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DevLustro Certified Data Analyst – Training Course

What the specialist says

Businesses don’t want reports, they want decisions — this course shows you how to build exactly that.

Sujatha N Data & BI Specialist

Acquire Key Data Analysis Skills: Master Data Analytics, Earn Certification, Launch Your Data Career! The DevLustro Certified Data Analyst Training Course offers comprehensive instruction in R, Tableau, and Power BI ,  To build expertise in data analysis and visualization. Additionally, students can enhance their programming skills with a Core & Advanced Python Programmer Course , Upon completion of these courses, students gain industry-relevant knowledge and tools to excel in the field of data analytics. DevLustro provides 100% placement assurance , ensuring opportunities in top organizations. This program is designed to equip learners with the skills required for high-demand roles. Course was selected for our collection of top-rated courses trusted by businesses worldwide.

Our Core Highlights

World Class Instructor
World Class Instructor Mentorship from global experts
1:1 with Industry Expert
1:1 with Industry Expert Personalised coaching tailored to you
Global Hiring Network
Global Hiring Network 400+ hiring partners around the world
Average Salary Hike
Average Salary Hike 55% average hike for our alumni

Course Description

Acquire Key Data Analysis Skills: Master Data Analytics, Earn Certification, Launch Your Data Career! The Elysium Certified Data Analyst Training Course offers comprehensive instruction in R, Tableau, and Power BI ,  To build expertise in data analysis and visualization. Additionally, students can enhance their programming skills with a Core & Advanced Python Programmer Course , Upon completion of these courses, students gain industry-relevant knowledge and tools to excel in the field of data analytics. Elysium provides 100% placement assurance , ensuring opportunities in top organizations. This program is designed to equip learners with the skills required for high-demand roles. Course was selected for our collection of top-rated courses trusted by businesses worldwide.

Data Analyst Course

Course Details

Gain expertise in data visualization techniques to communicate insights effectively.

Understand and apply data governance and compliance policies.

Data Analysis is the infrastructure that enables the extraction of insights from data.

Data Cleaning is where data will be cleansed and duplicates removed.

Data Analysts understand data and derive meaningful insights.

Data Analysis is the foundation on which data-driven decision-making and business intelligence are built.

Course Goals

  • Master data analysis fundamentals, including data manipulation, visualization, and reporting.
  • Dive into advanced concepts such as predictive modeling and statistical analysis.
  • Learn to use powerful tools like SQL, Excel, Tableau, and Power BI.

Future Scope of this Course

  • Recognized worldwide

Our Career Service

  • Elysium Certified Data Analyst – Training Course
  • Personalized coordinator.
  • Trainer feedback.
  • Trainer availability post sessions.
  • Get your staff certified.
  • Certificate from governing bodies.

