Time Series Analysis with Python

Description

In this course, you will :

• A working knowledge of time series data analysis concepts like stationarity, autocorrelation, and seasonality.
• Working knowledge of Python time series data analysis libraries such as Pandas and NumPy.
• Python experience analysing and forecasting time series data.
• Capability to forecast time series data using statistical modelling approaches such as ARIMA.
• Advanced methodologies for time series data processing, such as machine learning algorithms and neural networks, are required.

Syllabus :

• Introduction to Time Series
• Python Basics for Time Series
• Time Series Analysis
• Basic Time Series Forecasting
• Advanced Time Series Forecasting
• Forecast Evaluation
• Time Series Analysis and Forecasting