₹0.00 Free
11 Lessons( 20 week )
- Industrial AI - Micro Courses
- 1. Introduction to Physical AI – Overview 0 minute
- 2. Introduction to Computer Vision & Sensing 0 minute
- 3. Historical Perspective 0 minute
- 4. Digital Image Processing Fundamentals 0 minute
- 5. Machine Learning for Computer Vision 0 minute
- 6. Deep Learning and Convolutional Neural Networks (CNNs) 0 minute
- 7. Object Detection & Tracking 0 minute
- 8. Image Segmentation & Semantic Understanding 0 minute
- 9. Advanced Topics in Computer Vision 0 minute
- 10. Real-World Applications & Case Studies 0 minute
- 11. Career Opportunities & Future Trends 0 minute
Course Overview
This course provides a comprehensive exploration of AI-powered computer vision and sensing, offering a deep dive into the theoretical foundations and practical applications of this transformative field. Computer vision and sensing have become integral to modern technology, driving innovations in robotics, autonomous vehicles, healthcare, security, and more. This course is designed to equip students with the skills and knowledge needed to develop and deploy cutting-edge vision systems, preparing them for a successful career in a rapidly evolving industry. By focusing on real-world problem-solving, students will learn to apply AI techniques to a variety of visual and sensory data, bridging the gap between theory and practice.
Course Objectives
- Master the fundamental concepts of computer vision and AI.
- Understand the principles of various sensing technologies.
- Learn to process and analyze different types of visual data.
- Acquire skills in building and training machine learning models for computer vision tasks.
- Develop a strong foundation in a variety of AI algorithms, including deep learning.
- Gain hands-on experience with popular computer vision libraries and frameworks.
- Explore practical applications of AI-powered vision systems in diverse industries.
- Learn to evaluate and optimize the performance of vision models.
- Identify and solve real-world problems using computer vision and sensing technologies.
Course Outcomes
Students will be able to:
- Classify images with high accuracy using deep learning models.
- Detect and track objects in real-time video streams.
- Segment images to isolate specific objects or regions.
- Process and interpret sensor data from various sources, such as LiDAR and radar.
- Apply convolutional neural networks (CNNs) to solve visual recognition problems.
- Recognize faces using AI-based techniques.
- Implement AI solutions for image and video analysis tasks.
- Develop AI-powered systems for industrial inspection and quality control.
- Build a complete end-to-end vision pipeline from data acquisition to model deployment.
- Integrate AI-powered vision solutions into robotic systems for autonomous navigation.
Course Audience
- Aspiring AI/ML Engineers focused on computer vision.
- Robotics Engineers looking to integrate vision capabilities into their projects.
- Data Scientists wanting to specialize in visual data analysis.
- Software Developers interested in building AI-powered applications.
- Researchers and Academics seeking to expand their knowledge in this field.
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