deep learning

Course Features

Skill level:

Intermediate

Duration:

 3 Months

Projects:

 Yes

Practical Ratio:

 30 : 70

Assessments:

 Yes

Quizzes:

 Yes

Course Details

Deep Learning is one of the most required skill in the industry and we are here to help you master deep learning and build a career in artificial intelligence.

Prerequisite

Language: Python or R.
Theory: Machine Learning Concepts.

Course Outcome

At the end of the course, you should be able to :

  • Gain a deep insight in Tensorflow and its execution.
  • Master & comprehend advanced topics like convolutional and recurrent neural networks & training deep networks.
  • Troubleshooting & improve deep learning models
  • Build your own deep learning project and how to deploy them to Production
  • Fine tuning Deep Learning Models

Curriculum

  • Maths Overview for DL
  • Current State of Tools & Platforms
  • Deep Learning Concepts
  • Activation Functions
  • Learning Mechanisms & Cost Functions
  • Gradient Descent
  • Regularization, Normalizations & Dropouts
  • Mini Batch & Optimization of Networks
  • Architecture; Pooling & FC Layers
  • Different Flavours of CNN
  • Layers optimization
  • Popular CNN Models
  • Attention Mechanism
  • Image Detection & Localization; Segmentation Networks
  • Object Detection at embedded hardware
  • Transfer Learning
  • Using CNN’s for NLP
  • New Research & State-of-art’ s
  • Basic Network Architecture
  • LSTM’s
  • GRU & Attention Models
  • Sequence Modelling with other RNN flavours
  • RNN and NLP
  • Encoder & Decoder
  • New Research & State-of-art’ s
  • DBN’s & RBM’s
  • Generative Adversarial Networks
  • Deep Reinforcement Learning
  • Auto-Encoders
  • Clustering