ruby.tar.gz

Learn how to identify anomalies in your data using SQL. Understand how to apply mathematical concepts such as mean, standard deviation, and z-score to detect when an anomaly occurred in your data and how to investigate past data to improve and refine the model.

Simple Anomaly Detection using SQL

## Target audience

The course is intended for people with an introductory level understanding of SQL and a good grip on intermediate mathematical concepts. 

## Topics

This course will be using data from server logs for anomaly detection. We will start by forming a basic intuition of what constitutes an "anomaly" and the mathematical significance of the "z-score." 

You will learn to understand the data at hand and how you can use data driven and mathematical techniques to best find anomalies and eventually improve the accuracy of the process. 

## Conventions

This course will follow an interactive hands-on convention with multiple coding examples and graphical illustrations to help with understanding the core concepts this course aims to convey. 

# Target audience

The course is intended for people with an introductory level understanding of SQL and a good grip on intermediate mathematical concepts. 

# Topics

This course will be using data from server logs for anomaly detection. We will start by forming a basic intuition of what constitutes an "anomaly" and the mathematical significance of the "z-score." 

You will learn to understand the data at hand and how you can use data driven and mathematical techniques to best find anomalies and eventually improve the accuracy of the process. 

# Conventions

This course will follow an interactive hands-on convention with multiple coding examples and graphical illustrations to help with understanding the core concepts this course aims to convey. 

Detecting Anomalies

Analyzing A Server Log

Backtesting

Improving Accuracy

Introduction

Target audience

Topics

Conventions