

Step 4. Enrol on the website. First-time users might get access to the course for free for 7 days.

Step 5. If you have subscribed for specialization and need access to all the course material, make the payment.

Filling the form

To join the Introduction to Computer Vision with Watson and OpenCV online course, you need to fill in your details. Once you have completed this instruction, enter the password, and you can start the course. If you are not registered on the website, you need to sign in with your Google/Facebook/Coursera ID.

Scholarship Details

Candidates who are financially weak can apply for financial aid for the Introduction to Computer Vision with Watson and OpenCV certification course. They need to click on ‘Financial Aid Available’ link available on the course page to access the application form, fill out the details in the form and submit it. Coursera takes about fifteen days to respond and notify the candidates about the application status.

How it helps

The Introduction to Computer Vision with Watson and OpenCV programme by Coursera is an enjoyable beginner level course to learn about OpenCV and its applications. Computer Vision modelling is complemented by related hands-on projects to give a comprehensive technical experience.

Moreover, the curriculum comprises various exercises and lab work which are performed on the Cloud. The course is 100% online and allows you to learn at your own pace. Join the certification course to enhance your skillset and obtain your certificate of completion.

Instructors

Ms Aije Egwaikhide
Senior Data Scientist
IBM

Other Bachelors, Other Masters

Mr Joseph Santarcangelo
Data Scientist
IBM

Ph.D

FAQs

What skills can I gain from Introduction to Computer Vision with Watson and OpenCV?

This certification course will develop your skills in computer vision and artificial intelligence. These are some of the most exciting fields within Machine Learning, and you will learn their applications across industries.

Can I preview course materials?

You can choose to audit the course, wherein you can view the syllabus and course materials for free.

What is the course duration?

The Introduction to Computer Vision with Watson and OpenCV course has modules spread out over four weeks. The total completion time for this course is about 21 hours.

Are there weekly deadlines for the modules?

The Introduction to Computer Vision with Watson and OpenCV course is flexible, and it can be completed quickly. You can reschedule deadlines, listen to lectures and complete assignments at your own pace.

Will I earn any university credit after completing the course?

The Introduction to Computer Vision with Watson and OpenCV course does not carry any university credit by itself. However, some universities may accept Course Certificates for credit. Get in touch with your institution and submit accordingly.