Image Processing and Computer Vision with Python & OpenCV
Learn Image Processing and Computer Vision from AI (ML & DL) professional
Affiliate disclosure: if you enroll through links on this page, the course provider may pay us a commission. This comes at no extra cost to you and does not influence how we describe courses.
What You'll Learn in This Course
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Learning Outcome 1
Image Processing with Python (skimage) (90% hands on and 10% theory)
Learning Outcome 2
Image Processing and Computer Vision with OpenCV (90% hands on and 10% theory)
Learning Outcome 3
Morphological operations with OpenCV (90% hands on and 10% theory)
Learning Outcome 4
Face detection with OpenCV (90% hands on and 10% theory)
Learning Outcome 5
Feature detection with OpenCV (90% hands on and 10% theory)
Skills You'll Develop
This comprehensive Image Processing and Computer Vision with Python & OpenCV curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
Course Requirements & Target Audience
Understand what you need to succeed in this course and determine if it's the right fit for your learning goals
Prerequisites & Requirements
What you need before starting this Image Processing and Computer Vision with Python & OpenCV course:
- 1. Passion for Learning 2. Curiosity for image analysis 3. NumPy knowledge
Who This Course Is For
This course is perfect for:
- Motivated learners at any level
- Self-paced students
- Anyone interested in the subject
This course might not be suitable if:
- • You're looking for a quick tutorial rather than comprehensive learning
- • You prefer learning without structured curriculum
- • You need highly specialized or niche content
Course Information & Details
Everything you need to know about this online course, from duration to certification
Course Instructor
Shiv Onkar Deepak Kumar
Expert instructor with industry experience
Course Language
English
All materials in English
Start Your Learning Journey Today
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
Course Enrollment
Budget-Friendly Course
Typically around $24.99
Pricing may vary. Check the course provider for current promotions and exact pricing.
What's Included
- 8.5 hours on-demand video
- 2 downloadable resources
- Access on mobile and TV
- Certificate of Completion
- Full lifetime access
Affiliate disclosure: if you enroll through links on this page, the course provider may pay us a commission. This comes at no extra cost to you and does not influence how we describe courses.
- ✓Instant access after enrollment
- ✓Learn at your own pace
- ✓Direct enrollment with Udemy
Where this course fits
Certifications in this area
- Microsoft Certified: Azure Data Fundamentals · Foundational
- Microsoft Certified: Azure AI Fundamentals · Foundational
- AWS Certified AI Practitioner · Foundational
- Microsoft Certified: Fabric Data Engineer Associate · Associate
- Microsoft Certified: Power BI Data Analyst Associate · Associate
- Databricks Certified Data Engineer Associate · Associate
Concepts behind this area
Transformers
A transformer is a neural-network design that takes a whole sequence in at once and, for every element in it, works out how strongly each of the other elements should influence that one.
Prompt Engineering
Prompt engineering is the practice of composing what you send a generative model, the instruction, the supporting material and the worked examples, so that it returns something you can actually use.
Retrieval-Augmented Generation
Retrieval-augmented generation is a pattern that searches a body of documents when a question arrives and places the passages it finds into the model's prompt, so the answer is drawn from those sources rather than from training alone.
SQL
SQL is the declarative language for asking questions of relational databases: you state which rows and columns you want and how tables relate, and the database engine works out how to retrieve them.
Data Analysis
Data analysis is the practice of interrogating data to answer a specific question, and of establishing how much weight the answer can bear.
Data Wrangling
Data wrangling is the work of repairing and reshaping real records, and of deciding what their gaps and inconsistencies mean, until a table can be trusted with the question being asked of it.
The field, explained: Artificial Intelligence & Machine Learning · Data & Analytics
Wider context: the fields we cover, the glossary and certification exams, all written by us rather than pulled from a provider feed.
