NOC:Advanced R Programming for Data Analytics in Business

Lecture 1 - Fundamentals of R

Lecture 2 - Data cleaning

Lecture 3 - Data Visualization - Part 1

Lecture 4 - Data Visualization - Part 2

Lecture 5 - Introduction to Probability Theory

Lecture 6 - Conditional Probabilities and Bayes Theorem

Lecture 7 - Random Variables and Probability Distributions

Lecture 8 - Binomial Distribution

Lecture 9 - Continuous Random Variables and Normal Distribution

Lecture 10 - Descriptive Analytics: Measures of Central Tendency

Lecture 11 - Descriptive Analytics: Measures of Variability and Shape

Lecture 12 - Statistical Inference: Sampling

Lecture 13 - Statistical Inference: Central Limit Theorem and Confidence Intervals

Lecture 14 - Statistical Inference: Hypothesis testing

Lecture 15 - Introduction to R

Lecture 16 - Inferential statistics: R Implementation

Lecture 17 - Statistical Inference: Sampling

Lecture 18 - Hypothesis Testing: R Implementation

Lecture 19 - Regression Modelling - Part 1

Lecture 20 - Regression Modelling - Part 2

Lecture 21 - Regression Algorithm: Application - Part 1

Lecture 22 - Regression Algorithm: Application - Part 2

Lecture 23 - Classification Algorithms: Logit/Probit Regression - Part 1

Lecture 24 - Classification Algorithms: Logit/Probit Regression - Part 2

Lecture 25 - Classification Algorithms: Application - Part 1

Lecture 26 - Classification Algorithms: Application - Part 2

Lecture 27 - Advanced Data Visualization - Part 1

Lecture 28 - Advanced Data Visualization - Part 2

Lecture 29 - Introduction to Panel Data Modelling

Lecture 30 - Panel data application and implementation with R

Lecture 31 - Advanced Time-Series Models

Lecture 32 - Introduction to ARMA process

Lecture 33 - Forecasting with ARMA models

Lecture 34 - Non-stationarity, Cointegration, and Error correction Models

Lecture 35 - Return and Volatility Modelling and Forecasting

Lecture 36 - Maximum Likelihood Estimation (MLE)

Lecture 37 - Quantile Regression - Part A

Lecture 38 - Quantile Regression - Part B

Lecture 39 - Solar Panel Marketing Case Study

Lecture 40 - PCA and Clustering - Part 1

Lecture 41 - PCA and clustering - Part 2

Lecture 42 - Tutorial - HR Analytics - Part 1

Lecture 43 - Tutorial - HR Analytics - Part 2

Lecture 44 - Application of Logistic Regression - Part 1

Lecture 45 - Application of logistic regression - Part 2