Our Training Program Benefits

  • Real-World Data Analysis Projects
  • Hands on assignment
  • Develop practical skills through hands-on labs and real-world projects.
  • Curriculum that focuses on the learner.
  • Live, interactive training by DevLustro experts.
  • Curriculum aligned with current industry practices.
  • Portfolio / project support for real-world use.
01Chapter-1 R Introduction
  • 01.01Introduction to R Studio
  • 01.02R Installation
  • 01.03R Advantages and Disadvantages
  • 01.04R Hadoop Integration
  • 01.05R Packages
  • 01.06List of R Packages
  • 01.07Basic Syntax
  • 01.08Comments
  • 01.09Data Types
  • 01.10Data Structures
  • 01.11Variables
  • 01.12Keywords
  • 01.13Operators
  • 01.14Input/Output
  • 01.15R Variables
  • 01.16Scope of Variables
  • 01.17Dynamic Scoping
  • 01.18Lexical Scoping
02Chapter-2 Control Statements
  • 02.01R If Statement
  • 02.02If-else Statement
  • 02.03else if Statement
  • 02.04R Switch Statement
  • 02.05R Next Statement
  • 02.06R Break Statement
  • 02.07R For Loop
  • 02.08R Repeat Loop
  • 02.09R While Loop
  • 02.10Create Functions
  • 02.11Function Arguments
  • 02.12Types of Functions
  • 02.13Recursive Function
  • 02.14Conversion Functions
  • 02.15Local and Global Variables
03Chapter-3 Data Structures
  • 03.01Strings
  • 03.02Lists
  • 03.03Arrays
  • 03.04Matrix
  • 03.05Data Frame
  • 03.06Classes
  • 03.07Objects
  • 03.08Encapsulation
  • 03.09Polymorphism
  • 03.10Inheritance
  • 03.11Abstraction
  • 03.12Looping Over Objects
  • 03.13S3 Class
  • 03.14Explicit
  • 03.15R Debugging
  • 03.16Error Handling
  • 03.17Reading Files
  • 03.18Writing Files
  • 03.19Working with Binary Files
  • 03.20R CSV File
  • 03.21R Excel File
  • 03.22R Binary File
  • 03.23R JSON File
  • 03.24R XML File
  • 03.25R Database
  • 03.26R Data Visualization
  • 03.27R Pie Charts
  • 03.28R Boxplot
  • 03.29R Histogram
  • 03.30R Line Graphs
  • 03.31R Scatterplots
04Chapter-4 Manipulating Data
  • 04.01Selecting Rows/Observations
  • 04.02Selecting Columns/Fields
  • 04.03Merging Data
  • 04.04Relabeling the Column Names
  • 04.05Converting Variable Types
  • 04.06Data Sorting
  • 04.07Data Aggregation
  • 04.08Linear Regression
  • 04.09Multiple Regression
  • 04.10Logistic Regression
  • 04.11Poisson Regression
  • 04.12Normal Distribution
  • 04.13Binomial Distribution
  • 04.14Classification in R
  • 04.15Time Series Analysis
  • 04.16Random Forest in R
  • 04.17T-Test in R Chi-Square Test
05Chapter-5 Introduction to Tableau
  • 05.01What is Tableau
  • 05.02Architecture of Tableau
  • 05.03Features of Tableau
  • 05.04Installation of Tableau Desktop/Public
  • 05.05Navigation
  • 05.06Design Flow
  • 05.07File System
  • 05.08Data Types
  • 05.09Data Source Connection
  • 05.10Import Excel File
  • 05.11Data Cleaning
  • 05.12Joining Databases
  • 05.13Data Blending
  • 05.14Splitting Text to Columns
  • 05.15Displaying Data in Worksheet
  • 05.16Adding, Renaming, and Duplicating Fields
  • 05.17Pivot Table and Heat Map
  • 05.18Highlight Table
  • 05.19Bar Chart
  • 05.20Line Chart
  • 05.21Area Chart
  • 05.22Pie Chart
  • 05.23Scatter Plot
  • 05.24Word Cloud
  • 05.25Tree Map
  • 05.26Blended Axis
  • 05.27Dual Axis
06Chapter-6 Advance Data Visualization/Graph
  • 06.01Bar Chart
  • 06.02Stacked Bar Chart
  • 06.03Bar in Bar Chart
  • 06.04Combo Chart
  • 06.05Line Chart
  • 06.06Single Axis
  • 06.07Dual Axis
  • 06.08Blended Axis
