Data Analytics with Python

Data Analytics with Python

Lec 1, Introduction to Data Analytics

Lec 2, Python Fundamentals -I

Lec 3, Python Fundamentals -II

Lec 4, Central Tendency and Dispersion - I

Lec 5, Central Tendency and Dispersion - II

Lec 6, Introduction to Probability-I

Lec 7, Introduction to Probability-II

Lec 8, Probability Distribution - I

Lec 9, Probability Distribution - II

Lec 10, Probability Distributions - III

Lecture 11, Python Demo for Distribution

Lec 12, Sampling and Sampling Distribution

Lec 13, Distribution of Sample Means, population, and variance

Lec 14: Confidence interval estimation: Single population - I

Lec 15, Confidence Interval Estimation: Single Population - II

Lec 16, Hypothesis Testing- I

Lec 17, Hypothesis testing- II

Lec 18, Hypothesis Testing-III

Lec 19, Errors in Hypothesis Testing

Lec 20, Hypothesis Testing about the Difference in Two Sample Means

Lec 21, Hypothesis testing : Two sample test -II

Lec 22, Hypothesis Testing: Two sample test - III

Lec 23, ANOVA- I

Lec 24, ANOVA- II

Lec 25, Post Hoc Analysis(Tukey’s test)

Lec 26, Randomize block design (RBD)

Lec 27, Two Way ANOVA

Lec 28, Linear Regression - I

Lec 29, Linear Regression - II

Lec 30, Linear Regression-III

Lec 31, Estimation, Prediction of Regression Model Residual Analysis

Lec 32, Estimation, Prediction of Regression Model Residual Analysis - II

Lec 33, MULTIPLE REGRESSION MODEL - I

Lec 34, MULTIPLE REGRESSION MODEL-II

Lec 35, Categorical variable regression

Lec 36, Maximum Likelihood Estimation- I

Lec 37, Maximum Likelihood Estimation-II

Lec 38, LOGISTIC REGRESSION- I

Lec 39, LOGISTIC REGRESSION-II

Lec 40, Linear Regression Model Vs Logistic Regression Model

Lec 41, Confusion matrix and ROC- I

Lec 42, Confusion Matrix and ROC-II

Lec 43, Performance of Logistic Model-III

Lec 44, Regression Analysis Model Building - I

Lec 45, Regression Analysis Model Building (Interaction)- II

Lec 46, Chi - Square Test of Independence - I

Lec 47, Chi-Square Test of Independence - II

Lec 48, Chi-Square Goodness of Fit Test

Lec 49, Cluster analysis: Introduction- I

Lec 50, Clustering analysis: part II

Lec 51, Clustering analysis: Part III

Lec 52, Cluster analysis: Part IV

Lec 53, Cluster analysis: Part V

Lec 54, K- Means Clustering

Lec 55, Hierarchical method of clustering -I

Lec 56, Hierarchical method of clustering- II

Lec 57, Classification and Regression Trees (CART : I)

Lec 58, Measures of attribute selection

Lec 59, Attribute selection Measures in CART : II

Lec 60, Classification and Regression Trees (CART) - III