Lecture 1 - Introduction to Business Forecasting
Lecture 2 - Data Driven Decision Making and Essentials of Predictive Analytics
Lecture 3 - Data Driven Decision Making and Essentials of Predictive Analytics
Lecture 4 - Types of Forecasting: Qualitative Approaches and Quantitative Approaches
Lecture 5 - Components of a Time Series and Measures of Forecast Accuracy
Lecture 6 - Components of a Time Series and Measures of Forecast Accuracy
Lecture 7 - Moving Average Methods: Simple, Weighted, and Exponential Moving Average
Lecture 8 - Moving Average Methods: Simple, Weighted, and Exponential Moving Average
Lecture 9 - Exponential Smoothing
Lecture 10 - Trend Projections and Holt Model
Lecture 11 - Simple Linear Regression and Measure of Goodness and Standard Error
Lecture 12 - Simple Linear Regression and Measure of Goodness and Standard Error
Lecture 13 - Simple Linear Regression and Measure of Goodness and Standard Error
Lecture 14 - Multiple Linear Regression and Multicollinearity
Lecture 15 - Multiple Linear Regression and Multicollinearity
Lecture 16 - Multiple Linear Regression and Multicollinearity
Lecture 17 - Seasonality, Seasonal Index, and Quarterly Average Method
Lecture 18 - Seasonality, Seasonal Index, and Quarterly Average Method
Lecture 19 - Seasonality and Trend: Winter's Holt Method
Lecture 20 - Seasonality and Trend: Winter's Holt Method
Lecture 21 - Multiplicative Decomposition Method
Lecture 22 - Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF)
Lecture 23 - ARIMA: Auto-Regressive (AR) Process
Lecture 24 - ARIMA: Moving Average (MA) Process
Lecture 25 - ARIMA: Auto-Regressive Moving Average (ARMA) Process
Lecture 26 - Auto-Regressive Integrated Moving Average (ARIMA) Model
Lecture 27 - Introduction to Machine Learning
Lecture 28 - Introduction to Machine Learning
Lecture 29 - Logistic Regression
Lecture 30 - Logistic Regression
Lecture 31 - Human Judgment in Time Series Analysis
Lecture 32 - Monte Carlo Simulation: Discrete Case
Lecture 33 - Monte Carlo Simulation: Discrete Case
Lecture 34 - Monte Carlo Simulation: Continuous case
Lecture 35 - System Dynamics (Additional Learning)
Lecture 36 - Predictive Analytics using @Risk Software
Lecture 37 - Predictive Analytics using @Risk Software
Lecture 38 - Predictive Analytics using @Risk Software
