PowerBI Training Certification with Python in Noida

PowerBI Training Certification with Python Course, Fees, and Jobs

PowerBI Training Certification with Python Course Description:
The Power BI Certification Training with Python course offered by Javatpoint is a comprehensive and hands-on program designed to equip learners with essential skills in data analysis, visualization, and predictive analytics using Microsoft Power BI and Python. This course is ideal for aspiring data analysts, business intelligence professionals, and anyone interested in leveraging data-driven insights to make informed business decisions.

PowerBI Training Certification Key Topics Covered:

• Introduction to Power BI and Python
• Data Extraction and Transformation using Power Query
• Data Modeling and DAX (Data Analysis Expressions)
• Creating Interactive Reports and Dashboards in Power BI
• Advanced Visualizations and Customizations
• Integrating Python in Power BI for Advanced Analytics
• Predictive Analytics using Python Libraries
• Data Insights and Decision-Making Strategies

PowerBI Training Certification Course Features:

Expert-led Training: Learn from industry experts with extensive experience in Power BI and Python.
Hands-on Projects: Work on real-world projects to apply your skills and reinforce your learning.
Comprehensive Curriculum: Cover the entire data analysis workflow, from data preparation to visualization and analysis.
Practical Exercises: Practice with datasets and gain confidence in solving data challenges.
Certification Guidance: Prepare for Power BI certification exams to boost your professional credentials.

PowerBI Training Certification Course Fees and Duration: 

Please contact Javatpoint or visit their website for the most up-to-date information regarding course fees and duration.

Prerequisites:
Basic knowledge of data analysis concepts and familiarity with Python programming is beneficial but not mandatory. Students should have a strong interest in data analytics and a willingness to learn new tools and techniques.

Who Should Attend PowerBI Training Course:

• Aspiring Data Analysts and Business Intelligence Professionals
• IT Professionals seeking to enhance their data analytics skills
• Managers and Decision Makers looking to gain insights from data
• Students and Graduates interested in pursuing a career in data analytics
• Enroll now in the Power BI Certification Training with Python course at Javatpoint to unlock the potential of data-driven decision-making and advance your career in the world of data analytics.

PowerBI Training Course Curriculum:

Introduction to Python

 What is Python?

 Features of Python

 Installation of Python

 Execution of Python Program

 Installation of IDE (Anaconda/PyCharm/Visual Studio/Sublime/Atom)

 How to work on IDE?

 Debugging Process in IDE

 What is PIP?

 What is Cpython?

 What is Jython?

 What is Ironpython?

 What is Pypy?

 Python versions

 How to give input?

 Printing to the screen

 Understanding the print() function

 Python Comments

 Python Keywords

 Python program in debugger mode

 Python interpreter architecture

 Python byte code compiler

 Python virtual machine (PVM)

 Python script mode

 How to compile Python program explicitly

Python Data Types

 About: Integer, Float, Complex Numbers, Boolean, nonetype

 String, List, Tuple, range

 Dictionary

 Set, Frozenset

 Type Conversion

Python Conditional Execution

 Boolean expressions

 Logical operators

 Conditional execution

 Alternative execution

 Chained conditionals

 Nested conditionals

 Short-circuit evaluation of logical expressions

Python Loop Statement

 Introduction to while Loop

 Introduction to for Loop

 Understanding the range() function

 What is Break statement in for Loop?

 What is Continue statement in for Loop?

 What is Enumerate function in for Loop?

Python Strings

 A string is a sequence

 Getting the length of a string using len

 Traversal through a string with a loop

 String slices

 Strings are immutable

 Looping and counting

 The in operator

 String comparison

 String methods

 Parsing strings

 Format operator

Python List

 Introduction to List

 How to create and access list

 Traversing a list

 What are List indices

 Lists and functions

 Deleting elements

 Basic List operations

 List slices

 List Comprehension

 List built-in methods

 Aliasing

 List arguments

Python Tuples

 Introduction to tuple

 How to access tuple element

 Basic tuple operations

 How to compare tuples?

 How to create nested tuple?

 About Tuple functions and methods

 How to use tuples as keys in dictionaries?

 How to Delete Tuple?

 About Slicing of Tuple

 What is Tuple immutability?

Python Set

 How to create a set, and iteration over set

 Python set operations

 Python set methods

 Set built-in methods

 Python Frozensets

Python Dictionary

 Introduction to dictionary

 How to declare dictionary?

 Properties of dictionary

 Dictionary as a set of counters

 Accessing Items from Dictionary

 Python Hashing

 Updating Dictionary

 Copying Dictionary

 Advanced text parsing

 Dictionary basic operations

 Advanced text parsing

 Sorting the Dictionary

 Looping and dictionaries

 Dictionary built-in methods

Variables, expressions, and statements

 Values and types

 Variables

 Variable names and keywords

 Statements

 Operators and operands

 Expressions

 Order of operations

 Modulus operator

 String operations

 Comments

 Choosing mnemonic variable names

Python Functions

 What is a Function?

