What is deep learning?

Types of deep learning models

Applications of deep learning

Mathematical foundations of deep learning

Optimization techniques for deep learning

Overview of TensorFlow

TensorFlow tensors and variables

TensorFlow operations and graphs

TensorFlow control flow

TensorFlow data pipelines

Feedforward neural networks

Convolutional neural networks

Recurrent neural networks

Autoencoders

Generative adversarial networks

Word embedding

Recurrent neural networks for NLP

Convolutional neural networks for NLP

Attention mechanisms

Transformers

Image classification

Object detection

Image segmentation

Generative models for CV

Speech recognition

Time series forecasting

Recommender systems

Anomaly detection

Model evaluation

Hyperparameter tuning

Experiment tracking

Productionizing deep learning models

Students will work on individual or group projects to apply deep learning to solve real-world problems restricted to Nigeria.