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Professional Program in Data Analytics

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cqs
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Java (22)

Professional Program in Data Analytics

PPDA(Professional Program in Data Analytics) is an undergraduate programming course.
The primary goal of this course is for students to understand what it means to be a Application Development, what skills they need, and how they’ll develop those skills during their time at university.
The secondary goal is for students to understand what it takes to succeed in their studies while working toward becoming professional Full Stack Developers.

Eligibility for Course

The eligibility criteria for PPDA is 10+2 or equivalent examination.

Duration of Course

It is a one-year course generally taken after a 10+2 or equivalent examination.

Course Overview

CONCEPT BUILDING
1 Programming fundamentals
  • Program and computer languages
  • Compiler and Interpreter
  • Problem-solving tools
2 Algorithm
  • Intro
  • Rules of Algo
  • Advantages
  • Disadvantages
3 Flowchart
  • Intro
  • Symbols of flowchart
  • Advantage
  • Disadvantage
4 PseudoCode
  • Intro
  • Keywords
  • Advantage
5 Fundamental of Coding
  • Identifiers
  • Data Types
  • Variables
  • Conditional Statement
  • Loops
  • Array
EXCEL
1 Identify The Fundamentals Of Information Analysis
2 Report Types And Their Formats
3 Explore The Information Analysis And Reporting Tools
4 Organizing Data
5 Perform Basic Calculations
6 Perform Statistical Calculations
7 Financial Calculations
8 Nested If Functions
9 Macros
10 What-If-Analysis
11 Multiple Lookups(Both Vertical And Horizontal)
12 Salary Sheet
13 Forecast Sheet
14 Pivot Table And Pivot Chart
15 Powerview
16 Introduction Of Vba
17 Consolidation
18 Sorting
SQL SERVER
1 Introduction
  • SQL Server
  • SSMS
  • Installation
  • Building Blocks of SQL
2 DATABASE
  • Create DB
  • Select DB
  • Rename DB
  • Drop DB
  • Create Table
  • Rename Table
  • Drop Table
  • Delete Table
  • Select Data
  • Insert Data
  • Update Data
  • Delete Data
  • Alter Table
  • Truncate
  • Select Into
  • Insert Into
3 View in SQL
  • Create View
  • Update View
  • Drop View
4 Aggregate Function
  • min()
  • max()
  • sum()
  • avg()
  • count()
5 Operators
  • Arithmetic Operators
  • Comparison Operator
  • Logical Operator
  • Like Operator
  • Union Operator
  • Intersect Operator
  • Except Operator

6 Alias

  • for Table
  • for Column
7 Constraints
  • not null
  • unique
  • Primary Key
  • Foreign Key
  • Check
  • Default
8 Clauses
  • select
  • where
  • distinct
  • Order By
  • Group By, cube and rollup
  • Having
9 Keys
  • Primary Key
  • Foreign Key
  • Composite Key
  • Unique Key
10 Joins
  • Inner Join
  • Full Outer Join
  • Right
  • Left
11 Conditional and Loop
  • If
  • If else
  • Case
  • while Loop
12 Exception
  • try
  • catch
13 Stored Procedure
  • Create Stored Procedure
  • Execute procedure
14 Triggers
  • Intro
  • Types of trigger
  • DML
  • DDL
15 Functions
  • Types of Function
  • Scalar
  • Table-Valued
16 Index
  • Clustered index
  • Non-Clustered index
17 Cursor
  • methods
  • variable
18 Transaction
  • Introduction
  • Control and State
  • Commit
  • Rollback
  • Savepoint
PYTHON
1 Introduction
  • Python Why? What? How? When? Where?
  • Features
  • IDLE and it’s mode
2 Fundamental of python programming
  • Identifiers
  • Keywords
  • Variables
  • Data types ( integer, sequenced, boolean, dict, set)
3 Control Statements
  • Decision making
  • Itteration
  • break & continue
4 Function
  • Intro of function
  • Types of Function
  • Built-in function
  • User-define function
5 OOP’s in Python
  • Concepts of oop’s
  • Class and Object
  • Constructor and methods
  • Inheritance
  • Polymorphism
  • Abstraction
  • Encapsulation
6 Exception Handling
  • Exception in python
  • try, except, else, finally
  • user-define exception
7 File Handling
  • File I/O
8 Database Connectivity
  • Introduction
  • Connnecting Database with python
  • Basic working of database connectivity
R LANGUAGE
1 Introduction
  • i.) JAVA Why? What? How? When? Where?
  • ii.) How to install
  • iii.) A simple R program and comments in R
2 Fundamentals of R Programming
  • i.) Identifiers and naming convention of R language
  • ii.) Reserved words and Keywords
  • iii.) Data types and it’s Types
  • iv.) Variables and it’s Types
  • v.) Literals
  • vi.) Type Casting
  • vii.) Operators
3 Control Structures
  • i.) Types of Control Statements
  • ii.) Decision making or Conditional Statements( if, if-else, if- else- if, nested if, switch-case)
  • iii.) Itteration or Loops( for, while, do-while,break ,continue)
4 Functions
5 Object-oriented programming
6 File Handling
7 Database(MySQL)
8 Data Visualization
MACHINE LEARNING
1 Introduction of Machine Learning
2 Why Machine Learning
3 Pre-requisite for ML
4 Use cases in Machine Learning
5 Algorithms ( Use Cases )
6 Machine Training Models
7 Regression & Analysis Model
8 Python Numpy
9 Python Pandas
10 MatplotLib for Graphs
11 introduction to seaborn & scikit.
12 Projects
POWER BI
1 Business Intelligence (BI) Concepts
2 Microsoft Power BI (MSPBI) Introduction
3 Connecting Power BI with Different Data Sources
4 Power Query for Data Transformation
5 Data Modelling in Power BI
6 Reports in Power BI
7 Reports & Visualization Types in Power BI
8 Dashboards in Power B
9 Reports & Visualization Types in Power BI