# Introduction to Deep Learning Course

## Course Description

In this full-day introductory workshop, youâ€™ll learn the basics of deep learning by training and deploying neural networks.

## Learning Outcomes

By the end of this course, participants will be able to:

- Implement common deep learning workflows using Tensorflow Keras framework.
- Experiment with data, training parameters, network structure, and other strategies to increase performance and capability.
- Deploy your neural networks to start solving real-world problems.

## Pre-requisites

- Basic knowledge of the Python programming language.

## Overview

## 01: Introduction to Deep Learning

## Lab 01: Introduction to Tensorflow Keras

## 02: Neural networks

## Lab 02: Classifying images of clothing

## 03: Classification and Convolutional Neural Networks

## Lab 03: Image classification with CNNs

## 04: Refining the model

## Lab 04: Dogs & Cats with data augmentation

### 4a Without Data augmentation

### 4b With Data augmentation

## 05: Deployment & Transfer Learning

## Lab 05: Tensorflow hub and Transfer learning

## Lab 06: Saving and Loading models

## 06: DL in other fields

## Lab 07: Final exercise, flowers with data augmentation

## Extra Lab 02: Handwritten digits generation with DCGAN