Tuesday, 17 September 2019

Data Analytics Online Training Data Analytics Online Training

FOR FREE DEMO contact :
Phone/WhatsApp : +91-(850) 012-2107
USA Number : 214-628-3894

Big Data Analytics Interview Questions and Answers, Recorded Video Sessions, Materials, Mock Interviews Assignments Will be provided
Big Data Analytics Agenda/Syllabus
(we can customize the course Curriculum as per your requirements)

DATA ANALYTICS Course Content

BASE SAS

  • Introduction To SAS System & Architecture
  • Features
  • Variables & SAS Syntax Rules
  • SAS Data Sets
  • Data Set Options
  • If – Then Else Statement
  • Where Statement
  • Creating & Redefining Variables
  • Reading Raw Data
  • Infile Statement With Options
  • Multiple Observations and Multiple Datasets.
  • Input Styles
  • SAS Functions
  • Do Loops
  • Leave and Continue Statements
  • Output Statement & Put Statement

BASE SAS PROCEDURES

  • Proc Sort
  • Proc Print
  • Proc Means
  • Proc Freq
  • Proc Plot
  • Proc Chart
  • Proc Compare
  • Proc Copy
  • Proc Summary
  • Proc Append
  • Proc Datasets
  • Proc Contents
  • Proc Delete
  • Proc Format
  • Proc Printto

SAS/REPORTS

  • Frequency Report
  • One-Way Frequency Report
  • Cross Tabular Frequency Report
  • Summary Statistics
  • Tabulate Procedure

SAS/ODS

  • Creating Rtf File
  • Creating Html File
  • Creating Pdf File
  • Creating Xml File

SAS/GRAPH

  • Gchart Procedure
  • Vertical, Horizontal, Pie
  • Donut
  • Group,Subgroups
  • Gplot Procedure
  • Mutliple Plots & Overlay
  • Symbol Statement
  • Title and Footnote Statements
  • Goptions

SAS/MACROS

  • Macro Concepts
  • Macros And Macro Variables
  • Creating Macro Variables
  • Using Macro Variables
  • Creating Modular Code With Macros
  • Invoking A Macro
  • Adding Parameters To Macros
  • Macros With Conditional Logic
  • Using Various Procedures In Macros
  • Automatic Variables
  • Macro Functions
  • Including External Macros

SAS/STAT

  • Proc Univariate
  • Proc Corr
  • Proc Reg
  • Proc Anova

PYTHON

  • Introduction to Python
  • Features of Python
  • Writing Our First Python Program
  • Executing a Python Program
  • Getting Help in Python
  • Reopening the Python Program in IDE
  • Datatypes in Python
  • Output statements
  • Various formats of The print()
  • Input Statements
  • Command Line Arguments
  • If Statement
  • If … else Statement
  • If … elif … else Statement
  • While Loop
  • For Loop
  • Infinite Loops
  • Nested Loops
  • Else Suite
  • Arrays in Python
  • Strings and Characters
  • Functions
  • Lists and Tuples
  • Dictionaries
  • Oops Concepts
  • Classes and Objects
  • Encapsulation
  • Abstraction
  • Inheritance
  • Polymorphism
  • Files in Python
  • Python’s Database Connectivity

GETTING STARTED R

  • R Basics
  • Variables and Class
  • Vectors, List, Factors, Matrix
  • Data Frames
  • Missing Values
  • Data Reading and Writing data
  • Data Visualization using GGPLOT
  • If-Else Conditions
  • Function
  • Loops
  • Data manipulation

MACHINE LEARNING

  • Introduction to Machine Learning
  • Types Of Machine Learning
  • Real time use cases in Machine Learning
  • Types of Algorithms Types of Problems –
    • Regression
    • Classification
    • Clustering
  • Regression
    • Linear Regression
    • Logistic Regression
  • Classification
    • Logistic Regression
    • Decision Tree,Random Forest
    • KNN,SVM
Posted by at

No comments:

Post a Comment

Subscribe to: Post Comments (Atom)