Data Science using SAS & R A comprehensive, job-oriented training program crafted by experts

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1 Data Science using SAS & R A comprehensive, job-oriented training program crafted by experts Disclaimer: This material is protected under copyright act AnalytixLabs, Unauthorized use and/ or duplication of this material or any part of this material including data, in any form without explicit and written permission from AnalytixLabs is strictly prohibited. Any violation of this copyright will attract legal actions

2 About AnalytixLabs AnalytixLabs is a capability building and training solutions firm led by McKinsey, IIM, ISB and IIT alumni with deep industry experience and a flair for coaching. We are focused at helping our clients develop skills in basic and advanced analytics to enable them to emerge as Industry Ready professionals and enhance career opportunities. AnalytixLabs has been also featured as top institutes by prestigious publications like Analytics India Magazine and Higher Education Review, since Bottom line Approach focus on practical & theory Personal attention and Individual counselling Industry best practices Content World class course structure Surpasses industry requirements Cater to Standard certifications High quality course material and real life case studies Faculty Seasoned analytics professionals Together we have 30 + years of experience with prestigious firms, like McKinsey, KPMG, Deloitte and AOL Regular sessions by industry experts Job-oriented training Lucrative job prospects in high growth domain Support for relevant certifications and diplomas Career counseling and planning Value for money with high return on investment

3 Global Data science and Big Data skill gap McKinsey Global Institute estimates a shortage of nearly 1.7 million big data talents by This includes a shortage of 140,000 to 190,000 workers with deep technical and analytical expertise, and a shortage of 1.5 million managers and analysts equipped to work with and use big data outputs

4 Candidates trained by us are working in leading companies across industries

5 Data Science using SAS and R is a comprehensive program with following modules, weekly assignments and case studies Module 1 Module 2 Module 3 Module 4 MS Excel 6 hours + Practice exercises Basic data handling to advanced mathematical and logical functions SAS Base & Advanced 24 hours + Practice Hands-on training on SAS & SQL for data mining & analytics reporting R Foundation 12 hours + Practice Hands-on training on R packages for data mining & analytics reporting Business Analytics using SAS & R 33 hours Basic and advanced analytics techniques with applications Crafted by team of experts and maintains a balance between theoretical concepts and practical applications

6 MS Excel Basic and Advanced Total Duration: 6 hours Introduction to Excel Navigating Worksheets Formatting and Editing Worksheet Data Grouping Data, Subtotals and Data Validation Working with Formulas and Functions Referencing Functions Filter, Sorting, Advance filter Conditional formatting Creating Charts and Graphics Simple charts Pie charts Dynamic charts Logical functions using Excel And, if, not, or, true, false Concatenate, left, right, mid, len, trim, Upper, lower, proper, exact, etc Analyzing Data with Excel Sum, Count, Sumifs, Countifs Consolidating Worksheets (Vlookup, Index, Match, Offset) Using Pivot Tables Data analysis toolpack Data tables Goal Seek Using Advanced Excel features Worksheet protection and security Data Validation Text to column, use of delimiter, etc

