Computer Vision using Python

About the Course:
In today’s technology driven world, there is a huge amount of visual data generated across different platforms. Computer vision enables us to interpret and utilize visual data, with applications spanning numerous industries, including autonomous vehicles, social media applications, medical imaging, and many more. As one of the fastest-growing programming languages, Python is ideal for harnessing the power of existing computer vision libraries to make sense of this vast data. Therefore, this course is designed to be your go-to resource for mastering the use of Python for Computer Vision tasks. Here, we’ll dive into how to utilize Python and the OpenCV (Open Computer Vision) library to work with images and video data.

What you will learn?
In this course, you’ll gain all the skills needed to become proficient in computer vision. We’ll begin by covering numerical processing with the NumPy library, learning to open and manipulate images using NumPy. From there, we’ll dive into OpenCV, focusing on image basics and working through techniques for image processing, such as color mapping, blending, thresholding, and gradients. Next, we’ll shift to video processing fundamentals in OpenCV, including streaming video from a webcam, followed by in-depth topics like optical flow and object detection, including face detection and object tracking. Finally, you will be able to learn the latest deep learning advancements in computer vision, including image recognition and custom image classification.

Course Objectives (By the end of this course, participants will be able to):
1. Understand the core concepts of computer vision and its applications in various industries.
2. Use Python libraries such as NumPy and OpenCV to effectively process image and video data.
3. Apply image processing techniques like color mapping, blending, and thresholding to manipulate visual data.
4. Stream and analyze video data, implementing advanced techniques like optical flow and object detection.
5. Utilize deep learning methods for tasks like image recognition and custom image classification.
6. Develop practical computer vision projects to demonstrate and apply learned skills in real-world scenarios.



Batch Details:
Class Timings: 4:00 pm – 6:00 pm (Saturdays), 10 pm – 12 pm (Sundays)
Start Date: 21st Dec 2024
End Date: 9th March 2025
Mode: Online (ILT over Zoom/Webex/GMeet)
Certification: Globally accepted
Duration: 48 Hours
Last Date to Register: 20th Dec 2024
Course Fee:
Students/PhD Scholars/RA/JRF/SRF/Postdoc fellows: Rs. 8000/-
Faculty/Working Professional: Rs. 10,000/-

Link to Register : - https://rzp.io/rzp/ComputerVisionCourse


Contact Person:
Dr. Subrat Kotoky
CTO, Ritvij Bharat Pvt. Ltd. (RBPL)
Ph.D. in Mechanical Engineering (IIT Guwahati)
rbpl.edu@gmail.com/subrat.kotoky@ritvij.co.in
9085317465/8473874389


Expert Profile: Mr. Shreyas Shukla
Professional Corporate Trainer & Microsoft Azure Certified Data Engineer
M.Tech-IIT Kharagpur & BE- The Aeronautical Society of India, New Delhi

1. DP-203: Microsoft Certified: Azure Data Engineer Associate
2. DP-900: Microsoft Certified: Azure Data Fundamentals
3. AZ-900: Microsoft Certified: Azure Fundamentals