Neural Networks in Python

Does the world of artificial neural networks intrigue you? This free online course is your first step to understanding ANN and deep learning (teaching machines to do what comes naturally to humans). The videos will guide you through this process by helping you to build neural network models using Python. You will then use those models to make near-accurate predictions and use the libraries and data frames in Python to manipulate data.

What You Will Learn In This Free Course

ANN Overview

This module introduces you to Artificial Neural Networks (ANN), starting with the concept of perception, through activation functions, to complex networks. You will also gain a basic understanding of how neural networks are formed, their architecture, and hyperparameters.

Python Crash Course

In this module, you will learn the basics of python, starting from the installation processes. You will get an overview of Anaconda and the Jupyter Notebook. Next, you will see how to run the python commands and functions, including arithmetic and string operators, lists, tuples, and dictionaries.

Neural Network Models

In this module, you will learn how to build simple and complex neural network models. You will start by creating a simple single perceptron classification model. Next, you will install TensorFlow and Keras and use them to create and evaluate models. You will also learn to save and load your model, and use callbacks at each epoch value.

Diploma in Neural Networks in Python – Deep Learning for Beginners – First Assessment

This assessment enables you to review your learning of the first three modules of the course, Diploma in Neural Networks in Python – Deep Learning for Beginners on Alison.com.; Module

Data Preprocessing

In this module, you will learn how to prepare the data for analysis. It starts with the basic theory of a decision tree, where you will learn concepts such as a Data Dictionary and Univariate Analysis. It then covers data pre-processing topics like outlier treatment, missing value imputation, variable transformation, and Test-Train split.

Linear Regression

This module starts with simple linear regression and then covers multiple linear regression in Python. You will begin by understanding the basic concepts and then learn to quantify a model’s accuracy and the meaning of F statistic. You will also learn to interpret the variables in the dataset and the result of the regression problem.

Diploma in Neural Networks in Python – Deep Learning for Beginners – Second Assessment

This assessment enables you to review your learning of the fourth and fifth modules of the course, Diploma in Neural Networks in Python – Deep Learning for Beginners on Alison.com; Module

Course assessment