 Why functions?

 Define and call a function

 Types of Functions

 Built-in functions

 Significance of Indentation (Space) in Python

 Return Statement

 Adding new functions

 Types of Arguments in Functions

 Parameters and arguments

 Default Arguments, Non-Default Arguments

 Keyword Arguments, Non-keyword Arguments, Arbitrary Arguments

 Type conversion functions

 Scope of variables

 Anonymous Functions

 Math functions

 Random numbers

 Map(), filter(), reduce() functions

 Definitions and uses

 Generator function

 Decorator function

 Python Iterator

 Function as arguments

 Nested functions

 Flow of execution

 Fruitful functions and void functions

 Functions as return statement

 Function return statement

 Closure

Python Iteration

 Updating variables

 The while statements

 Infinite loops

 Finishing iterations with continue

 Definite loops using for

•  Loop patterns
  • Counting and summing loops
  • Maximum and minimum loops

Advanced Python

Exception Handling in Python

 What is Exception Handling

 Try Expert

 Many Exceptions

 Else in Exception Handling

 Finally Keyword

 Raise an exception

 Common RunTime Errors in Python

 Try …Except

 Try …Except …else

 Try …finally

 Abnormal termination

 Python Errors

 Hashability

Python Class and Object

 Introduction to OOPs Programming

 Object Oriented Programing System and its Principles

 Basic concepts of Object and Classes

 How to define Python Classes

 Self-variable in Python

 Access Modifier

 What is inheritance and its Types?

 How inheritance Works

Python Regular Expressions

 What is Regular Expression?

 Regular Expression Syntax

 Extracting data using regular expressions

 What is the need of Regular expressions?

 Character matching in regular expressions

 Combining searching and extracting

 About Re module

 About Regular expression Patterns

 About Literal characters and Meta characters

 Functions/ methods related to rogex

Modules and Packages

 Why Modules?

 How to Import Modules?

 Script v/s Module

 Standard v/s third party Modules

 Why packages

File Handling

 About File Handling

 How to create a File

 Pass by reference vs Value

 Append Data to a File

 How to read a File

 How to Read File line by line

 About Files modes and its syntax

 Lambda Expressions

 Understanding File Handling with Block

Python Data Structure

 How to implement Lists and its methods?

 How implement Tuple and its methods?

 How implement Set and its methods?

 Difference between List, Tuple and Set

 How implement Dictionary and its methods?

Database

 Introduction to Database

 About Database concepts

 What is Database Package?

 Understanding Data Storage

 Basic data modeling

 Database Browser for SQLite

 Structured Query Language summary

 About Relational Database (RDBMS) concepts

 Hosting a Database on Cloud/Local System

SQL

 SQL (Structured Query Language) Basics

 DML (Data Manipulation Language), DDL (Data Definition Language), DQL (Data Query Language)

 How to create, alter and drop the DDL?

 How to insert, update, delete and merge the DML?

 How to select the DQL?

 SQL constraints

 Primary and foreign key, composite key

 How to select distinct?

•  SQL operators
  • Addition (+)
  • Subtraction (-)
  • Multiplication (*)
  • Division (/)
  • Modulus (%)
•  SQL Comparison Operators:
  • =
  • !=
  • <>
  • >
  • <
  • >=
  • <=
  • !<
  • !>
•  SQL Logical Operators:
  • ALL
  • AND
  • ANY
  • BETWEEN
  • EXISTS
  • IS NULL
  • OR
  • UNIQUE
•   SQL like, where, order by, view, joins, aliases
•  Joins:
  • Inter Join
  • Full (Outer) Join
  • Left (Outer) Join
  • Right (Outer) Join
•  MySQL Functions
•  String Functions:
  • Char_length
  • Lower
  • Reverse
  • Upper
•  Numeric Functions:
  • Max
  • Min
  • Sum
  • Avg
  • Count
  • abs
•  Date Functions:
  • Curdate
  • Curtime
  • Now

Python for Data Analytics

NumPy Package

 What is NumPy array?

 Array Constructor

 Introduction to Array

 Range() function

 LINPAC

 How to create 2-D Arrays

 About: Vector Operation and Matrix Operation

 What is Array indexing and Slicing?

 Indexing in 1-D Arrays

 Indexing in 2-D Arrays

 Slicing in 1-D Arrays

 Slicing in 2-D Arrays

 Scalar Vectorization

 Array Comparison

Pandas Package

 Introduction to pandas

 Pandas and Data Manipulation

 What is Labeled and structured data?

 What are Series and DataFrame objects?