  • 06.09Dual Axis Chart
  • 06.10Line
  • 06.11Lollipop Chart
  • 06.12Donut
  • 06.13Bullet Graph
  • 06.14Histogram Chart
  • 06.15Animated Graph
07Chapter-7 Building View Advance Map Option
  • 07.01Explain Latitude and Longitude
  • 07.02Default Location/Edit Locations
  • 07.03Symbol Map & Filled Map
  • 07.04Map Layer
  • 07.05Image in Map
  • 07.06Map Option
  • 07.07Connecting to Different Data Sources
  • 07.08Excel
  • 07.09SQL Server
  • 07.10Live vs Extract Connection
  • 07.11Creating Extract
  • 07.12Refreshing Extract
  • 07.13Increment Extract
  • 07.14Refreshing Live
  • 07.15Data Source Editor
  • 07.16Pivoting and Splitting
  • 07.17Data Interpreter: Clean Dirty Data
  • 07.18TWB vs TWBX
  • 07.19How to Create a Packaged Workbook
  • 07.20Difference Between .tde and .hyper File
08Chapter-8 Advanced Data Preparation
  • 08.01Joins
  • 08.02Inner Join
  • 08.03Left
  • 08.04Right
  • 08.05Outer
  • 08.06Complex Joins
  • 08.07Referential Integrity
  • 08.08Union
  • 08.09Data Blending and When Required
  • 08.10Cross-Database Join
  • 08.11Why Visualization Comes into the Picture?
  • 08.12Importance of Visualizing Data
  • 08.13Poor Visualization vs Perfect Visualization
  • 08.14Principles of Visualization
  • 08.15Goal of Data Visualization
  • 08.16Filter
  • 08.17Types of Filters
  • 08.18Quick Filter
  • 08.19Global Filter
  • 08.20Normal Filter
  • 08.21Relevant Filter
  • 08.22Dimension Filter
  • 08.23Measure Filter
  • 08.24Condition-Based Filter
  • 08.25Advanced Filter Using Wildcards
  • 08.26Right-Click Filtering
  • 08.27Top N / Bottom N Filter
  • 08.28Filtering Order of Operation
  • 08.29Extract Filter
  • 08.30Data Source Filter
  • 08.31Context Filter
  • 08.32Action Filters
  • 08.33Filter
  • 08.34Highlight
  • 08.35Go to URL
  • 08.36Go to Sheet
  • 08.37Set Action
  • 08.38Parameter Action
  • 08.39Action Jumps
  • 08.40Viz in Tooltips
09Chapter-9 Basic Calculation
  • 09.01Sorting
  • 09.02Calculation - String, Basic, Dote and Logic
  • 09.03Continuous and Discrete data
  • 09.04Workinq with Dotes
  • 09.05Creating calculated Fields
  • 09.06Logical Functions
  • 09.07Case If Function
  • 09.08ZN Function
  • 09.09Else If Function
  • 09.10Ad-Hoc Functions
  • 09.11Manipulating Text - left and riqht function
  • 09.12Table Calculation
  • 09.13Running Total
  • 09.14Percent Calculation
  • 09.15Percent of Total
  • 09.16Year over Year Growth
  • 09.17Include
  • 09.18Exclude
  • 09.19Fixed
10Chapter-10 Grouping Data/Dynamic Representation
  • 10.01Groups
  • 10.02Sets
  • 10.03In/Out Sets
  • 10.04Combined Sets
  • 10.05Top and Bottom in Single View Parameters
  • 10.06Dynamic Measure
  • 10.07Dynamic Dimension
  • 10.08Hierarchies
  • 10.09Bins
  • 10.10Combined Field
  • 10.11Trend Line
  • 10.12Forecasting
  • 10.13Clustering
  • 10.14Reference Line
  • 10.15Box Plot (Understanding Outliers in Data)
  • 10.16Distribution Band
  • 10.17Reference Band
  • 10.18Size
  • 10.19Updating Axis
  • 10.20Colors
  • 10.21Borders
  • 10.22Transparency
  • 10.23Chart Line
  • 10.24Reference Line
  • 10.25Mark Label
  • 10.26Annotation
  • 10.27Responsive Tool Tip
  • 10.28Canvas Selection
  • 10.29Tiled Objects
  • 10.30Floating Objects
  • 10.31Pixel Perfect Alignment
  • 10.32Summary Box
  • 10.33Chart Titles and Captions
  • 10.34Adding Image and Text
  • 10.35Adding Shadowing
  • 10.36Adding Separator Lines
  • 10.37Dynamic Chart Titles
  • 10.38Information Icons
