This comprehensive online course on time series analysis will take you on a journey from understanding the fundamental concepts to applying advanced techniques in real-world scenarios. Whether you're a data scientist, analyst, or researcher, this course is designed to equip you with the knowledge and skills to effectively analyze and forecast time-dependent data.
Through a combination of theoretical explanations, hands-on exercises, and practical examples using popular programming languages like R, you'll gain the confidence to tackle complex time series problems and make data-driven decisions.
What will You Learn?
What is Time Series and Times Series Analysis
Purpose of Time Series Analysis
Application of Time Series Analysis
Important Elements of Time Series Analysis
Trend, Seasonality, Cyclicity and Irregularity
Decomposition of Time Series Elements
Stationary Vs. Non-stationary
Why Stationary is important
Types of Model - Autoregressive (AR) and Moving Average (MA)
ACF and PACF
Use Case using R
Forecasting using R
Requirements
Anyone can Join
Computer/ Laptop
Devote time to perform tasks given during the sessions
Audience
Business Analyst/ Data Analyst/ Data Scientist Aspirants
Suitable for both beginners
Students that want to be in the top 10% of Business Data Analysts
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