Modules / Lectures


Sl.No Chapter Name MP4 Download
1Lec 1: Rules of probabilityDownload
2Lec 44: Higher-dimensional data in biologyDownload
3Lec 2: Discrete probability distributionDownload
4Lec 45: Principle component analysisDownload
5Lec 3: Continuous probability distributionDownload
6Lec 46: Principle component analysis using RDownload
7Lec 4: Moments: mean and varianceDownload
8Lec 47: t-SNEDownload
9Lec 5: Moments: variance and covarianceDownload
10Lec 48: t-SNE using RDownload
11Lec 6: Bayes theorem and likelihoodDownload
12Lec 49: Diffusion mapsDownload
13Lec 7: Concept of statistical testsDownload
14Lec 8: Vector and vector operationsDownload
15Lec 9: Matrix and matrix operationsDownload
16Lec 10: Determinant and Inverse of a matrixDownload
17Lec 11: Eigenvalue and eigenvectorDownload
18Lec 12: Linear system of equationsDownload
19Lec 13: Singular value decompositionDownload
20Lec 14: Getting ready with RDownload
21Lec 15: Algebraic and logical operations in RDownload
22Lec 16: Reading and writing dataDownload
23Lec 17: Statistics using R – descriptive statisticsDownload
24Lec 18: Statistics using R – t-test and ANOVADownload
25Lec 19: Linear algebra using RDownload
26Lec 20: Scatter plot, Line plot & Bar plotDownload
27Lec 21: Histogram & Box plotDownload
28Lec 22: Heatmap and Volcano plotDownload
29Lec 23: Network visualizationDownload
30Lec 24: Data visualization using ggplot2 - IDownload
31Lec 25: Data visualization using ggplo2 - IIDownload
32Lec 26: CorrelationsDownload
33Lec 27: Linear regression - IDownload
34Lec 28: Linear regression - IIDownload
35Lec 29: Linear regression using RDownload
36Lec 30: Multiple linear regressionDownload
37Lec 31: Multiple linear regression using RDownload
38Lec 32: Nonlinear regressionDownload
39Lec 33: Nonlinear regression using RDownload
40Lec 34: Clustering and classificationDownload
41Lec 35: Logistic regressionDownload
42Lec 36: Logistic regression using RDownload
43Lec 37: Distance mesaures for clusteringDownload
44Lec 38: k-means clusteringDownload
45Lec 39: k-means clustering using RDownload
46Lec 40: Hierarchical clusteringDownload
47Lec 41: Hierarchical clustering using RDownload
48Lec 42: Decision tree classifierDownload
49Lec 43: Support vector machinesDownload

Sl.No Chapter Name English
1Lec 1: Rules of probabilityDownload
Verified
2Lec 44: Higher-dimensional data in biologyPDF unavailable
3Lec 2: Discrete probability distributionDownload
Verified
4Lec 45: Principle component analysisPDF unavailable
5Lec 3: Continuous probability distributionDownload
Verified
6Lec 46: Principle component analysis using RPDF unavailable
7Lec 4: Moments: mean and varianceDownload
Verified
8Lec 47: t-SNEPDF unavailable
9Lec 5: Moments: variance and covarianceDownload
Verified
10Lec 48: t-SNE using RPDF unavailable
11Lec 6: Bayes theorem and likelihoodDownload
Verified
12Lec 49: Diffusion mapsPDF unavailable
13Lec 7: Concept of statistical testsPDF unavailable
14Lec 8: Vector and vector operationsDownload
Verified
15Lec 9: Matrix and matrix operationsDownload
Verified
16Lec 10: Determinant and Inverse of a matrixPDF unavailable
17Lec 11: Eigenvalue and eigenvectorPDF unavailable
18Lec 12: Linear system of equationsPDF unavailable
19Lec 13: Singular value decompositionPDF unavailable
20Lec 14: Getting ready with RDownload
Verified
21Lec 15: Algebraic and logical operations in RDownload
Verified
22Lec 16: Reading and writing dataDownload
Verified
23Lec 17: Statistics using R – descriptive statisticsPDF unavailable
24Lec 18: Statistics using R – t-test and ANOVAPDF unavailable
25Lec 19: Linear algebra using RPDF unavailable
26Lec 20: Scatter plot, Line plot & Bar plotPDF unavailable
27Lec 21: Histogram & Box plotPDF unavailable
28Lec 22: Heatmap and Volcano plotPDF unavailable
29Lec 23: Network visualizationPDF unavailable
30Lec 24: Data visualization using ggplot2 - IPDF unavailable
31Lec 25: Data visualization using ggplo2 - IIPDF unavailable
32Lec 26: CorrelationsPDF unavailable
33Lec 27: Linear regression - IPDF unavailable
34Lec 28: Linear regression - IIPDF unavailable
35Lec 29: Linear regression using RPDF unavailable
36Lec 30: Multiple linear regressionPDF unavailable
37Lec 31: Multiple linear regression using RPDF unavailable
38Lec 32: Nonlinear regressionPDF unavailable
39Lec 33: Nonlinear regression using RPDF unavailable
40Lec 34: Clustering and classificationPDF unavailable
41Lec 35: Logistic regressionPDF unavailable
42Lec 36: Logistic regression using RPDF unavailable
43Lec 37: Distance mesaures for clusteringPDF unavailable
44Lec 38: k-means clusteringPDF unavailable
45Lec 39: k-means clustering using RPDF unavailable
46Lec 40: Hierarchical clusteringPDF unavailable
47Lec 41: Hierarchical clustering using RPDF unavailable
48Lec 42: Decision tree classifierPDF unavailable
49Lec 43: Support vector machinesPDF unavailable


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4HindiNot Available
5KannadaNot Available
6MalayalamNot Available
7MarathiNot Available
8TamilNot Available
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