  • 10.39Creating a Story
  • 10.40Publishing to PDF
  • 10.41Exporting to Pivot Tables and Images
  • 10.42Exporting Packaged Workbooks
  • 10.43Tableau Reader
  • 10.44Tableau Online
  • 10.45Tableau Server
  • 10.46Tableau Public
  • 10.47Version Control
11Chapter-11 lntroduction To Power Bi
  • 11.01Introduction to Power BI - Need, Importance
  • 11.02Power BI - Advantages and Scalable Options
  • 11.03History - Power View, Power Query, Power Pivot
  • 11.04Power BI Data Source Library and DW Files
  • 11.05Cloud Collaboration and Usage Scope
  • 11.06Business Analyst Tools, MS Cloud Tools
  • 11.07Power BI Installation and Cloud Account
  • 11.08Power BI Cloud and Power BI Service
  • 11.09Power BI Architecture and Data Access
  • 11.10On-Premise Data Access and Microsoft OneDrive
  • 11.11Power BI Desktop - Installation, Usage
  • 11.12Sample Reports and Visualization Controls
  • 11.13Power BI Cloud Account Configuration
  • 11.14Understanding Desktop & Mobile Editions
  • 11.15Report Rendering Options and End User Access
  • 11.16Power View and Power Map, Power BI Licenses
12Chapter-12 Report visualizations and Properties
  • 12.01Power BI Design: Conversions, Visualizations, and Fields
  • 12.02Import Data Options with Power BI Model, Advantages
  • 12.03Direct Query Options and Real-time (LIVE) Data Access
  • 12.04Data Fields and Filters with Visualizations
  • 12.05Visualization Filters, Page Filters, Report Filters
  • 12.06Conditional Filters and Clearing, Testing Sets
  • 12.07Creating Customized Tables with Power BI Editor
  • 12.08General Properties, Sizing, Dimensions, and Positions
  • 12.09Alternate Text and Tiles, Header (Column, Row) Properties
  • 12.10Grid Properties (Vertical, Horizontal) and Styles
  • 12.11Table Styles: Alternate Row Colors - Static, Dynamic
  • 12.12Sparse, Flashy Rows, Condensed Table Reports, Focus Mode
  • 12.13Totals Computations, Background, Borders Properties
  • 12.14Column Headers, Column Formatting, Value Properties
  • 12.15Conditional Formatting Options: Color Scale
  • 12.16Page-Level Filters and Report-Level Filters
  • 12.17Visual-Level Filters and Format Options
  • 12.18Report Fields, Formats, and Analytics
  • 12.19Page-Level Filters and Column Formatting, Filters
  • 12.20Background Properties, Borders, and Lock Aspect
  • 12.21Chart Report Types and Properties
  • 12.22Stacked Bar Chart, Stacked Column Chart
  • 12.23Clustered Bar Chart, Clustered Column Chart
  • 12.24100% Stacked Bar Chart, 100% Stacked Column Chart
  • 12.25Line Charts, Area Charts, Stacked Area Charts
  • 12.26Line and Stacked Row Charts
  • 12.27Line and Stacked Column Charts
  • 12.28Waterfall Chart, Scatter Chart, Pie Chart
  • 12.29Field Properties: Axis, Legend, Value, Tooltip
  • 12.30Field Properties: Color Saturation, Filter Types
  • 12.31Formats: Legend, Axis, Data Labels, Plot Area
  • 12.32Data Labels: Visibility, Color, and Display Units
  • 12.33Data Labels: Precision, Position, Text Options
  • 12.34Analytics: Constant Line, Position, Labels
  • 12.35Working with Waterfall Charts and Default Values
  • 12.36Modifying Legends and Visual Filters - Options
  • 12.37Map Reports: Working with Map Reports
  • 12.38Hierarchies: Grouping Multiple Report Fields
  • 12.39Hierarchy Levels and Usage in Visualizations
  • 12.40Preordered Attribute Collection - Advantages
  • 12.41Using Field Hierarchies with Chart Reports
  • 12.42Advanced Query Mode or Connection Settings - Options
