Post Graduate Certificate in Advanced Machine Learning & AI

Architectures of recurrent neural networks and applications in Natural Language Processing (NLP)

Become familiar with the Kaggle platform and understand the lifecycle of a machine learning project

Characteristics of various architectures of deep convolutional neural networks and applications in computer vision

How to apply feature engineering to image and text data

How to build fusion neural networks consisting of CNNs and RNNs

How to build, train, and apply convolution neural networks

How to build, train, and apply fully connected deep neural networks

How to build, train, and apply recurrent neural networks

How to create interactive visualizations using TensorBoard

How to develop Artificial Neural Networks algorithms and concepts

How to evaluate performance of ML models and interpret the results

How to fine-tune Neural Network hyperparameters

How to improve the performance of convolutional neural networks

How to improve the performance of deep neural networks by hyperparameter tuning, regularization and optimization

How to pre-process and prepare data and perform in-depth exploration using Tensorflow and Keras

How to split your data and when to use multi-task, transfer, and end-to-end deep learning

How to train ANN models and make predictions using Tensorflow and Keras

How to train ML models and make predictions using Tensorflow and Keras

How to use the backpropagation algorithm and other modern variants of it

How to work with data and perform data exploration tasks using Tensorflow

How to write code using common Keras functionality

Utilize Transfer Learning

How to write code using common Tensorflow functionality