Ivy s Business Analytics Certification Programme Details (Module I + II+ III + IV)

Transcription

1 Ivy s Business Analytics Certificatin Prgramme Details (Mdule I + II+ III + IV) Based n Industry Cases, Live Exercises, & Industry Executed Prjects Mdule (I) - Analytics Essentials 81 hrs 1. Statistics Refresher Overview (6 Hrs) Ppulatin metrics: Mean, Median, Mde, Std Deviatin, Variance, C-variance Intrductin t types f distributins Nrmal, Pissn, Binmial, Gamma Hypthesis Testing t Test, F Test etc Ordinary Least Squares methd fr regressin 2. Advanced Analysis & Reprting n Excel using VBA, Macrs (45 hrs) Intrductin t MS Excel, Basic Functins and Usage Srting, Filtering, Advance Filtering, Subttal Pivt Tables Data Entry Frms What-if-Analysis Data Tables, Scenari Manager & Gal Seek Different Charts Graphs Which ne t use and when Vlkup, Hlkup, Match, Index Style & Number Frmatting, Cnditinal Frmatting Wrksheet & Wrkbk Reference Smart Printing Optins Lgical Operatrs & Functins IF and Nested IF Data Validatin Text Functins Relative & Abslute Macr Recrding VBA Prgramming Making Macr d Autmated Tasks fr Yu Recrd a Macr Autmate a Task using Macr Analysis Using VBA Objects VBA Cllectin Objects The Applicatin Object Wrkbk and Windw Objects The Range Objects Variable, Data Types, and Cnstants Types f Variables Prmting fr User Input Arrays Interacting with Users VBA Sub, Event and Functin Prcedures Create Sub Prcedures, Event Prcedures and Functin Prcedures - 1 -

2 Ways t Execute these Prcedures Hw t Execute Functin Prcedures Cntrl Lgic and Lps Cnditinal Lgic Cnditinal Statements and the If/Then/Else and Select/Case Cde Structures Lping VBA User Frms Overview Industry Prjects using VBA 3. SQL based Relatinal Database Cncepts using MS-Access (15 hrs) Relatinal Database Fundamentals Steps t Design Efficient Relatinal Database Mdels Case Studies n Designing Database Mdels Case Study Implementatin n Handling Data in MS-Access 2007 Imprting / Exprting Large Amunt f Data int/frm MS-Access Intr t SQL Statements Writing Transactinal SQL Queries, Merging, jining, srting, indexing, etc. Hands-n Exercises n Manipulating Data Using SQL Queries Creating Database Mdels Using SQL Statements Individual Prjects n Handling SQL Statements 4. Structured Thinking Wrkshps (9 Hrs) Analytical Prblem Slving Skills, Creative Thinking, Rt Cause Analysis, Decisin Tree Analysis, Fish Bne Analysis, Mind Mapping, Mint Pyramid s Principle, etc. Techniques t Handle Case Based Interviews Grup / Individual Exercises / Case Studies 5. Effective Interviewing Skills Wrkshp (3 Hrs) Myths abut Interviews and Cmmn Mistakes Cnvincing the Interviewer Crrect Preparatin fr Interview and its Advantages The 4 Steps t Interview Success Cmpnents f Gd Interview Hw t face cmmn interview questins 6. Analytics Industry Resume Building Wrkshp (3 Hrs) What d Analytics Recruiters Lk fr in a Resume? Analytics Resume Best Practices Analytics Industry Keywrds t Include in Resume Hw t Describe Relevant Analytics Prjects in Resume? - 2 -

3 Effective Strategies t Get Yur Resume Nticed 7. Ivy s Career Center Wrkshps (These wrkshp hurs are nt cunted twards the ttal duratin) Industry Netwrking Sessins with At Least Tw Industry Guest Speakers Mck Interview Sessins with Industry Prfessinals Analytics Cmpany-wise Interview Questins (Cllected frm ur Alumni and Recruiters) Cmprehensive Analytics Interview Questin Banks (SAS, VBA, Behaviral, etc) - 3 -

