Course Information
- Available
- *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Course Overview
Build Powerful Computer Vision, Deep Learning, and OCR Solutions with Python, Numpy, Pandas, and OpenCV
Master Computer Vision and Deep Learning with Python and OpenCV
Unlock the power of AI and machine learning to build intelligent computer vision applications.
This comprehensive course will equip you with the skills to:
Master Python Programming: Gain a solid foundation in Python programming, essential for data analysis, visualization, and machine learning.
Harness the Power of OpenCV: Learn to process images and videos using OpenCV, a powerful computer vision library.
Dive into Deep Learning: Explore state-of-the-art deep learning techniques, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs).
Build Real-World Applications: Apply your knowledge to practical projects, such as:
Object Detection and Tracking: Identify and track objects in real-time videos.
Image Classification: Categorize images into different classes.
Image Segmentation: Segment objects of interest from background images.
Facial Recognition: Recognize and identify individuals from facial images.
Medical Image Analysis: Analyze medical images to detect diseases.
Autonomous Vehicles: Develop self-driving car technology, object detection, and lane detection.
Retail: Customer analytics, inventory management, and security surveillance.
Security and Surveillance: Facial recognition, object tracking, and anomaly detection.
Leverage Advanced Techniques: Learn advanced techniques like transfer learning, fine-tuning, and model optimization to build high-performance models.
Explore Cutting-Edge Topics: Delve into generative AI, video analysis, and 3D computer vision to stay ahead of the curve.
Deploy Your Models on Edge Devices: Learn how to deploy computer vision models on devices like Raspberry Pi and NVIDIA Jetson.
Why Choose This Course?
Comprehensive Curriculum: Covers a wide range of topics, from beginner to advanced.
Hands-On Projects: Gain practical experience with real-world projects.
Expert Instruction: Learn from experienced instructors with a deep understanding of computer vision and deep learning.
Flexible Learning: Learn at your own pace with self-paced video lessons and downloadable resources.
24/7 Support: Get timely assistance from our dedicated support team.
Career Advancement: Advance your career in AI, machine learning, and computer vision.
Join us today and unlock the power of computer vision!
Course Content
- 26 section(s)
- 76 lecture(s)
- Section 1 Course Starter
- Section 2 Introduction to Python
- Section 3 Python Setup
- Section 4 Data Types and Operators
- Section 5 Loops - If-Else, For, While
- Section 6 Functions, Modules & File Handling
- Section 7 Popular Coding Practices and Exception Handling
- Section 8 Advanced Functions - Lambda, Map, Filter, Reuse
- Section 9 Object Oriented Programming, Decorator and Generator
- Section 10 Built-in Modules - DateTime, Math, Random, Statistics, Sys, OS
- Section 11 External Libraries - Numpy, Pandas, Matplotlib, OpenPyXL
- Section 12 Introduction to OpenCV
- Section 13 Image Thresholding
- Section 14 Image Noise Removal
- Section 15 Image Cropping & Rotation Techniques
- Section 16 Image Annotation
- Section 17 Image Detection Techniques
- Section 18 OpenCV for Videos
- Section 19 OpenCV for OCR
- Section 20 Advanced Computer Vision: Generative Models, Video Analysis, and Edge AI
- Section 21 Project 1 - Python Web Scraping using BeautifulSoup and RegEx
- Section 22 Project 2 - Sending Email with Python (Flask)
- Section 23 Project 3 - Extract text from PDF using Python
- Section 24 Project 4 - Template matching using OpenCV
- Section 25 Project 5 - Track Object by Marking in Live Camera using OpenCV
- Section 26 More Learnings
What You’ll Learn
- Learn Python from the ground up and build your own computer vision and deep learning solutions.
- Understand Python data types, operators, loops, functions, modules, and file handling, as well as best coding practices.
- Master advanced Python concepts such as lambda functions, object-oriented programming, decorators, and generators.
- Learn to use Python built-in libraries such as DateTime, Math, Random, Statistics, Sys, and OS.
- Gain expertise in Numpy, Pandas, Matplotlib, and OpenPyXL for high-performance data manipulation and visualization.
- Build a strong foundation in OpenCV to work with images and videos efficiently.
- Use OpenCV to perform image thresholding, noise removal, cropping, rotation, annotation, and detection.
- Apply OpenCV to live webcam and recorded video streams.
- Develop Python solutions for web scraping, sending emails using Flask, and extracting text from PDF documents.
- Build OpenCV solutions for template matching and object tracking in real time.
Skills covered in this course
Reviews
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LLalit
This course is a great introduction to Computer Vision and Deep Learning with Python and OpenCV. The instructor is knowledgeable and engaging, and the course materials are well-organized and easy to follow. I especially appreciated the hands-on projects, which gave me a chance to apply what I was learning to real-world problems. If you're interested in learning computer vision and deep learning, I highly recommend this course. It's a great way to get started in these rapidly growing fields.
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JJean-Luc Freymond
Very strong foreign accent and bad sound quality.
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SSamantha Water
Excellent course on python and opencv with downloadable code available for each of the concepts available
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MMichael Kemp
The course content is well designed and best part is all the code works smoothly. Instructor explains the concepts very clearly and is quick in responding to any queries. I will strongly recommend this course for developers