Live Projects Training
Discover hands-on live projects for budding developers and kickstart your coding journey with guided strategies.
Explore our Categories
Human Pose Estimation
This immersive, hands-on course is designed to provide students with a comprehensive understanding of computer vision and deep learning for human pose estimation. Human pose estimation is crucial in various fields, including sports analytics, action recognition, and human-computer interaction. Through this course, students will explore the intricacies of pose estimation algorithms and develop the skills to build and implement deep neural networks for this purpose.
Prerequisite:
Python, TensorFlow/PyTorch, OpenCV, NumPy aan Matplotlib
Difficulty:
Skills to be Learned:
Building and training CNN models for pose estimation
Image Classification on MNIST Dataset (Using ANN)
Kickstart your journey in deep learning with this project-based course, focusing on image classification using Artificial Neural Networks (ANNs) and the well-known MNIST dataset.
Prerequisite:
NumPy, TensorFlow, or PyTorch.
Difficulty:
Advanced
Skills to be Learned:
In-depth knowledge of Artificial Neural Networks and their components.
Image Classification using Pretrained Models (VGG16, ResNet50)
This comprehensive course is tailored for individuals keen on mastering computer vision and deep learning, focusing on image classification with pretrained models VGG16 and ResNet50, using the CIFAR-10 dataset.
Prerequisite:
Basic understanding of machine learning and deep learning concepts.
Difficulty:
Advance
Skills to be Learned:
Utilizing leading pretrained models like VGG16 and ResNet50.
Image Segmentation By Clustering
Dive into the world of computer vision with our project-based course focusing on image segmentation. Learn to partition images using clustering techniques, extract features, and refine segmentation results. Ideal for those with basic programming knowledge and an interest in image analysis.
Prerequisite:
OpenCV, NumPy, SciPy, Scikit-learn, Matplotlib
Difficulty:
Intermediate
Skills to be Learned:
Understanding of image segmentation, implementation of clustering algorithms
Lane Detection
Dive into the realm of computer vision and deep learning with this project-based course, where you'll learn the intricacies of lane detection crucial for autonomous vehicles and robotics.
Prerequisite:
Python, OpenCV for computer vision tasks, TensorFlow or PyTorch for CNN-based approaches.
Difficulty:
Advanced
Skills to be Learned:
Core computer vision principles for lane detection.
Live Project Training Benefits
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Learn by doing - Work on real-world projects to gain practical experience.
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Get personalized feedback from experienced instructors.
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Collaborate with other learners in a supportive environment.
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Build a portfolio of projects to showcase your skills.
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Receive a certificate of completion upon completing the training.
Training Delivery
Our live project training is delivered online through a video conferencing platform. This allows you to participate in the training from anywhere in the world. We also offer on-site training for organizations that prefer this option.
Training Schedule
We offer live project training on a variety of schedules, including:
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Weekend training: Classes are held on weekends to accommodate working professionals.
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Weekday training: Classes are held on weekdays during the day or evening.
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Self-paced training: You can learn at your own pace with our online video tutorials.
Training Fees
Our training fees vary depending on the specific program you choose. We offer discounts for early bird registration and group bookings.
