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Computer Vision Trainer

Aryavart Institute of Technology

based on 2 Reviews

2-5 years

Supaul

1 vacancy

Computer Vision Trainer

Aryavart Institute of Technology and Management

posted 5mon ago

Key skills for the job

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Course Development: Design and develop comprehensive training programs in computer vision, tailored to various skill levels, including beginner, intermediate, and advanced learners. Topics include image processing, object detection, image classification, and deep learning for computer vision.
Content Creation: Create and update instructional materials such as presentations, coding exercises, datasets, and real-world case studies that reflect current computer vision practices and technologies.
Training Delivery: Conduct live, interactive training sessions via online platforms, focusing on essential computer vision skills such as image manipulation, feature extraction, and model training and evaluation.
Student Assessment: Evaluate student performance through quizzes, assignments, and practical projects. Provide constructive feedback to enhance their understanding and application of computer vision concepts.
Support and Mentorship: Offer personalized support to students, addressing their questions and assisting with troubleshooting issues related to computer vision techniques, tools, and methodologies.
Continuous Improvement: Stay updated with the latest trends and advancements in computer vision, including new techniques, tools, and research, and integrate these advancements into the training curriculum.

Qualifications:

For Experienced Professionals:

Experience: Minimum of 2-5 years of professional experience in computer vision, with hands-on experience in applying computer vision techniques to real-world problems.
Teaching Experience: Previous experience in teaching or training, especially in a freelance or online setting, is highly desirable.
Technical Skills: Proficiency in computer vision libraries and frameworks such as OpenCV, TensorFlow, Keras, or PyTorch. Experience with deep learning models for computer vision (e.g., CNNs, object detection models like YOLO, Faster R-CNN) is essential.
Certifications: Relevant certifications in computer vision or related fields (e.g., Deep Learning Specialization, Computer Vision with TensorFlow) are preferred but not mandatory.
Communication Skills: Strong communication skills with the ability to clearly and effectively explain complex computer vision concepts and techniques.

For Freshers:

Education: A degree or certification in Computer Vision, Data Science, Computer Science, Engineering, or a related field.
Technical Skills: Basic knowledge of computer vision techniques and tools, gained through academic coursework, internships, or personal projects. Familiarity with libraries such as OpenCV or TensorFlow is a plus.
Passion for Teaching: A strong interest in teaching and mentoring students in computer vision, with a commitment to developing effective training methods.
Communication Skills: Excellent verbal and written communication skills, capable of making complex computer vision topics understandable to diverse audiences.