Data Science using SAS

Introduction to the Analytics world and ETL

Analytics World
- Introduction to Analytics
- Concept of ETL
- S-A-S in advanced analytics
Global Certification: Induction and walk through
- Getting Started
- Software installation
- Introduction to GUI
- Different components of the language
- All programming windows
- Concept of Libraries and Creating Libraries
- Variable Attributes - (Name, Type, Length, Format, In format, Label)
- Importing Data and Entering data manually
Understanding Datasets
- Descriptor Portion of a Dataset (Proc Contents)
- Data Portion of a Dataset
- Variable Names and Values
- Data Libraries

Base S-A-S - Accessing the Data

Understanding Data Step Processing
- Data Step and Proc Step
- Data step execution
- Compilation and execution phase
- Input buffer and concept of PDV
Importing Raw Data Files
- Column Input and List Input and Formatted methods
- Delimiters, Reading missing and non standard values
- Reading one to many and many to one records
- Reading Hierarchical files
- Creating raw data files and put statement
- Formats / Informat
Importing and Exporting Data (Fixed Format / Delimited)
Proc Import / Delimited text files
Proc Export / Exporting Data
Datalines / Cards;
Atypical importing cases (mixing different style of inputs)
- Reading Multiple Records per Observation
- Reading “Mixed Record Types”
- Sub-setting from a Raw Data File
- Multiple Observations per Record
- Reading Hierarchical Files
Importing Tips

Data Understanding, Managing and Manipulation

Understanding and Exploration Data
- Introduction to basic Procedures - Proc Contents, Proc Print
Understanding and Exploration Data
- Operators and Operands
- Conditional Statements (Where, If, If then Else, If then Do and select when)
- Difference between WHERE and IF statements and limitation of WHERE statements
- Labels, Commenting
- System Options (OBS, FSTOBS, NOOBS etc…)
Data Manipulation
- Proc Sort - with options / De-Duping
- Accumulator variable and By-Group processing
- Explicit Output Statements
- Nesting Do loops
- Do While and Do Until Statement
- Array elements and Range
Combining Datasets (Appending and Merging)
- Concatenation
- Interleaving
- Proc Append
- One To One Merging
- Match Merging
- IN = Controlling merge and Indicator

Data Mining with Proc SQL

Introduction to Databases
Introduction to Proc SQL
Basics of General SQL language
Creating table and Inserting Values
Retrieve & Summarize data
Group, Sort & Filter
Using Joins (Full, Inner, Left, Right and Outer)
Reporting and summary analysis
Concept of Indexes and creating Indexes (simple and composite)
Connecting S-A-S to external Databases
Implicit and Explicit pass through methods

Macros for Automation

Macro Parameters and Variables
Different types of Macro Creation
Defining and calling a macro
Using call Symput and Symget
Macros options (mprint symbolgen mlogic merror serror)

Fundamental of 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 Chi-square

Introduction to Predictive Modelling

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)
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

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

Introduction to Machine Learning

Statistical learning vs. Machine learning
Major Classes of Learning Algorithms -Supervised vs Unsupervised Learning
Concept of Overfitting and Under fitting (Bias-Variance Trade off) & Performance Metrics
Types of Cross validation(Train & Test, Bootstrapping, K-Fold validation etc)

Regression & Classification Model Building

Recursive Partitioning(Decision Trees)
Ensemble Models(Random Forest, Bagging & Boosting)
K-Nearest neighbours

Travel Flights Analysis

Study the flights data along with their schedules, weather and also plane information thereby understanding flight routes and delays. This case study comprises of four sections (Import and understand the data, Preparing data for analysis, Perform exploratory analysis, forming & testing hypothesis etc)

Laptop Sales Analysis

Data mining the sales transaction data using SAS to find key sales trends.

Banking Case study

Understand customer spend & repayment behavior, along with evaluating areas of bankruptcy, fraud, and collections. Also, respond to customer requests for help with proactive offers and service.

