By embracing data science tools and technologies, companies can more effectively inform strategic decision-making, reducing uncertainty and eliminating analysis-paralysis.
• What is Data Analytics & Data Science
• Different types of Data Analytics (Descriptive, Diagnostic, Predictive, Prescriptive)
• What is Artificial Intelligence
• What is IOT
• Machine Learning (Supervised & Unsupervised Learning)
• Overview of Banking, Healthcare, Telecom domain
• Working with multiple data sources – RDBMS (SQL Server, Oracle, My SQL, DB2), NOSQL (MongoDB, Cassandra, CouchDB)
• Real world Applications of Machine Learning & Deep Learning
• What to expect from this course (Salary, Market trends, job roles, Domain)

Methods for getting Data into SAS, Informats(Numeric Informats, Character Informats, Date & Time Informats, Convert Dates & SAS Date Values), Formats (Numeric formats, Character formats, Date & Time formats), Pointers (Column Pointers, Line Pointers), Input Style (List input, Column input, Formatted input Modified Mixing input)

Proc Import, Infile Statement, Options, File name statement with DDE, Proc Export, File & Put Statement, Automatic Variable, Assigning variable attributes (Temporary attributes, Permanant attributes), Global options, Local Options, Data Control Option,Statements, Global Statements, Local Statements, Control Statements.

Arithmetic Functions(ABS, INT, FLOOR, CEIL, ROUND, MAX, MIN, SUM, MEAN, MOD, SQRT, STD, LOG, EXP, N, NMISS, MISSING, LARGEST, SMALLEST, LAG, DIF,), String Functions(COMPRESS, COMPBL, INDEX, SUBSTR, SCAN, TRANSLATE, TRANSWRD, TRIM, LEFT, STRIP, UPCASE, LOWCASE, PROPCASE, INPUT, PUT, LENGTH, CAT, FIND), Retrieving Data from Multiple tables, Natural Join, Inner Join, Outer Join (Right, Left, Full)

Date & Time Functions ( TODAY, DAY, HOUR, WEEKDAY, DATE, DATEPART, DATETIME, INTCK, INTNX, MDY, TIMEPART, YEAR, MONTH, QTR, DATEJUL, YRDIF), Reatain statement, Sum Statement, Conditional Control Statements(If Statement, If-then Statement, -If-Then-Else Statement Where Statement, Loops, Dountil Loop, Dowhile Loop) Array Statement.

Proc Print, Proc Transpose, Proc Contents, Proc Sort, Proc Formats, Proc Append, Proc Summary, Proc Datasets, Proc Tabulate, Proc Import, Proc Report, Proc Export, Proc Datasets, Proc Freq, Proc Means, Proc Reg

Subsetting Datasets, Concatenating, Merging, One-to-one merging, One-to-many merging, Many-to-one merging, Many-to-many merging, Matching merging, Updating, Retrieving Data From Multiple Table ( Natural Merge, Inner Merge, Outer Merge)

Data Structure  Introduction to SAS interface and library structure and definition  Reading data using datalines and importing and exporting datasets  Infile statement - reading raw data  Formats and Informat  Variable attributes and data modification using Data and Set statements Data Management  Using conditional statements to modify data - Where, If and Nested IF  Appending and Merging datasets  SAS Functions for data manipulation  Loops and Arrays in SAS

Basic Stats, Introduction to Predictive Analytics, Predictive modeling in SAS, Relevance in industry and need of the hour, Types of analytics – Marketing, Risk, Operations, etc, Future of analytics and critical requirement.

Data Sampling, Hypothesis Testing, Sampling Distribution, Inference, P- Value, Critical Region, T-Test, Chi Square Test, F- Test, Data Preparation, Different Data Type, Data Cleaning, Derived Variables, Aggregate Data

The Correlation Techniques, Pearson's Correlation Coefficient (r), Variance, Co Variance, Correlation matrix, types of correlation, Simple Linear Regression, Regression Formulas, Assumptions of Classical Linear Regression Model, Zero Covariance and No Multicollinearity, Parameter Estimation Method, Deciding important variables, Model Selection Criterion.

Introduction to Predictive Analytics, Predictive modeling in SAS, Relevance in industry and need of the hour, Types of analytics – Marketing, Risk, Operations, etc, Future of analytics and critical requirement.

Generalized Linear Models (GLMs), Binary Logistic Regression, SAS Logistic Regression Output Explanation, Fitting the Model in SAS, Fitting the Model in R, Test for Regression Coefficients, Validation Statistics, Goodness of Fit for Logistic Regression(Chi-square Test), Concordance, Prediction Using Logistic Regression, Making Predictions, Multicollinearity in Logistic Regression.

Inter variable dependence, Hierarchical Clustering, k means clustering, Principal Component Analysis(PCA), Data Reduction, Eigen values, Eigen vectors, Assumption of PCA, Interpretation of results

Time Series Analysis, Assumptions of Time Series Analysis and Identifying Patterns in Time Series Data, General aspects of analysis, Autoregressive and moving averages, ARIMA Procedures and Time Series Model.

Domain Specific Case Study (Healthcare, Retail, Banking, E-Commerce etc.) and Project Discussion with Industry Experts.

Business Overview, Introduction to Data Visualisation, Introduction to Business Intelligence, Data Visualization tools, Data Connection, Tableau Server & Tableau Reader, Tableau Features

Basic Chart Type, Excel Data to Visualisation, Data Visualisation on Transformed Data using SQL, Steps to create basic charts (Bar Chart, Pie Chart, Line Chart, Dual Axis Chart, Stacked Area Chart, Scatter Plot Chart, World Map Visualisation), Creating Dashboards(Filters & Highlighting).

Overview of SQL, Installing the Test environment, Editors & Platform to Learn SQL, Complete SQL in Class, Using the basic SELECT statement, Selecting rows, Selecting columns, Counting rows, Inserting data, Updating data, Deleting data, Fundamental of SQL. Function: Numbers and SQL, About numeric types, Finding the type of a value, Integer division and remainders, Rounding numbers, Dates in SQL, Use of Dates and times, Date- and time-related functions, Aggregates Functions, How, aggregates work, Using aggregate functions, Aggregating DISTINCT values, Exploring SQL Transactions, Why use transactions?, Using transactions

Studying Triggers in SQL, Updating a table with a trigger, Preventing automatic updates with a trigger, Automating timestamps with a trigger, What are Subselect and Views in SQL, Creating a simple subselect, Searching within a result set, Creating a view, Creating a joined view, A Simple CRUD Application in SQL, Touring the CRUD application, The SELECT functions, The INSERT, UPDATE, and DELETE functions