7 SAS Base and Advanced Total Duration: 24 hours SAS +R Edge program also available separately - Module Introduction - Data importing - Understanding Introduction to SAS, GUI Concepts of Libraries, PDV, data execution etc Building blocks of SAS (Data & Proc Steps - Statements & options) Debugging SAS Codes Importing different types of data & connecting to data bases Data Understanding(Meta data, variable attributes(format, informat, length, label, etc)) SAS Procedures for data import/export/understanding(proc import/proc contents/proc print, etc) Data Manipulation Data Manipulation steps(sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type conversions, renaming, formatting, etc) Data manipulation tools(operators, Functions, Procedures, control structures, Loops, arrays, etc) SAS Functions (Text, numeric, date, utility functions) SAS Procedures for data manipulation(proc sort, proc format, Proc transpose, etc) SAS Options (System Level, procedure level) Exploratory Data Analysis & Data visualization Introduction exploratory data analysis Descriptive statistics, Frequency Tables and summarization Univariate Analysis (Distribution of data & Graphical Analysis) Bivariate Analysis(Cross Tabs, Distributions & Relationships, Graphical Analysis) SAS Procedures for Data Analysis(proc freq/proc means/proc summary/proc tabulate/proc univariate, etc) SAS Procedures for Graphical Analysis (Proc Sgplot, Proc gplot, etc) Reporting - Output Exporting Introduction to Reporting SAS Reporting Procedures ( Proc print, Proc Report, Proc Tabulate etc) Exporting data sets into different formats (Using proc export( Concept of ODS(output delivery system) ODS System - Exporting output into different formats Optimizing SAS Codes Introduction to Advanced SAS - Proc SQL & Macros Understanding select statement (From, where, group by, having, order by etc) Proc SQL - Data creation/extraction Proc SQL - Data Manipulation steps Proc SQL - Summarizing Data Proc SQL - Concept of sub queries, indexes etc SAS Macros - Creating/defining macro variables SAS Macros - Defining/calling macros SAS Macros- Concept of local/global variables SAS Macros - Debugging techniques

8 R Foundation Total Duration: 12 hours SAS +R Edge program also available separately - Module Introduction - Data Importing/Exporting Introduction R/R-Studio - GUI Concept of Packages - Useful Packages (Base & other packages) in R Data Structure & Data Types (Vectors, Matrices, factors, Data frames, and Lists) Importing Data from various sources Database Input (Connecting to database) Exporting Data to various formats) Viewing Data (Viewing partial data and full data) Variable & Value Labels Date Values Data Manipulation Data Manipulation steps (Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type conversions, renaming, formatting, etc) Data manipulation tools(operators, Functions, Packages, control structures, Loops, arrays, etc) R Built-in Functions (Text, Numeric, Date, utility) Data Manipulation R User Defined Functions R Packages for data manipulation(base, dplyr, plyr, reshape, car, sqldf, etc) Data Analysis - Visualization Introduction exploratory data analysis Descriptive statistics, Frequency Tables and summarization Univariate Analysis (Distribution of data & Graphical Analysis) Bivariate Analysis(Cross Tabs, Distributions & Relationships, Graphical Analysis) Creating Graphs- Bar/pie/line chart/histogram/boxplot/scatter/density etc) R Packages for Exploratory Data Analysis(dplyr, plyr, gmodes, car, vcd, Hmisc, psych, doby etc) R Packages for Graphical Analysis (base, ggplot, lattice,etc)

9 Business Analytics using SAS and R Total Duration: 33 hours Business Analytics program also available separately - Module 1+4 Introduction to Statistics Basic Statistics - Measures of Central Tendencies and Variance Building blocks - Probability Distributions - Normal distribution - Central Limit Theorem Inferential Statistics -Sampling - Concept of Hypothesis Testing Statistical Methods - Z/t-tests( One sample, independent, paired), Anova, Correlations and Chisquare Introduction to Predictive Modeling Introduction to Predictive Modeling Types of Business problems - Mapping of Techniques Different Phases of Predictive Modeling Data Preparation Need of Data preparation Data Audit Report and Its importance Consolidation/Aggregation - Outlier treatment - Flat Liners - Missing values- Dummy creation - Variable Reduction Variable Reduction Techniques - Factor & PCA Analysis Segmentation Introduction to Segmentation Types of Segmentation (Subjective Vs Objective, Heuristic Vs. Statistical) Segmentation Heuristic Segmentation Techniques (Value Based, RFM Segmentation and Life Stage Segmentation) Behavioural Segmentation Techniques (K-Means Cluster Analysis) Cluster evaluation and profiling Interpretation of results - Implementation on new data Decision Trees Decision Trees - Introduction - Applications Types of Decision Tree Algorithms CHAID Vs. CART Decision Trees - Validation Overfitting - Best Practices to avoid Implementation of Solution Linear Regression Introduction - Applications Assumptions of Linear Regression Building Linear Regression Model Understanding standard metrics (Variable significance, R- square/adjusted R-square, Global hypothesis,etc) Validation of Models (Re running Vs. Scoring) Standard Business Outputs (Decile Analysis, Error distribution (histogram), Model equation, drivers etc.) Interpretation of Results - Business Validation - Implementation on new data Logistic Regression Introduction - Applications Linear Regression Vs. Logistic Regression Vs. Generalized Linear Models Building Logistic Regression Model Understanding standard model metrics (Concordance, Variable significance, Hosmer Lemeshov Test, Gini, KS, Misclassification, etc) Validation of Logistic Regression Models (Re running Vs. Scoring) Standard Business Outputs (Decile Analysis, ROC Curve, Probability Cut-offs, Lift charts, Model equation, Drivers, etc) Interpretation of Results - Business Validation - Implementation on new data Time Series Forecasting Introduction - Applications Time Series Components( Trend, Seasonality, Cyclicity and Level) and Decomposition Classification of Techniques(Pattern based - Pattern less) Basic Techniques - Averages, Smoothening, etc Advanced Techniques - AR Models, ARIMA, etc Understanding Forecasting Accuracy - MAPE, MAD, MSE, etc