  • 12.43Direct Import and In-memory Loads, Advantages
  • 12.44Hierarchies and Drilldown Options
  • 12.45Hierarchy Levels and Drill Modes - Usage
  • 12.46Drill-through Options with Tree Map and Pie Chart
  • 12.47Higher Levels and Next Level Navigation Options
  • 12.48Aggregates with Bottom/Up Navigations
  • 12.49Multi-Field Aggregations and Hierarchies in Power BI
  • 12.50DRILLDOWN, SHOWNEXTLEVEL, EXPANDTONEXTLEVEL
  • 12.51SEE DATA and SEE RECORDS Options - Differences
  • 12.52Toggle Options with Tabular Data, Filters
  • 12.53Drilldown Buttons and Mouse Hover Options - Visuals
  • 12.54Dependent Aggregations, Independent Aggregations
  • 12.55Automated Records Selection with Tabular Data
  • 12.56Report Parameters: Creation and DataType
  • 12.57Available Values and Default Values, Member Values
  • 12.58Parameters for Column Data and Table / Query Filters
  • 12.59Parameters Creation - Query Mode, UI Option
  • 12.60Linking Parameters to Query Columns - Options
  • 12.61Edit Query Options and Parameter Manage Entries
  • 12.62Connection Parameters and Dynamic Data Sources
  • 12.63Synonyms - Creation and Usage Options
13Chapter-13 Power Query & M Language
  • 13.01Power BI Interface and Query / Dataset Edits
  • 13.02Working with Empty Tables and Load / Edits
  • 13.03Empty Table Names and Header Row Promotions
  • 13.04Undo Headers Options. Blank Columns Detection
  • 13.05Data Imports and Query Marking in Query Editor
  • 13.06JSON Files & Binary Formats with Power Query
  • 13.07JavaScript Object Notation - Usage with M Language
  • 13.08Applied Steps and Usage Options. Revert Options
  • 13.09Creating Query Groups and Query References. Usage
  • 13.10Query Rename, Load Enable and Data Refresh Options
  • 13.11Combine Queries - Merge Join and Anti-Join Options
  • 13.12Combine Queries - Union and Union All as New Dataset
  • 13.13M Language: NestedJoin and JoinKind Functions
  • 13.14REPLACE, REMOVE ROWS, REMOVE COL, BLANK - M Language
  • 13.15Column Splits and FilledUp / FilledDown Options
  • 13.16Query Hide and Change Type Options. Code Generation
  • 13.17Invoke Function and Freezing Columns
  • 13.18Creating Reference Tables and Queries
  • 13.19Detection and Removal of Query Datasets
  • 13.20Custom Columns with Power Query
  • 13.21Power Query Expressions and Usage
  • 13.22Blank Queries and Enumeration Value Generation
  • 13.23M Language Semantics and Syntax. Transform Types
  • 13.24IF..ELSE Conditions, TransformColumn() Types
  • 13.25RemoveColumns(), SplitColumns(), ReplaceValue()
  • 13.26Table.Distinct Options and GROUP BY Options
  • 13.27Table.Group(), Table.Sort() with Type Conversions
  • 13.28PIVOT Operation and Table.Pivot().List Functions
  • 13.29Using Parameters with M Language (Power Query Editor)
  • 13.30Advanced Query Editor and Parameter Scripts
  • 13.31List Generation and Table Conversion Options
  • 13.32Aggregations using Power Query & Usage in Reports
  • 13.33Report Generation using Web Pages & HTML Tables
  • 13.34Reports from Page Collection with Power Query
  • 13.35Aggregate and Evaluate Options with M Language
  • 13.36Creating High-Density Reports, ArcGIS Maps, ESRI Files
  • 13.37Generating QR Codes for Reports
  • 13.38Table Bars and Drill Thru Filters
14Chapter-14 Dax Expressions - Level 1
  • 14.01Purpose of Data Analysis Expressions (DAX)
  • 14.02Scope of Usage with DAX, Usability Options
  • 14.03DAX Context: Row Context and Filter Context
