Business Intelligence and Data Science

Business Intelligence is a set of processes, architectures, and technologies that convert raw data into meaningful information that drives profitable business actions. It is a suite of software and services to transform data into actionable intelligence and knowledge. BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts and maps to provide users with detailed intelligence about the state of the business. Data Science will develop necessary skills among students to empower them with ability to gain insights and understanding from data. Students will be able to use statistical analysis, quantitative techniques, explanatory, and predictive modelling on data to generate information and insights to help make actionable decisions.

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Lecture NameDownload
Course OutlineBIDS- Course Outline - IPM_v0.02(1).docx
Session 1,2 and 3 - AritraSession 1-3 IPM.pptx
Session 4 to 7 - AritraSession 4 to 7.pptx
Session 4 to 7 Datasets - AritraWeekday.csv
Session 4 to 7 Datasets - AritraWeekend.csv
Session 4 to 7 Problem Set - AritraProblem for Practice.pdf
Session 4 to 7 R Package Installations - Aritrapackages for installations.txt
Session 8 and 9 DeckSession 8 and 9.pptx
Session 8 and 9 Dataset Economiceconomics_data.RData
Session 8 and 9 Dataset Economic DDEconomics Data Description.txt
Session 8 and 9 Dataset Waffle DivorceWaffle_Divorce.RData
Session 8 and 9 Dataset Waffle Divorce DDWaffle Divorce Data Description.txt
Session 8 and 9 Dataset Credit Card 1Customer Acqusition.csv
Session 8 and 9 Dataset Credit Card 2Repayment.csv
Session 8 and 9 Dataset Credit Card 3spend.csv
Session 8 and 9 Dataset Credit Card DDDD.txt
Session 8 and 9 Dataset Healthcaredata.csv
Session 8 and 9 Dataset Healthcare DDdata_dictionary.csv
Session 8 and 9 Dataset Healthcare DD 2DD.txt
Session 10 to 13 DeckSession 10 to 13.pptx
Session 10 to 13 NB ComputationNaive Bayes.xlsx
Session 10 to 13 Datacustomer_personality.csv
Session 10 to 13 Code Customer Personalitycustomer_personality.R
Session 10 to 13 Code GroceryGrocery_data.r
Session 14 to 17 DeckRegression.pptx
Data for Regression - Data 1scatterplot_data.xlsx
Data for Regression - Data 2data for regression.csv
Data for Regression - Data 3advertising.csv
Data for Regression - Data Description Data 2data for regression DD.txt
Data for Regression - CodeCode2.R
Session 10 to 13 Naive Bayes New Example and CompuNaive Bayes New Example.pptx
Session 18 to 20 DeckClustering.pptx
Session 18 to 20 DataWholesale customers data.csv
Session 18 to 20 Data DescriptionWholesale customers data DD.txt
Session 18 to 20 Codeclustering.R
Quiz 2 - BIDSQuiz 2.pdf