10 Course completion and career assistance Course completion & Certification criteria What is included in career assistance? You shall be awarded an AnalytixLabs certificate only post the submission and evaluation of mandatory course project work. These will be provided as a part of the training. Post successful course completion, candidates can seek assistance from AnalytixLabs for profile building. A team of seasoned professionals will help you based on your overall education background and work experience. This will be followed by interview preparation along with mock interviews (if required) There is no pass/fail for these assignments and projects. Our objective is to ensure that trainees get strong hands- on experience so that they are well-prepared for job Job referrals are based on the requirements we get from interviews along with performance at their jobs. various organizations, HR consultants and large pool of AnalytixLabs ex-students working in various companies. Incase the assignments and projects are not up-to-themark, trainees are welcome to take help and support for improvisation. While weekly schedule is shared with trainees for regular assignments, candidates get 3 months, post course completion, to submit their final assignment and projects. No one can truthfully provide job guarantee, particularly for good quality job profiles in Analytics. However, most of our students do get multiple interview calls and good career options based on the skills they learn during training. For this there will be continuous support from our side for as long as required.

11 Time and investment SAS + R + Business Analytics: 80 hours + Practice, INR 30, % ST / $1200 (foreign nationals) SAS + R + Business Analytics (self-paced): 80 hours + Practice, INR 25, % ST / $900 (foreign nationals) R + Business Analytics: 48 hours + Practice, INR 25, % ST / $750 (foreign nationals) Business Analytics: 33 hours + Practice, INR 20, % ST / $600 (foreign nationals) Timing: 6 hours per weekend live training (Saturday & Sunday 3 hours each) + Practice Training mode: Fully interactive live online class /Class room (In Gurgaon center only) (In addition to the above, you will also get access to the recordings for future reference and self study) Components: Learning Management System access for courseware like class recordings - study material, Industryrelevant project work Certification: Participants will be awarded a certificate on successful completion of the stipulated requirements including an evaluation Base SAS Global Certification: $180 (optional) SAS Business Analyst Global Certification: $180 (optional)

12 We provide trainings both in fully interactive live online and classroom* mode Saves commuting time and resources in today s chaotic world Delivered lectures are recorded and can be replayed by individuals as per their needs Fully interactive live online class with personal attention Ensures best use of time and resources One of strongest global trends in education, both in developing and developed countries Access to quality training and 24x7 practice sessions available at the comfort of your place Studies prove that online education beats the conventional classroom *Classroom only available at Gurgaon center

13 Contact Us Visit us on: For course registration, please visit: For more information, please contact us: Or Call us we would love to speak with you: (+91) Join us on: Twitter - Facebook - LinkedIn - Blog -