 What is Data Cleansing?

 What is Data normalization?

 What is Data visualization?

 Deleting and Dropping Columns

 Series

 Apply() function

 Creating Series

 Data Frame and Basic Functionality

 Head() function

 About: Merges and Joins

 What is Data inspection?

 What is Data fill?

 Mean() function

 Data Frame Manipulation

 Indexing and missing Values

 Grouping and Reshaping

How to load datasets

 From excel

 From CSV

 From HTML table

Accessing Data from DataFrame

  at and iat

 loc() Function and Iloc() function

 head() Function and tail() Function

Exploratory Data Analysis (EDA)

 About describe() function

 groupby() function

 crosstab() function

 About Boolean slicing and query

Data Cleaning

 About: Map() and apply() functions

 How to combine Data Frames?

 How to add and remove rows and columns?

 How to sort data?

 How to handle missing values?

 How to handle duplicates?

 How to handle data error?

 How to handle Date and Time?

 Hosting a Database on Cloud or local system

 CRUD Operation on Database Tables trough Python

 Processing and Cleaning Data through Pandas methods

 Dealing with missing values

Python for Data Visualization:

 Introduction to Data Visualization

Matplotlib package:

 Introduction to MatPlotlib Library

 How to use matplotlib.pyplot interface

 Types of charts

 How to plot Histogram and pie chart?

 About: Bar Chart, Stacked Chart, Scatter plot

 Outlier detection using Boxplot

 Adding data to an Axes object

 How to customize plots?

 How to customize Data appearance?

 How to create a grid of subplots?

 Area plot for Indexed Data

Seaborn package:

 Introduction to Seaborn library

 How to show Seaborn Plots?

 How to use Seaborn with Matplotlib defaults?

 How to set xlim and ylim in Seaborn?

 Visualizing networks and interconnections

Introduction to Statistics

 Sample and population

•  Measures of central tendency:
  • Arithmetic mean
  • Harmonic mean
  • Geometric mean
  • Mode
  • First quartile, Second quartile (median), Third quartile
  • Standard deviation
•  Graphical exploratory Data Analysis
•  How to plot and compute simple summary Statistics
•  Quantitively exploratory Data Analysis

Probability Distribution

 Introduction to probability

 What is Conditional Probability?

 What is Normal Distribution?

 What is Uniform Distribution?

 What is Exponential Distribution?

 About Right and Left skewed Distribution

 What is Random Distribution?

 About Central Limit Theorem

 Probabilistically- Discrete variables

 Statistical interface rests upon probability

 Thinking Probabilistically- Continuous variables

Hypothesis Testing

 What is Normality?

 What is Mean Test?

 About T-test

 About Z-test

 What is ANOVA test?

 What is Chi square test?

 About Correlation and covariance

Advanced Excel:

•  Data Visualization:
  • How to specify a valid range of values for a cell?
  • How to specify a list of valid values for a cell?
  • How to specify custom validations based on formula for a cell?
•  Working with templates:
  • How to design the structure of a template?
  • How to use templates for standardization of worksheets?
•  Sorting and Filtering Data
  • How to sort tables?
  • How to use multiple-level sorting and custom sorting?
  • How to filter data for selected view?
  • How to use advanced filter options?
•  Working with Reports
  • How to create subtotals and multi-level subtotals?
  • How to create, format and customize Pivot tables and Pivot charts?
  • How to use advanced options of Pivot tables?
  • How to use external data sources?
  • How to create slicers?
•  WhatIf Analysis
  • How to seek goal?
  • How to create data tables?
  • How to create scenario manager?
•  Charts
  • How to use and format charts?
  • How to use 3D Graphs?
  • How to use Bar and Line chart together?
  • How to use Secondary Axis in Graphs?

Tableau:

•  Tableau Home
  • Tableau overview
  • Environment setup
  • About Navigations
  • About Design flow
  • About Files Types
  • About Data Terminology
•  Data Sources:
  • How to customize data view?
  • How to extract data?
  • How to use field operations?
  • How to edit metadata?
  • What is Data joining?
  • What is Data Blending?
•  Tableau Worksheets:
  • How to add worksheets?
  • How to rename and reorder worksheets?
  • How to save and delete worksheets?
•  Tableau Calculation:
  • Numeric Calculation operations and Functions
  • String Calculation operations and Functions
  • Date Calculation functions
  • Table Calculation functions
  • Load expressions and operations
•  Tableau Sorting and Filter:
  • How to use basic sorting and basic filters?
  • How to use quick filters, conditional filters, top filters, context filters and Filter operations?

BONUS

 How big is Big Data?

 How to store BIG DATA in Commodity Hardware's?

 Current processing frameworks

 Cluster Computing architecture insights

 Maintaining High Availability of data

 About Market domain and its growth?