4 (Mdule II)- Industry Applicable Cre Analytics with Case Studies (21 Hrs) 1. Imprtance f Data fr Management Decisins Data Types Classifying Data t Cnvey Meaning Diagrammatic and Graphic Representati n Measures f Central Tendency and Dispersin Data Mdeling Ratis and Index Numbers Discussin with cases and examples 2. Time Series Analysis Mathematical Mdels fr Time Series Measurement f Seasnal, Cyclical and Irregular Variatins Discussin with cases and examples 3. Prbability Cncepts and Applicatins Bayesian Thery Prbability Distributins and Mathematical Expectatin Discussin with cases and examples 4. Basics f Sampling and Sampling Distributin 5. Thery f Estimatin and Testing f Hypthesis Discussin with cases and examples 6. Crrelatin and Regressin Mdels 7. Frecasting Discussin with cases and examples 8. Thery f Attributes Discussin with cases and examples 9. Statistical Decisin Analysis Discussin with cases and examples 10. Analysis f Variance Discussin with cases and examples 11. Multivariate Analysis Discussin with cases and examples - 4 -

5 Mdule (III) - Advanced Analytics using SAS 9 (Base, Advance and Stats Mdeling) 63 hrs 1. SAS Analytics Intrductin t SAS & Data Prcessing, SAS Data steps SAS Functins Types f variables, Variable Frmats SAS prcedures including Prc SQL SAS Macrs Statistical Mdelling Cncepts and Practical Assignments - Regressin ARIMA Clustering Lgistic Time Series Analysis Handling Data in SAS Case Studies I, II, and III Assignments / Exercises 2. Industry Executed Analytics Prjects n SAS Dedicated Practice Sessins n Industry Scenaris in SAS Industry Executed Predictive Mdeling Prjects in SAS (5 Prjects frm Retail, Healthcare, Finance, Educatin, Aviatin industries) Please Nte: Fr minute details n any f the abve mdules, please reach ut t us thrugh phne ( / ) r (inf@ivyprschl.cm)

6 Mdule (IV): Data Management & Analysis using R 30 hrs Curse Outline Data Handling, Visualizatin and Statistical Mdeling in R Data Handling and Visualizatin in R Intrductin and Overview f R Package Data Cleaning and Management in R Lgic Building in R Data Visualizatin in R Exercise: Data Summarizatin using Financial Retail Datasets Data Mdeling & Statistics Refresher Data Mdeling Techniques Overview Missing Imputatins Multi-cllinearity Check Hypthesis Testing In-Case Study: Academic Perfrmance Case Study Self-Case Study: Health Care Case Study Linear Regressin Regressin BLUE Prperty Residual Analysis Multiple Regressin Mdel Building In-class Case Study: Predict Academic Perfrmance f Schl Students Self Case Study: Predict Custmer Value fr an Insurance Firm Lgistic Regressin Mdel thery, Mdel Fit Statistics Reject Reference, Binning, Classing Dummy Creatin, Dummy Crrelatin Mdel Develpment (Multiclinearity, WOE, IV, HLT, Gini KS, Rank Ordering, Clustering Check) Mdel Validatin (Rerun, Scring) Final Dashbard In-class Case Study: Predict Custmer Churn fr a Telecm firm Self Case Study: Predict Prpensity t Buy Financial Prduct amng Existing Bank Custmers Factr Analysis & Clustering Factr Analysis Cluster Analysis In-class & Self Case Study: Lan Dataset Time Series / ARIMA Frecasting Univariate Time Series ARIMA In-class Case Study: Frecast Gld Prices Self Case Study: Frecast US Treasury Bnd Prices Text Mining & Analysis - 6 -

7 Extract & Prcess Unstructured Text Data frm Scial Media Channels Hw t Chse Crrect Statistical Tls fr Text Analysis In-class Case Study: Brand Specific Twitter Stream Data Self Case Study: Brand Impact f Maggi Disaster n Nestle Intrductin t Machine Learning Hw des Machine Learning Wrk? ML using Randm Frest In-class Case Study: Create Ideal Hme Buyer Prfile - 7 -