Analytical Edupoint Adchini, Delhi

Core Java Programming Introduction of Java Introduction to Java; features of Java Comparison with C and C++ Download and install JDK/JRE (Environment variables set up) The JDK Directory Structure First Java Program through command prompt First Java Program through Eclipse Data types and Operators Primitive Datatypes, Declarations, Ranges Variable Names Conventions Numeric Literals, Character Literals String Literals Arrays(One dimensional; two- dimensional) Array of Object References Accessing arrays, manipulating arrays Enumerated Data Types Non-Primitive Datatypes Defining a class, variable and method in Java Method Signature; method calls Expressions in Java; introduction to various operators Assignment Operator Arithmetic Operators Relational Operators Logical Operators Conditional Operators Operator Precedence Implicit Type Conversions Upcasting and downcasting Strict typing Type conversion Control Flow statements Statements and it's various categories in Java if, if-else, if-else-if switch case for statement (both flavours traditional and enhanced for) while and do-while loops The continue Statement; labelled continue statement The break Statement; labelled break statement return statement OOPS and its application in Java Classes and Objects Defining a class;Defining instance variables and methods Creating objects out of a class Method calls via object references Abstraction Interfaces and Abstract classes Abstract and non-abstract methods Inheritance extends and implements keywords in Java Super class and Sub class this keyword, super keyword in Java for inheritance Concrete classes in Java Polymorphism Compile time polymorphism -- Overloading of methods Run time polymorphism -- Overriding of methods Method Overriding rules and method overloading rules

C++ Language Syllabus Overview:- C++ language is a superset of the ‘C’ language and was initially known as “C with Classes”. In "C" operator ++ is used to increment the value by 1. That means to the language ‘C’, developers have added some extra features and hence named as C++. C++ is a general purpose programming language and supports object oriented programming features. Course Objectives: Understanding about object oriented programming. Gain knowledge about the capability to store information together in an object. Understand the capability of a class to rely upon another class. Learn how to store one object inside another object Learn use of one method can be used in variety of different ways Understanding the process of exposing the essential data to the outside of the world and hiding the low level data Create and process data in files using file I/O functions Understand about constructors which are special type of functions Learn how to write code in a way that it is independent of any particular type Pre-requisite / Target Audience: Programmers looking for jobs Programmers wanting to write efficient code Computer Science students having Data Structures as part of their curriculum Non Computer science students wanting to enter IT industry

C Language Syllabus Introduction and First Program Why Programming History of C Language Hello World Program Variables and Data types Identifiers in C Variables and DataTypes Constants Constants Printf and Scanf Unformatted IO Functions Operators and Expressions Operators and Expressions Relational and Logical Operators Bitwise Operators Control Flow Statements If Statement Switch Statement Unconditional Branching using goto statement While Loop Do While Loop For Loop Break and Continue Special Cases

Module 1 What is Marketing What is Difference between Conventional Marketing and Digital Marketing Introduction of Digital Marketing Famous Tools for Digital Marketing Pre Requisite of Digital Marketing Module 2 Introduction of Marketing Fundamentals How to reach Target Audience Module 3 Market Research Importance of Market Research Online Survey and Form and Creation Survey Analysis Quiz and their Strategy Module 4 Website Design Build your website Wordpress Vs. Wix and Weebly How to purchase domain How to verify WHOIS Information How to add Pages, Post, Menus and Widget WordPress Themes WordPress Security and With Plugins

GST Course

Tally Course

Taxation Course

Introduction to Web development (3 hours) General introduction about web pages. Client side VS Server side. What are web HTML, CSS and javascript. What tools do we need to build a web page? Introduction to HTML (12 hours) HTML Elements (3 hours) HTML attributes (3 hours) Styling and formatting HTML (3 hours) Forms (3 hours) [Practice] Introduction to CSS and Javascript (9 hours) Introduction to CSS (4.5 hours) Introduction to javascript (4.5 hours) [Project] Server Side Development – PHP (30 hours) Sitting and configuring work environment. PHP syntax, variables, Operators … etc. PHP Functions. PHP with Forms. PHP Server Variables. PHP & MYSQL. [Project]

Web Designing Course

DCA Computer Course

BASIC COMPUTING SKILLS BASIC CONCEPTS AND COMPUTER ORGANIZATION SOFTWARE AND PROGRAMMING LANGUAGE COMMUNICATION AND COMPUTER NETWORK OPERATING SYSTEM BASICS OF MS WORD BASICS OF MS EXCEL FUNDAMENTALS OF INTERNET COMPUTER APPLICATION INTRODUCTION TO SYSTEMS ANALYSIS AND DESIGN SYSTEM DESCRIPTION TECHNIQUES SYSTEM DEVELOPMENT METHODOLOGIES CONCEPT OF DATABASE CREATING TABLES CREATING FORMS CREATING QUERIES CREATING REPORTS CREATING REPORTS FUNDAMENTALS OF “C” OPERATORS AND EXPRESSIONS IN “C” INPUT AND OUTPUT OF DATA A COMPLETE C PROGRAM MAKING DECISIONS IN “C” FUNCTIONS IN “C” ARRAYS POINTERS STRUCTURES AND UNIONS DATA FILES C PREPROCESSOR SETTING UP A COMPUTER BUSINESS CENTRE