Visualization

Perform different graphical analysis (bar chart, pie chart, box plot, histogram, stacked charts, heat maps, scatter plots, panel charts etc) for solving various business problems

Credit Card Customers Segmentation

A credit card company wishes to understand its customer behavior so to have an enriched customer profile by having intelligent KPI’s. The idea is to apply advanced algorithms like factor and cluster analysis for data reduction and customer segmentation based on the behavioral data.

Proactive Attrition Management

A wireless telecom companies wants to reduce customer churn by developing a proactive churn management model. The idea is to build a logistic regression based predictive model to develop an incentive plan for enticing would-be churners to remain with the company.

Predicting Loan Default

A bank would like to build credit risk model (application score card using PD models) to accept/ reject applications for loans. Also it wants to understand the key drivers for default or delinquency.

Key Drivers for Customer credit card 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 and help set the credit limit and designing new product offerings.

Time Series Forecasting

Use time series analysis to forecast the outbound passenger movement for next few quarters.

Sentiment Analysis

Objective of this analysis is to obtain data from Twitter and check how the sentiment varies by country for a particular brand/keyword/company.

Access to 108 hours instructor led live classes of 24x3 hours each, spread over 18 weekends, apart from 18 hours of video content

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

Career guidance 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 Learning Management System (LMS) account. 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 LMS. 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. Batch change policies will however, apply in this case.

Please note that incase you are not able to complete your course within one year of course validity, due to reasons at your end, limited support might be available post the completion of one year.

For how long are the recordings available to me?

1 year post your course commencement. If needed, you can also repeat any number of classes you want in the next one year after course completion. Batch change policies will however, apply in this case.

In case required because any genuine reasons, the recordings access can be extended further for upto 1 year post the completion of one year validity. Please note that given the constant changes in the Analytics industry, our courses continue to be upgraded and hence old courses might no longer hold relevance. Hence, we do not promise lifetime access just for marketing purposes.

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 by Suo Jure. The downloading/distribution of these recordings in anyway is strictly prohibited and illegal as they are protected under copyright act. Incase a student is found doing the same, it will lead to an immediate and permanent suspension in the services, access to all the learning resources will be blocked, course fee will be forfeited and the institute will have all the rights to take strict legal action against the individual.

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. Once all your submissions are received and evaluated well, the certificate shall be awarded.

Please note that incase you are not able to complete the course within the one year validity, AnalytixLabs might hold a mock interview/viva, apart from your submissions, before issuing the certificate.

Do you help in placements?

We follow a comprehensive and a self-sustaining system to help our students with placements. This is a win-win situation for our candidates and corporate clients. As a pre-requisite for learning validation, candidates are required to submit the case studies and project work provided as a part of the course (flexible deadline). Support from our side is continuous and encompasses help in profile building, CV referrals (as and when applicable) through our ex-students, HR consultants and companies directly reaching out to us.

We will provide guidance to you in terms of what are the right profiles for you based on your education and experience, interview preparation and conducting mock interviews, if required. 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.

To avoid any kind of ambiguity, we strongly suggest that you go through our course brochures.

Please also note that incase you are unable to complete the course in the one year course validity period, we might not be able to assist with placements. The discussion you would have had with our counsellors/faculty at the time of registration is also basis the profile you hold at that time. Incase your course has got delayed due to reasons at your end, this might effect the profile, in which case it might be difficult for us to assist in placements.

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 and Bengaluru 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?

Instructor Led Live online or Classroom - Within 7 days of registartion date and latest 3 days before batch start
Video-based - 2 days

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.

“

Super duper amazing classes. They really just clarify all your doubts before moving on to the next part. I took the advance big data science course and I am thoroughly satisfied that I did not take up any other classes, I thought should have taken at the time. They are technically versed in their respective technologies in this case Python - Pandas and Scipy and they just go the distance to clarify all doubts and make things as simple as possible.