This course is suitable for people who understand machine learning concepts and have little/no idea of Neural networks. Also, the learner should have basic programming knowledge in python. This course covers the following

1. Neural network Basics(working).

2. Various neural networks(MLP, RNN, CNN, LSTM, Transformers).

3. Coaching with examples from live use cases(banking and financial domain).

4. INtroduction to and familiarise with deep learning frameworks such as Tensorflow/Pytorch

5. Homework assessments from real-world business use cases.

At the end of the course, the learner will have a clear understanding of how Neural networks operate and how to solve business use cases using the various algorithms available. The learning will be able to train a model using Neural networks on real data, optimize the model, tune hyperparameters and perform various tasks like Batch normalization to improve the performance of the model. The learning will also be comfortable using Tensorflow framework for developing Deep learning models.