Module 1 What is Software Testing and its Importance Career Opportunity and Future in Software Testing Organization Types and Team Structure Project Bidding and Kick of Meeting Module 2 Requirement Gathering, Requirement Document(SRS) Query Log, Defects, Bug and Error Why Software have Bugs ? Types of Software Testing Black Box Testing, White Box Testing and Gray Box Testing Module 3 Functional Testing and Performance Testing Unit Testing Build Verification Testing(BVT) Smoke Testing and Live Practice Priority and Severity Types of Environments (Dev, QA, Staging, Prod and Mirror Prod) Module 4 Sanity Testing and Practical Examples Task Tracking Tools Test Matrix Compatibility Testing and Retesting System Testing Integration Testing and Practicals

Module 1 Summary and Introduction of Java Difference in JRE/JDK/JVM Run time Environment Set Up/ Environmental Variable Set Up Data Type, Variable & Constant with examples Operators is java (+, -, *, /, % and increment and Decrement operator) Conditional statements in java (is, If else & Switch) Control statements in java (For, while, do while and for each) Module 2 Arrays one dimensional, Two dimensional and Multidimensional Classes and Objects Introduction to OOPs Encapsulation or data hiding (Getters & Setters) Inheritance in Java Access Modifiers (Public, Private, Protected & Default) Module 3 Class Modifiers (Static & Final) Abstraction in Java- abstract class Interface String Handling Super, final, finally and “This” uses. Recursion Var- Arg Method Exception Handling List- Array list & Linked List Sets- Hast set, Linked Hash set Collection Class Tree set, Map, Hash Map Interview Questions

Part 1: INTRODUCTION OF DBMS AND INSTALLATIONS PROCESS Data, Databases and RDBMS Software’s Advantages of SQL Server Uses, Database Engine Many Component and OLTP Databases BI Tool Components & Data Science Components Uses of SQL, Real-time Usages, SQL versus Microsoft T-SQL [MSSQL] Instance Name and Server Name, Features, Collation, Admin Users Real-time Projects Included, Job Responsibilities; Versions and Editions of SQL Server SQL Server and SSMS Installation, SQL Server - Career Options SQL Server Pre-requisites: SQL Server 2019 / 2017/2014/2012 Installations PART 2: BASICS SQL AND SSMS TOOL SSMS, Different Connections (Local and Remote) Sys Databases, Creating Objects with GUI Insertions of data, Limit, Storage capacity Sys Files, Commands with script, Select Scanning and Retrieving of data(Basic Level) PART 3: DATABASE CREATIONS AND COMANDS (DDL AND DML) Creating DB, Entitles (Tables) All about “SELECT” Diff Data types in SQL, Select with simple and where conditions, Different kinds of Operators OR, AND, IN, LIKE, NOT LIKE, Wild cards, IS, IS NOT OPERATORS, TOP AND DISTINCT keywords and Many more.

VBA Macro Programming & Automation Macro Recording and Running Programming Concept Developer Tab and Menu Recording a Macro Saving Macro in Different Workbooks Various Methods of Running a Macro Command Button Design Mode Running Mode & Break Mode Modules and Procedures Absolute and Relative Reference Introduction to Visual:- Basic Editor Project Explorer and Code Window Modules Functions and Subroutines Worksheet Properties in Property Window Programming Basic Public and Private Subroutines Object Methods and Properties Object Hierarchy & Collection Creating a Folder/Subfolder Opening , Saving, Closing New Workbook Opening a saved Workbook Selecting/Activating/Renaming/Adding Sheets Range, Cells, Columns & Row Properties Writing a Simple Code in VBA

INTRODUCTION TO EXCEL An Overview of Excel Screen Basic Concept of Spreadsheet and Workbook Creating, Editing Saving and printing) Excel Terminology: - Rows, Column and Cell Working with functions & Formulas Graphically representing data: Charts and Graphs Analyzing Data: Data Menu Subtotal, Filtering Data Difference between Excel 2007, 2010, 2013, 2016 and Office 365, its Boundaries & Features Formatting Worksheets, Securing & Protecting Spreadsheets All Tabs of Microsoft Excel 2013, 2016, Office 365 Simple Data Entry Number, Text, Date, Selecting Range Cut, Copy, Paste, Format Printer and Move Data. Saving Excel Format LOOKUP FUNCTIONS: The LOOKUP function, Date and time functions Annotating formulas, Lookup, V-Lookup, H-Lookup, Match, Index, Usage Of Match Function Hlookup And Index, 2D & 3D Lookup, Mixed Lookup Vlookup with Iferror, Multiple Vlookup, Vlookup with Choose Reverse VLookup, Index with Double Match DEVELOP THE WORKSHEET: Plan a Worksheet, Row and Column labels Split Worksheet/box/bar, copy data and formulas Display/Move Toolbars, Enhance worksheet appearance Use multiple windows: Copy/Paste between worksheets Link Worksheets, Consolidate worksheets Important link from other Applications Use Auto Format: Create, use and modify styles and templates Print Features: Create/edit an outline

