Data Science using SAS & R

A comprehensive business analytics and data science training using SAS and R

Learning tools without techniques is half the job done. So to help candidates emerge as 'Industry Ready' professional, this course encompasses basic statistical concepts to advanced analytics and predictive modelling techniques using most widely used analytics tools, like Excel, R, SAS (including Proc SQL).

This course has emerged from our most coveted flagship program SAS+ Business Analytics and evolved over last 4 years based on the changing industry requirements to provide you job oriented Data Science and Business Analytics skills.

Crafted and delivered by a team of industry experts, this comprehensive program has all components required to give you a strong foundation and head-start into the field of Analytics!

Who Should do this course?

Candidates from various quantitative backgrounds, like Engineering, Finance, Maths, Statistics, Business Management who want to head start their career in analytics.

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Course Duration 72 hours + Practice
Classes 24
Tools Excel, SAS, R
Learning Mode Live/Video Based
Next Batch17th January, 2016

  • Relevance in industry & need of the hour
  • Types of analytics – Marketing, Risk, Operations, etc
  • Business & Technology drivers for analytics
  • Analytics Tool Kit - Popular tools & Techniques in the Industry
  • Future of analytics & critical requirement
  • Types of problems and business objectives in various industries
  • Different phases of Analytics Project
  • Introduction to Excel
  • Working with Formulas and functions
  • Formating & Conditional Formating
  • Filtering, sorting, paste special etc
  • Fuctions(Logical & Text, Mathematical, Statistical etc)
  • Data Manipulation & Data Aggregation
  • Data Analysis using functions
  • Analyzing Data using Pivots
  • Descriptive Statistics
  • Creating Charts & Graphics
  • Data analytics tool (What -if analysis, Goal seek, Data Table, Solver)
  • Protecting Workbooks, worksheets and formulas
  • 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 steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type converstions, 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)
  • 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)
  • 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
  • Introduction to Advnaced 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
  • 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 steps(Sorting, filtering, duplicates, merging, appending, subsetting, derived variables, sampling, Data type converstions, renaming, formating etc)
  • Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays etc)
  • R Built-in Functions (Text, numeric, date, utility functions)
  • R User Defined Functions
  • R Packages for data manipulation(base, dplyr, plyr, reshape,car, sqldf etc)
  • 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)
  • 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 Chi-square
  • Introduction to Predictive Modeling
  • Types of Business problems - Mapping of Techniques
  • Different Phases of Predictive Modeling
  • Need of Data preparation
  • Data Audit Report and its importance
  • Data Preparation steps - Consolidation/aggregation - Outlier treatment - Flat Liners - Missing values- Dummy creation - Variable Reduction
  • Variable Reduction Techniques - Factor & PCA Analysis
  • Introduction to Segmentation
  • Types of Segmentation (Subjective Vs Objective, Heuristic Vs. Statistical)
  • Heuristic Segmentation Techniques (Value Based, RFM Segmentation and Life Stage Segmentation)
  • Behavioral Segmentation Techniques (K-Means Cluster Analysis)
  • Cluster evaluation and profiling
  • Interpretation of results - Implementation on new data
  • Decision Trees - Introduction - Applications
  • Types of Decision Tree Algorithms
  • 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 Linear Regression 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
  • 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
London Olympics Media Analytics
Data summarization and report generation using the concepts learnt in SAS module.
Laptop Sales Analysis
Data mining the sales transaction data using SAS to find key sales trends.
Credit Card Customers Segmentation
Build an enriched customer profile using intelligent KPIs. Apply advanced algorithms like factor and cluster analysis for data reduction and customer segmentation based on the behavioral data.
Key Drivers for Customer Spending
The objective of this case study is to understand what's driving the total spend of credit card(Primary Card + Secondary card) and identify the key spend drivers . This will require candidates to apply OLS/ linear regression and follow end-to-end model building process
Proactive Attrition Management
Build a logistic regression based predictive model for a telecom service provider to identify churn indicators to predict and proactively manage the customer attrition.
Predicting Loan Default
Apply the logistic regression to identify the risky customers with high likelihood to default on loan repayment.
Time Series Forecasting
Use time series analysis to forecast the outbound passenger movement for next four quarters..
Online Retail Analysis
Use Proc SQL for mining the online retail data to answer the key business questions

Access to 72 hours instructor led live classes of 24x3 hours each, spread over 12 weekends

Video recordings of the class sessions for self study purpose

Weekly assignment, reference codes and study material in PDF format

Module wise case studies/ projects

Specially curated study material and sample question for SAS Global Certification

Placement assitance and career support post the completion of some selected assignments and case studies

What if I miss a class?

