DEEP LEARNING
16153
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DEEP LEARNING

DEEP LEARNING
OBJECTIVES

The objective of this training program is to equip participants with a strong foundation in deep learning and computer vision, enabling them to build and deploy models that can analyze and interpret images, videos, and other visual data.

OUTCOMES
  • Understand the basics of deep learning and neural networks
  • Build and train deep learning models for computer vision tasks, such as image classification, object detection, and segmentation
  • Apply computer vision techniques for tasks such as face recognition, image registration, and optical flow analysis
  • Use libraries and frameworks such as TensorFlow, PyTorch, OpenCV, and scikit-learn
  • Create end-to-end deep learning and computer vision projects
  • Debug and optimize deep learning and computer vision models
SCOPE
  • Computer vision engineer
  • Deep learning engineer
  • Research scientist
  • Data scientist
  • Machine learning engineer
PROJECTS
  • Building a convolutional neural network (CNN) for image classification
  • Using transfer learning to train an image recognition model
  • Building a face recognition system using OpenCV and deep learning
  • Building an object detection and tracking system for surveillance video
  • Building a lane detection system for self-driving cars