  • 14.04DAX Entities: Calculated Columns and Measures
  • 14.05DAX Data Types: Numeric, Boolean, Variant, Currency
  • 14.06Date-time Data Type with DAX, Comparison with Excel
  • 14.07DAX Operators & Symbols, Usage, Operator Priority
  • 14.08Parenthesis, Comparison, Arithmetic, Text, Logic
  • 14.09DAX Functions and Types: Table Valued Functions
  • 14.10Filter, Aggregation, and Time Intelligence Functions
  • 14.11Information Functions, Logical, Parent-Child Functions
  • 14.12Statistical and Text Functions, Formulas and Queries
  • 14.13Syntax Requirements with DAX, Differences with Excel
  • 14.14Naming Conventions and DAX Format Representation
  • 14.15Working with Special Characters in Table Names
  • 14.16YTD, QTD, MTD Calculations with DAX
  • 14.17DAX Calculations and Measures
  • 14.18Using TOPN, RANKX, RANK.EQ
  • 14.19Computations using STDEV, VAR
  • 14.20SAMPLE Function, COUNTALL, ISERROR
  • 14.21ISTEXT, DATEFORMAT, TIMEFORMAT
  • 14.22Time Intelligence Functions with DAX
  • 14.23Data Analysis Expressions and Functions
  • 14.24DATESYTD, DATESQTD, DATESMTD
  • 14.25ENDOFYEAR, ENDOFQUARTER, ENDOFMONTH
  • 14.26FIRSTDATE, LASTDATE, DATESBETWEEN
  • 14.27CLOSINGBALANCEYEAR, CLOSINGBALANCEQTR
  • 14.28SAMEPERIOD and PREVIOUSMONTH, QUARTER
  • 14.29KPIs with DAX, Vertipaq Queries in DAX
  • 14.30IF..ELSEIF.. Conditions with DAX
  • 14.31Slicing and Dicing Options with Columns, Measures
  • 14.32DAX for Query Extraction, Data Mashup Operations
  • 14.33Calculated Columns and Calculated Measures with DAX
15Chapter-15 Powerbi Deployment & Cloud
  • 15.01Power BI Report Validation and Publish
  • 15.02Understanding Power BI Cloud Architecture
  • 15.03Power BI Cloud Account and Workspace
  • 15.04Reports and DataSet Items Validation
  • 15.05Dashboards and Pins - Real-time Usage
  • 15.06Dynamic Data Sources and Encryptions
  • 15.07Personal and Organizational Content Packs
  • 15.08Gateways, Subscriptions, Mobile Reports
  • 15.09Data Refresh with Power BI Architecture
  • 15.10PBIX and PBIT Files with Power BI - Usage
  • 15.11Visual Data Imports and Visual Schemas
  • 15.12Cloud and On-Premise Data Sources
  • 15.13How Power BI Supports Data Model?
  • 15.14Relation between Dashboards to Reports
  • 15.15Relation between Datasets to Reports
  • 15.16Relation between Datasets to Dashboards
  • 15.17Page to Report - Mapping Options
  • 15.18Publish Options and Data Import Options
  • 15.19Need for Pins & Visuals and Pins & Reports
  • 15.20Need for Data Streams and Cloud Integration
  • 15.21Report Publish Options and Verifications
  • 15.22Working with Power BI Cloud Interface & Options
  • 15.23Navigation Paths with "My Workspace" Screens
  • 15.24FILE, VIEW, EDIT REPORTS, ACCESS, DRILLDOWN
  • 15.25Saving Reports into pdf, pptx, etc. Report Embed
  • 15.26Report Rendering and EDIT, SAVE, Print Options
  • 15.27Report PIN and individual Visual PIN Options
  • 15.28Create and Use Dashboards. Menu Options
  • 15.29Goto Dashboard and Goto LIVE Page Options
  • 15.30Operations on Pinned Reports and Visuals
  • 15.31TITLE, MEDIA, USAGE METRICS & FAVOURITES
  • 15.32SUBSCRIPTION Options and Reports with Mobile View
  • 15.33Options with Report Page: Print and Subscribe
  • 15.34Report Actions: USAGE METRICS, ANALYSE IN EXCEL
  • 15.35Report Actions: RELATED ITEMS, RENAME, DELETE
  • 15.36Dashboard Actions: METRICS, RELATED ITEMS
  • 15.37Dashboard Actions: SETTINGS FOR Q & A, DELETE