Don’t worry. You will always get a recording for the class in your inbox. Have a look at that and reach out to the faculty in case of doubts. All our live classes are recorded for self-study purpose and future reference, and these can also be accessed through our Learning Management System. Hence, in case you miss a class, you can refer to the video recording and then reach out to the faculty during their doubts clearing time or ask your question in the beginning of the subsequent class.

You can also repeat any class you want in the next one year after your course completion.

For how long are the recordings available to me?

6 months post your course completion. If needed, you can also repeat any number of classes you want in the next one year after course completion.

Virtually the recordings are available to you for lifetime, but for judicious use of IT resources, the access to these recordings get deactivated post 6 months, which can be extended upon requests.

Can I download the recordings?

No. Our recordings can be accessed through your account on LMS or stream them live online at any point of time though.

Recordings are integral part of AnalytixLabs intellectual property. The downloading/distribution of these recordings in anyway is strictly prohibited and illegal as they are protected under copyright act.

What if I share my LMS login details with a friend?

The sharing of LMS login credentials is unauthorized, and as a security measure, if the LMS is accessed by multiple places, it will flag in the system and your access to LMS can be terminated.

Will I get a certificate in the end?

Yes. All our course are certified. As part of the course, students get weekly assignments and module-wise case studies. Based on the selected assignments and case studies (atleast 70%), the certificate shall be awarded.

Do you help in placements?

We follow a comprehensive process to help you with placements. Once you have completed and submitted all your case assignments, we will initiate the placement process for you. This starts with help in profile building and forwarding your profile to multiple companies through various channels like our references through our ex-students, dedicated  in-house placement cells and companies directly reaching out to us. We will provide guidance to you in terms of what profiles are good for you, what to expect in various interviews and also conducting mock interviews for you. The placement process for us doesn’t end at a definite time post your course completion, but is a long relationship that we will like to build.

For us placements are a win-win situation for both our corporate clients and individual students.

Do you guarantee placements?

No institute can guarantee placements, unless they are doing so as a marketing gimmick! It is on a best effort basis.

In professional environment, it is not feasible for any institute to do so, except for a marketing gimmick. For us, it is on a best effort basis but not time – bound – in some cases students reach out to us even after 3 years for career support.

Do you have a classroom option?

Yes we have classroom option for Delhi-NCR candidates. However, most of our students end up doing instructor led live online classes, including those who join classroom in the beginning. Based on the student feedback, the learning experience is same both in classroom and instructor led live online fully interactive mode.

How do I attend the online classes? Are they interactive or self-paced?

We provide both the options and for instructor led live online classes we use the gold standard platform used by the top universities across the globe. These video sessions are fully interactive and students can chat or even ask their questions verbally over the VoIP in real time to get their doubts cleared.

What do I need to attend the online classes?

To attend the online classes, all you need is a laptop/PC with a basic internet connection. Students have often shared good feedback of attending these live classes through their data card or even their mobile 3G connection, though we recommend a basic broadband connection.

For best user experience, a mic-headphone is recommended to enhance the voice quality, though the laptop’s in-built mic works fine and you can ask your question over the chat as well.

How can I reach out to someone if I have doubts post class?

Through the LMS, students can always connect with the trainer or even schedule one-to-one time over the phone or online. During the course we also schedule periodic doubts-clearing classes though students can also ask doubts of a class in the subsequent class.

LMS also has a discussion forum where a lot of your doubts might get easily answered.

Incase you are having a problem still, repeat the class and schedule one-to-one time with the trainer.

What is your refund policy?
  • Live online - 3 days post start of the course
  • Video-based - 2 days
  • Classroom – 3 days before the starting of the course
Can I pay in installments?

Yes. While making the fee payment, most of the courses have the installment option.

I am having difficulty coping up with my classes. What can I do?

For all the courses, we also provide the recordings of each class for their self-reference as well as revision in case you miss any concept in the class. In case you still have doubts after revising through the recordings, you can also take one-to-one time with the faculty outside classes during. Furthermore, if students want to break their courses in different modules, they get one year time to repeat any of the classes with other batches.

What are the system requirements for the software?

There is no particular system requirement for this course since the tools required for this course (Excel, SAS and R) can easily be installed on almost every laptop with basic configuration available these days. However, if possible, it is recommended to have 64-bit operating system.

The SAS + BA professional course from the AnalytixLabs is well designed with relevant assignments and case studies. The faculty is experienced to resolve subject as well as industry related queries. The approach to conduct sessions is absolutely scientific and practical. In addition, they were helpful enough to explain things with additional sessions.

- Ruma Chakravarty, MR Consultant & Trainer
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