Deep Learning / Machine Learning

Beginners' content:

• Deep Learning for Computer Vision
  
• Understand general terms and background of deep learning
• Implement common deep learning workflows such as Image Classification and Object Detection
• Manipulate training parameters to improve accuracy
• Modify internal layers of neural networks to adapt to new problems
• Deploy your networks to start solving real-world problems

Intermediate content:

• Deep Learning for Multiple Data Types
  
• Implementing deep learning workflows like image segmentation and text generation
• Comparing and contrasting data types, workflows, and frameworks
• Combining computer vision and natural language processing
• Modify Tensorflow / Pytorch code using Python 

Advanced content:

• Deep Learning for Multi-GPUs

• Approaches to multi-GPUs training

• Algorithmic and engineering challenges to large-scale training

• Key techniques used to overcome the challenges mentioned above

• Deep Learning on HPC clusters