Introduction to Hadoop HDFS Architecture MapReduce Flow Chart Combiner in Hadoop Hello world job Partitioner in Hadoop Why we need combiners in Hadoop Sqoop in Hadoop WhyPartitioner in MapRednce (Hadoop) How to load data into hive table in Hadoop Difference between Internal and External Table in Hadoop What is Oozie in Hadoop Hadoop distributed file system commands What is HIVE in Hadoop What is Hbase in Hadoop MapReduce Code Mapper Code What is Pig in Hadoop_ Implementing Hello World Job(DriverCode) How to display Tables from RDBMS MySQL from Sqoop (Hadoop) Why we need Sqoop (Hadoop) How to display Database from RDBMS mysql for Sqoop (Hadoop) How to Import Tables from RDBMS MySQL from HDFS (Hadoop)

SAP Course

MODULE 1 Introduction to Machine Learning What is Machine learing? Overview about scikit-learn package Types of ML Basic steps of ML ML algorithms Machine learning examples MODULE 2 Data Preprocessing Dealing with missing data Identifying missing values Imputing missing values Drop samples with missing values Handling with categorical data Nominal and Ordinal features Encoding class labels One hot encoding Split data into training and testing sets Feature scaling MODULE 3 Machine Learning Classifiers K-Nearest Neighbors (KNN) Decision tree Random forest Support vector machines (SVM) Naive Bayes Logistic Regression

Part -1 Core Python Section 1 Getting started with Python programming Overview Introductory Remarks about Python A Brief History of Python How python is differ from other languages Python Versions Installing Python and Environment Setup IDLE Getting Help How to execute Python program Writing your first Python program How to work on different Popular IDE’s [Pycharm, Jupyter Notebook, Spyder etc.] Section 2 Variables, Keywords and Operators Variables Memory mapping of variables Keywords in Python Comments in python Operators Arithmetic Operators Assignment Operators Comparison Operators Logical Operators Membership Operators Identity Operators Bitwise Operators Basics I/O and Type casting Getting user input Section 3 Data types in Python Numbers Strings Lists Tuples Dictionary Sets

Tableau Desktop Introduction to Tableau Section 1 Introduction to Tableau Tableau Installation and Setup Connecting With Different Database Live Vs Extract Data Structure Section 2 Data Type Column Formatting Sort & Grouping Measure Name and Values and their usage Discrete Vs Continuous Data and working on them Section 3 Parameters, Combines and Sets Filters and its types Drill Down and Hierarchies (system defined and user defined Granularity Section 4 Title and Caption Size, Color, Label, Shapes, Font, Details and Alignment Shading, Borders and Tooltip Worksheet Interface Managing Metadata

DATA SCIENCE WITH R PARAMETERS SPECIFICATIONS Tools Used R Learning Mode (Classroom – Instructor based) Duration 58 – 52 Hours Batch size 5- 8 Students Location Delhi (Saket) Course includes Live scenarios, Case Studies, Project, Assessments, Mock Interview. Study Material PPTs, Doc, Data, PDFs etc. TARGET AUDIENCE: Any graduate - No prior knowledge of Data Science / Analytics is required. WHAT IS R? R is open source data analysis software: and widely uses by Data scientists, statisticians, Researchers and Data analysts—anyone who needs to make sense/insight of data can use R for Statistical Analysis, Data visualization, and Predictive Modeling. R is created by Ross Ihaka and Robert Gentleman at the University of Auckland in New Zealand in the 1990s as a statistical platform for their students, and thus it has been extended over the decades by thousands of user-created libraries/packages. R is a programming language: An object-oriented language created by statisticians, R provides objects, operators, and functions that allow users to explore, model, and visualize data. R is a vector language, so anyone can add functions to a single Vector without putting in a loop. And at the same time R is powerful and faster than other languages, we can easily implement Machine Learning algorithms in a fast and simple way.

Data Science with SAS PARAMETERS SPECIFICATIONS Tools Used SAS Learning Mode (Classroom – Instructor based) Duration 48 – 52 Hours Batch size 5- 8 Students Location Delhi (Saket) Course includes Live scenarios, Case Studies, Project, Assessments, Mock Interview. Study Material PPTs, Doc, Data, PDFs etc. Target Audience: Any graduate - No prior knowledge of Data Science / Analytics is required What is SAS? SAS is licensed based software suite developed by SAS Institute for advanced analytics, Multivariate analyses, Business Intelligence, Data Management, and Predictive analytics. SAS is widely uses by Data scientists, statisticians, Researchers and Data analysts—anyone who needs to make sense/insight of data can use SAS for Statistical Analysis, Data visualization, and Predictive Modeling. SAS is a leader in business analytics and No. 1 in Advanced and Predictive Analytics market share. SAS held a 30.5 percent market share for 2016 in the advanced and predictive analytics category.