Computer vision (CV), a subfield of computer science, focuses on replicating the complex functionalities of the human visual system. In the CV process, real-world images and videos are captured, processed, and analyzed to allow machines to extract contextual, useful information from the physical world.
Until recently, computer vision functioned in a limited capacity. But due to the recent innovations in artificial intelligence and deep learning, this field has made great leaps. Today, CV surpasses humans in most routine tasks connected with detecting and labeling objects.
The high-quality content of the Mastering Computer Vision from the Absolute Beginning Using Python course presents you with a great opportunity to learn and become an expert. You will learn the core concepts of the CV field. This course will also help you to understand the digital imaging process and identify the key application areas of CV. The course is:
Easy to understand.
Practical with live coding.
Rich with state of the art and updated knowledge of this field.
Although this course is a compilation of all the basic concepts of CV, you are encouraged to step up and experience more than what you learn. Your understanding of every concept is tested at the end of each section. The Homework assignments/tasks/activities/quizzes along with solutions will assess your learning. Several of these activities are focused on coding so that you are ready to run with implementations.
The two hands-on projects in the last section—Change Detection in CCTV Cameras (Real-time) and Smart DVRs (Real-time)—make up the most important learning element of this course. They will help you sharpen your practical skills. Successful completion of these two projects will help you enrich your portfolio and kick-start your career in the CV field.
The course tutorials are divided into 320+ videos along with detailed code notebooks. The videos are available in HD, and the total runtime of the videos is 27 hours+.
Now is the perfect time to learn computer vision. Get started with this best-in-class course without any further delay!
Teaching is our passion:
In this course, we apply the proven learning by doing methodology. We build the interest of learners first. We start from the basics and focus on helping you understand each concept clearly. The explanation of each theoretical concept is followed by practical implementation. We then encourage you to create something new out of your learning.
Our aim is to help you master the basic concepts of CV before moving onward to advanced concepts. The course material includes online videos, course notes, hands-on exercises, project work, quizzes, and handouts. We also offer you learning support. You can approach our team in case of any queries, and we respond in quick time.
After completing this course successfully, you will be able to:
Relate the concepts and theories in computer vision with real-world problems.
Implement any project from scratch that requires computer vision knowledge.
Know the theoretical and practical aspects of computer vision concepts.
Who this course is for:
The introduction and importance of Computer Vision (CV).
Why is CV such a popular field nowadays?
The fundamental concepts from the absolute beginning with comprehensive unfolding with examples in Python.
Practical explanation and live coding with Python.
The concept of colored and black and white images with practice.
Deep details of Computer Vision with examples of every concept from scratch.
TensorFlow (Deep learning framework by Google).
The use and applications of state-of-the-art Computer Vision (with implementations in state-of-the-art framework Numpy and TensorFlow).
Theory and implementation of Panoramic images.
Image Filtering with implementation in Python.
Edge Detection, Shape Detection, and Corner Detection.
Object Tracking and Object detection.
Building your own applications for change detection in the live feed of cameras by using Computer Vision Techniques using Python.
Developing a complete project to make a very intelligent and efficient DVR using Python.
No prior knowledge is needed. You will start from the basics and slowly build your knowledge in computer vision.
A willingness to learn and practice.
Knowledge of Python will be a plus.
Since we teach by practical implementations, practice is a must.