  • 15.38PIN Actions: METRICS, SHARE, RELATED ITEMS
  • 15.39PIN Actions: SETTINGS FOR Q & A, DELETE
  • 15.40EDIT DASHBOARD (CLOUD), On-The-Fly Reports
  • 15.41Dataset Actions: CREATE REPORT, REFRESH
  • 15.42SCHEDULED REFRESH & RELATED ITEMS
  • 15.43Dashboard Integration with Apps in Power BI
  • 15.44Publish Power BI Report Templates
  • 15.45Import and Export Options with Power BI
  • 15.46Dataset Navigations and Report Innovations
  • 15.47Quick Navigation Options with "My Workspace"
  • 15.48Dashboards, Workbooks, Reports, Datasets
  • 15.49Working with MY WORKSPACE group
  • 15.50Installing the Power BI Personal Gateway
  • 15.51Automatic Refresh - Possible Issues
  • 15.52Adding images to the dashboards
  • 15.53Reading & Editing Power BI Views</li
  • 15.54Managing report in Power BI Services
  • 15.55PowerBl Gateway - Download and Installation
  • 15.56Personal and Enterprise Gateway Features
  • 15.57PowerBl Settings : Dataset - Gateway lnteqrotion
  • 15.58Configurinq Dataset for Manual Refresh of Data
  • 15.59Configuring Automatic Refresh and Schdules
  • 15.60Workbooks and Alerts with Power BI
  • 15.61Dataset Actions and Refresh Settinqs with Gateway
16Chapter-16 Insights And Subscriptions
  • 16.01Data Navigation Paths and Data Splits
  • 16.02Getting data from existing systems
  • 16.03Data Refresh and LIVE Connections
  • 16.04pbit and pbix: differences. Usage Options
  • 16.05Quick Insights for Power BI Reports
  • 16.06Quick Insights for Power BI Dashboards
  • 16.07Generating Insights with Cloud Datasets
  • 16.08Generating Reports with Cloud Datasets
  • 16.09Using relational databases on-premises
  • 16.10Using relational databases in the cloud
  • 16.11Consuming a service content pack
  • 16.12Creating a custom dataset from a service
  • 16.13Creating a content pack for your organization - Consuming an organizational content pack
  • 16.14Updating an organizational content pack
  • 16.15Adding Tiles Images, Videos, Data Streams
  • 16.16Creating New Reports from Cortana, Advantages
17Chapter-17 Introduction To Script
  • 17.01What is Script, Program?
  • 17.02Types of Scripts
  • 17.03Difference between Script and Programming Languages
  • 17.04Features and Limitations of Scripting
  • 17.05Types of Programming Language Paradigms
  • 17.06What is Python?
  • 17.07Why Python?
  • 17.08Who Uses Python?
  • 17.09Characteristics of Python
  • 17.10What is PSF (Python Software Foundation)?
  • 17.11History of Python
  • 17.12Python Versions
  • 17.13How to Download and Install Python
  • 17.14Install Python with Different IDEs
  • 17.15Features and Limitations of Python
  • 17.16Creating Your First Python Program
  • 17.17Printing to the Screen
  • 17.18Reading Keyboard Input
  • 17.19Using Command Prompt and GUI or IDE
  • 17.20Python Distributions
18Chapter-18 Different Modes In Python
  • 18.01Execute the Script
  • 18.02Interactive and Script Mode
  • 18.03Python File Extensions
  • 18.04Setting PATH in Windows
  • 18.05Clear screen inside Python
  • 18.06Learn Python Main Function
  • 18.07Python Comments
  • 18.08Quit the Python Shell
  • 18.09Shell as a Simple Calculator
  • 18.10Order of Operations
  • 18.11Multiline Statements
  • 18.12Quotations in Python
  • 18.13Python Path Testing
  • 18.14Joining Two Lines
  • 18.15Python Implementation Alternatives
  • 18.16Subpackages in Python
  • 18.17Uses of Python in Data Science, IoT
  • 18.18Working with Python in Unix/Linux/Windows/Mac/Android
