# Course curriculum

• 1

### Module 01: Course Introduction

• Segment - 01 - Introduction
• Segment - 02 - Get Started With the Python Data Science Environment: Anaconda
• Segment - 03 - Anaconda for Mac Users
• Segment - 04 - The iPython Environment
• Segment - 05 - Why PyTorch?
• Segment - 06 - Install PyTorch
• Segment - 07 - Further Installation Instructions for Mac
• Segment - 08 - Working With CoLabs
• 2

### Module 02: Introduction to Python Data Science Packages

• Segment - 09 - Python Packages for Data Science
• Segment - 10 - Introduction to Numpy
• Segment - 11 - Create Numpy Arrays
• Segment - 12 - Numpy Operations
• Segment - 13 - Numpy for Basic Vector Arithmetic
• Segment - 14 - Numpy for Basic Matrix Arithmetic
• Segment - 15 - PyTorch Basics: What Is a Tensor?
• Segment - 16 - Explore PyTorch Tensors and Numpy Arrays
• Segment - 17 - Some Basic PyTorch Tensor Operations
• 3

### Module 03: Other Python Data Science Packages For Dealing With Data

• Segment - 18 - Read in CSV Data
• Segment - 19 - Read in Excel Data
• Segment - 20 - Basic Data Exploration With Pandas
• 4

### Module 04: Basic Statistical Analysis With PyTorch

• Segment - 21 - Ordinary Least Squares (OLS) Regression - Theory
• Segment - 22 - OLS Linear Regression - Without PyTorch
• Segment - 23 - OLS Linear Regression From First Principles - Theory
• Segment - 24 - OLS Linear Regression From First Principles - Without PyTorch
• Segment - 25 - OLS Linear Regression From First Principles - With PyTorch
• Segment - 26 - More OLS With PyTorch
• Segment - 27 - Generalized Linear Models (GLMs) - Theory
• Segment - 28 - Logistic Regression - Without PyTorch
• Segment - 29 - Logistic Regression - With PyTorch
• 5

### Module 05: Introduction to Artificial Neural Networks (ANN)

• Segment - 30 - Introduction
• Segment - 31 - PyTorch ANN Syntax
• Segment - 32- What Are Activation Functions?
• Segment - 33 - More on Back Propagation
• Segment - 34 - Bringing them Together
• Segment - 35 - Setting up ANN Analysis with PyTorch
• Segment - 36 - DNN Analysis with PyTorch
• Segment - 37 - More DNNs
• Segment - 38 - DNNs For Identifying Credit Card Fraud
• Segment - 39 - An Explanation of Accuracy Metrics
• 6

### Module 06: Neural Networks on Images

• Segment - 40 - What are Images?
• Segment - 41 - Read in Images in Python
• Segment - 42 - Basic Image Conversions
• Segment - 43 - Why AI and Deep Learning?
• Segment - 44 - Artificial Neural Networks (ANN) For Image Classification
• Segment - 45 - Deep Neural Networks (DNN) For Image Classification
• 7

### Module 07: Introduction to Artificial Intelligence (AI) and Deep Learning

• Segment - 48 - What is CNN?
• Segment - 50 - More on CNN
• Segment - 51 - Introduction to Transfer Learning: Theory
• Segment - 49 - Implementing CNN on Imaginary Data
• Segment - 52 - Implement CNN Using a Pre-Trained Model