Introduction to Time Series Analysis

8 hours of instruction

Learn how to apply time series basics and concepts to create accurate forecasts for their organizations and make better decisions when developing strategies.

OBJECTIVES

1. Explore the components and core concepts used in time series analysis and modeling
2. Process, clean, and format time series data for analysis
3. Visualize time series data for different time periods using line and box plots

PREREQUISITES

Data Wrangling in Python

SYLLABUS & TOPICS COVERED

1. Basics
   • Time series analysis definition and use cases
   • What makes data a time series
   • Basics and components of time series modeling
   • Visualize time series data
2. Concepts
   • Core concepts in time series analysis: random walk, stationarity, moving averages, trend, and
3. Seasonality
   • Deconstruct time series into its components

SOFTWARE REQUIREMENTS

You will have access to a Python-based JupyterHub environment for this course. No additional download or installation is required.