CVision Pro: Deep Dive into AI Vision
This 12-week immersive course in Computer Vision offers a no-coding, concept-driven journey through the evolving landscape of visual intelligence. Starting from core foundations—such as feature extraction, object tracking, and classification—it progresses through advanced techniques in real-time detection, segmentation, and 3D vision. Learners also explore frontier topics like generative AI (text-to-image/video), multimodal vision-language models (like CLIP, GPT-4V), and cutting-edge tools such as YOLOv8, SAM, and ViT. With practical case studies across healthcare, robotics, retail, and AR/VR, the course not only imparts deep conceptual clarity but also guides learners on real-world deployment strategies, industry innovations, and career roadmaps in the AI Vision domain.
Who Should Join?
✅ Week 1: Introduction to Computer Vision
- Overview: What is Computer Vision?
- Traditional vs. Deep Learning Computer Vision
- Visual Processing Pipeline: Image → Process → Predict → Act
- Industry Domains: Healthcare, Surveillance, Automotive, Retail
✅ Week 2: Feature Extraction & Representation
- Fundamentals of Visual Features: Edges, Corners, Textures
- Classical Approaches: SIFT, ORB, SURF
- Deep Learning Feature Extraction: CNN Filters
- Real-Life Application Walkthroughs
✅ Week 3: Visual Tracking & Motion Analysis
- Object Tracking Techniques: Optical Flow, Kalman Filter, Particle Filters
- Deep Learning Trackers: Deep SORT
- Case Studies: Retail Analytics, Player Tracking, Smart Cities
✅ Week 4: Deep Learning for Object Classification
- Convolutional Neural Networks (CNN): Layer-wise intuitive understanding
- Transfer Learning: VGG, ResNet, EfficientNet
- Integration into Real-World Systems
- Applications: Quality Control, Agriculture, Recycling
✅ Week 5: Object Detection Techniques
- Classification vs. Detection: Concepts & Differences
- Bounding Box Regression & Anchors
- Advanced Models: YOLO Series, SSD, Faster R-CNN
- Case Studies: Surveillance Systems, Inventory Management
✅ Week 6: Advanced Object Detection in Real-Time
- Optimizing Real-time Performance
- Deployment Challenges & Solutions
- Practical Scenarios: Autonomous Vehicles, Real-Time Analytics
- Edge Deployment: NVIDIA Jetson, Google Coral
✅ Week 7: Image Segmentation and Semantic Understanding
- Semantic vs. Instance Segmentation
- Pixel-Level Accuracy: U-Net, Mask R-CNN
- Industry Cases: Medical Imaging, Autonomous Driving, Virtual Try-On
✅ Week 8: Advanced Image Segmentation & Applications
- Refining Segmentation Results
- Challenges and Limitations
- Deployment Insights: Healthcare and AR Applications
✅ Week 9: 3D Computer Vision Essentials
- 2D to 3D Vision: Depth Estimation, Stereo Vision
- Technologies: LiDAR, SLAM, Point Clouds
- Applications: Robotics, Drones, AR/VR
✅ Week 10: Generative Vision (Text-to-Image & Text-to-Video)
- Generative Models: DALL·E, Midjourney, Sora
- Understanding Diffusion and Transformer Models
- Applications: Advertising, Animation, Fashion Industry
✅ Week 11: Vision-Language Models & Multimodal Integration
- Multimodal AI: CLIP, GPT-4V, Gemini Vision
- Real-world Integration and Challenges
- Current Trends and Business Use-Cases
✅ Week 12: Recent Breakthroughs & Career Insights
- Cutting-edge Models: YOLOv8, Segment Anything (SAM), Vision Transformers (ViT)
- Industrial and Consumer Trends: Robotics, Smart Cameras, Wearables
- Deployment Innovations: NVIDIA DeepStream, Edge Computing
- Career Pathways: Roles, Roadmaps, Skill Enhancement