INTRODUCTION TO THE COURSE: The Key Concepts and Software Tools
  • Introduction to the Course
  • Data and Scripts For the Course
  • Installing R and R Studio
  • Read in CSV & Excel Data
  • Remove Missing Values
  • More Data Cleaning
  • Exploratory Data Analysis(EDA): Basic Visualizations with R
Start With Time Series Data
  • Works With Dates in R
  • Pre-Processing Data With Times
  • Visualize Temporal Data in R
  • Components of Time Series Data
  • Moving Averages (MA) For Visualizing a Trend/Pattern
  • Detecting Significant Trend
  • Other Ways Of Identifying Trend in Time Series Data
  • Visualize Monthly Temporal Data
  • Identify Cyclical Behavior with Fourier Transforms
  • STL Decomposition
  • Work With Seasonality
Important Pre-Conditions of Time Series Modelling
  • Is My Time Series Stationary?
  • Differencing: Make A Non-Stationary Time Series Stationary
  • Make the Mean & Variance Constant
  • Seasonal Differencing
  • Detrending Time Series With Linear Regression
  • Detrending Time Series With Mean Subtraction
Time Series Based Forecasting
  • Simple Exponential Smoothing for Short Term Forecasts
  • Other Basic Forecasting Techniques
  • Moving Averages (MA) For Forecasting
  • Simple Moving Average
  • Theta Lines For Forecasting
  • Forecasting On the Fly
  • Linear Regression For Predicting Values As a Function of Time
  • Linear Regression For Forecasting With Trend & Seasonality
  • Lags
  • Weekly Lags
  • Lagged Regression
  • Automatic ARIMA Model Fitting and Forecasting
  • Automatic ARIMA With Real Life Data
  • ARIMA With Fourier Terms
  • BATS For Forecasting
Machine Learning Techniques For Time Series Data
  • Linear Regression With "timetk"
  • Linear Regression On Real Data
  • Machine Learning Regression Models for Non-Parametric Data For Forecasting
  • XGBoost For Time Series Forecasting
  • Theory Behind ANN (Artificial Neural Network) and DNN (Deep Neural Networks)
  • Neural Network for Forecasting
  • RNNs With Temporal Data
  • Evaluate the Performance of an RNN Model
Detecting Sudden Changes/Major Events
  • Detect An Anomaly in Time Series Data
  • Breaks For Additive Season and Trend (BFAST) For Time Series in R
  • Structural Change Detection
  • Structural Changes in Forex Regime
  • Github