Programming AI Vision Using Python is a 4-day practical training program that equips learners with the skills to develop computer vision applications using Python, OpenCV, and AI libraries such as TensorFlow or PyTorch. The course focuses on building real-time vision systems for object detection, image classification, and video analysis, providing hands-on experience in combining traditional image processing with modern AI models.
Course Duration
4 Days
Exam
Multiple-choice
Access Mode
Physical
Certification Validity
Lifetime
Modules Included
Introduction to Computer Vision and Python Setup
Image Processing with OpenCV (Filtering, Thresholding, Edge Detection)
AI-Based Object Detection and Image Classification
Real-Time Video Stream Analysis and Application Development
Final Project: Build a Mini AI Vision System
Top Job Roles
Computer Vision Developer
AI/ML Engineer
Python Developer
Robotics Vision Engineer
Surveillance System Developer
Research Assistant in AI and Vision
What kind of job can I get with this training?
You can apply for entry-level or intermediate roles in AI development, computer vision, or Python programming, especially in sectors like automation, surveillance, smart cities, and robotics.
Do I need to know AI or Python in advance?
Basic Python knowledge is recommended. The course provides guided practice to help you understand and apply AI vision techniques step by step.
Will I use real-world images or video data?
Yes. You’ll work with real datasets and camera inputs, creating applications that run in real time, like object counters, face detectors, and anomaly detection systems.
Can I apply these skills to embedded or IoT devices?
Yes. The course includes optimization tips and examples for edge deployment, especially for lightweight models suited to Raspberry Pi or Jetson Nano.
Certification Benefits
Learn practical AI vision development with industry tools
Gain proficiency in OpenCV and AI model integration
Build real-time video analysis systems using Python
Receive a Certificate of Completion and project files for your portfolio
Prepare for future roles in machine learning, automation, and robotics
