Modules / Lectures
Module NameDownloadDescriptionDownload Size
Week 1Week 0 Assignment 1Week 0 Assignment 1332 kb
Week 1Week 1 Assignment 1Week 1 Assignment 1293 kb
Week 2Week 2 Assignment 1Week 2 Assignment 1347 kb
Week 3Week 3 Assignment 1Week 3 Assignment 1339 kb
Week 4Week 4 Assignment 1Week 4 Assignment 1364 kb
Week 5Week 5 Assignment 1Week 5 Assignment 1334 kb
Week 6Week 6 Assignment 1Week 6 Assignment 1210 kb
Week 7Week 7 Assignment 1Week 7 Assignment 1338 kb
Week 8Week 8 Assignment 1Week 8 Assignment 1241 kb


New Assignments
Module NameDownload
noc19_cs13-assessmentid-101noc19_cs13-assessmentid-101
noc19_cs13-assessmentid-102noc19_cs13-assessmentid-102


Sl.No Chapter Name MP4 Download Transcript Download
1Data science for engineers Course philosophy and expectation DownloadDownload
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2Introduction to R DownloadDownload
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3Introduction to R (Continued)DownloadDownload
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4Variables and datatypes in RDownloadDownload
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5Data framesDownloadDownload
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6Recasting and joining of dataframesDownloadDownload
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7Arithmetic,Logical and Matrix operations in RDownloadDownload
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8Advanced programming in R : FunctionsDownloadDownload
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9Advanced Programming in R : Functions (Continued)DownloadDownload
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10Control structures DownloadDownload
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11Data visualization in R Basic graphicsDownloadDownload
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12Linear Algebra for Data scienceDownloadDownload
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13Solving Linear EquationsDownloadDownload
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14Solving Linear Equations ( Continued )DownloadDownload
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15Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,EigenvectorsDownloadDownload
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16Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors ( Continued 1)DownloadDownload
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17Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors ( Continued 2 )DownloadDownload
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18Linear Algebra - Distance,Hyperplanes and Halfspaces,Eigenvalues,Eigenvectors ( Continued 3 )DownloadDownload
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19Statistical ModellingDownloadDownload
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20Random Variables and Probability Mass/Density FunctionsDownloadDownload
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21Sample Statistics DownloadDownload
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22Hypotheses TestingDownloadDownload
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23Optimization for Data ScienceDownloadDownload
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24Unconstrained Multivariate OptimizationDownloadDownload
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25Unconstrained Multivariate Optimization ( Continued )DownloadDownload
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26Gradient ( Steepest ) Descent ( OR ) Learning RuleDownloadDownload
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27Multivariate Optimization With Equality ConstraintsDownloadDownload
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28Multivariate Optimization With Inequality ConstraintsDownloadDownload
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29Introduction to Data ScienceDownloadDownload
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30Solving Data Analysis Problems - A Guided Thought ProcessDownloadDownload
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31Module : Predictive ModellingDownloadDownload
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32Linear RegressionDownloadDownload
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33Model AssessmentDownloadDownload
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34Diagnostics to Improve Linear Model FitDownloadDownload
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35Simple Linear Regression Model BuildingDownloadDownload
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36Simple Linear Regression Model AssessmentDownloadDownload
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37Simple Linear Regression Model Assessment ( Continued )DownloadDownload
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38Muliple Linear RegressionDownloadDownload
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39Cross ValidationDownloadDownload
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40Multiple Linear Regression Modelling Building and SelectionDownloadDownload
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41ClassificationDownloadDownload
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42Logisitic RegressionDownloadDownload
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43Logisitic Regression ( Continued )DownloadDownload
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44Performance MeasuresDownloadDownload
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45Logisitic Regression Implementation in RDownloadDownload
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46K - Nearest Neighbors (kNN)DownloadDownload
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47K - Nearest Neighbors implementation in RDownloadDownload
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48K - means ClusteringDownloadDownload
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49K - means implementation in RDownloadDownload
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50Data Science for engineers - SummaryDownloadDownload
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