What you'll get
- 10+ Hours
- 5 Courses
- Course Completion Certificates
- Self-paced Courses
- Technical Support
- Case Studies
- Download Curriculum
Synopsis
- Provides access to a comprehensive bundle of five courses and projects, eliminating the need to purchase each course individually.
- Offers over 10 hours of engaging video content covering practical applications.
- Covers the essentials of the OpenCV library, including image wrapping, face datasets, object detection, and video analysis techniques.
- One-year course access allows learners to study at their own pace.
- Ideal for individuals dedicated to learning image processing and video analysis with OpenCV and pursuing a career in this field.
- Prior exposure to basic machine learning concepts is advantageous for effective learning.
- Participants will earn a completion certificate for each of the five courses and associated projects.
- Verifiable certificates include a unique link that enables learners to showcase their skills on resumes and LinkedIn profiles.
- Delivered as a self-paced video course, allowing flexibility to learn anytime, anywhere.
Content
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| OpenCV for Beginners | 2h 28m | ✔ | View Curriculum |
| Courses | No. of Hours | Certificates | Details |
|---|---|---|---|
| Video Analytics Using Opencv and Python Shells | 2h 13m | ✔ | View Curriculum |
| Face Detection Using OpenCV and Python | 1h 52m | ✔ | View Curriculum |
| Project on OpenCV - Hand Gesture | 2h 1m | ✔ | View Curriculum |
| Face Recognition using OpenCV | 2h 5m | ✔ | View Curriculum |
Description
This OpenCV Training Certification equips learners with essential skills in computer vision and machine learning, forming a strong foundation for careers in data science and programming. The course also introduces hardware-related competencies relevant to OpenCV applications, ensuring a well-rounded technical understanding. Participants will gain experience with software tools across multiple operating systems, including Linux, Windows, macOS, FreeBSD, OpenBSD, and NetBSD. Additionally, the training covers mobile operating systems such as Android, iOS, Blackberry, and Maemo, preparing learners to work on a variety of platforms.
Sample Certificate
Requirements
- Basic working knowledge of Python is required, preferably with some hands-on experience.
- Familiarity with core concepts and terminology of machine learning and data science is recommended.
- A general understanding of computer vision principles and awareness of current industry trends in emerging technologies.
- Foundational knowledge of statistics and mathematical tools to support learning and practical applications.
Target Audience
- Individuals working as data scientists, software developers, engineers, or testers looking to strengthen their knowledge of computer vision and OpenCV.
- Python programmers, research analysts, and consultants who want to expand their expertise in video analytics and related technologies.
- Students and learners interested in robotics, biometrics, and innovative applications of computer vision.
- College students working on project assignments or research initiatives that involve image processing or video analysis.
- Entrepreneurs and startup innovators aiming to implement new technologies and support their teams with practical OpenCV knowledge.