  • 18.19PyCharm IDE
  • 18.20How to Work on PyCharm
  • 18.21PyCharm Components
  • 18.22Debugging Process in PyCharm
  • 18.23Python Install Anaconda
  • 18.24What is Anaconda?
  • 18.25Coding Environments
  • 18.26Spyder Components
  • 18.27General Spyder Features
  • 18.28Spyder Shortcut Keys
  • 18.29Jupyter Notebook
  • 18.30What is Conda? And Conda List?
  • 18.31Jupyter and Kernels
  • 18.32What is PIP?
19Chapter-19 Variables In Python
  • 19.01What is a Variable?
  • 19.02Variables and Constants in Python
  • 19.03Variable Names and Values
  • 19.04Mnemonic Variable Names and Types
  • 19.05What Does "Type" Mean?
  • 19.06Multiple Assignment
  • 19.07Python's Different Numerical Types
  • 19.08What is a Data Type?
  • 19.09Types of Data Types
  • 19.10Numbers
  • 19.11List
  • 19.12Tuple
  • 19.13Strings
  • 19.14Dictionary
  • 19.15Sets
  • 19.16Lists are Mutable
  • 19.17Getting to Lists
  • 19.18List Indices
  • 19.19Traversing a List
  • 19.20List Operations, Slices, and Methods
  • 19.21Map, Filter, and Reduce
  • 19.22Deleting Elements
  • 19.23Lists and Strings
  • 19.24Advantages of Tuple over List
  • 19.25Packing and Unpacking
  • 19.26Comparing Tuples
  • 19.27Creating Nested Tuples
  • 19.28Using Tuples as Keys in Dictionaries
  • 19.29Deleting Tuples
  • 19.30Slicing of Tuple
  • 19.31Tuple Membership Test
  • 19.32Built-in Functions with Tuple
20Chapter-20 Dictionary
  • 20.01How to Create a Dictionary?
  • 20.02Python Hashing?
  • 20.03Python Dictionary Methods
  • 20.04Copying Dictionary
  • 20.05Updating Dictionary
  • 20.06Deleting Keys from the Dictionary
  • 20.07Dictionary items() Method
  • 20.08Sorting the Dictionary
  • 20.09Python Dictionary Built-in Functions
  • 20.10Dictionary len() Method
  • 20.11Variable Types
  • 20.12Python List cmp() Method
  • 20.13Dictionary Str(dict)
  • 20.14How to Create a Set?
  • 20.15Iteration Over Sets
  • 20.16Python Set Methods
  • 20.17Python Set Operations Union of Sets
  • 20.18Built-in Functions with Set
  • 20.19Python Frozenset
  • 20.20What is a String?
  • 20.21String Operations and Indices
  • 20.22Basic String Operations
  • 20.23String Functions, Methods
  • 20.24Delete a String
  • 20.25String Multiplication and Concatenation
  • 20.26Python Keywords, Identifiers, and Literals
  • 20.27String Formatting Operator
  • 20.28Structuring with Indentation in Python
  • 20.29Built-in String Methods
21Chapter-21 Python Operators
  • 21.01Arithmetic, Relational, and Comparison Operators
  • 21.02Python Assignment Operators Short-hand Assignment Operators
  • 21.03Logical Operators or Bitwise Operators Membership Operators
  • 21.04Identity Operators Operator Precedence
  • 21.05Evaluating Expressions
  • 21.06How to Use "if condition" in Conditional Structures
  • 21.07if Statement (One-Way Decisions)
  • 21.08if .. else Statement (Two-way Decisions)
  • 21.09How to Use "else condition"
  • 21.10if .. elif .. else Statement (Multi-way)
  • 21.11When "else condition" Does Not Work
  • 21.12How to Use "elif" Condition
  • 21.13How to Execute Conditional Statement with Minimal Code
  • 21.14Nested IF Statement
22Chapter-22 Operators
  • 22.01What is an Operator?
  • 22.02Different Types of Operators
  • 22.03Arithmetic Operators
  • 22.04Assignment Operator
  • 22.05Unary Minus Operator
  • 22.06Relational Operators
  • 22.07Logical Operators
  • 22.08Membership Operators
  • 22.09Identity Operators
  • 22.10How to Use "While Loop" and "For Loop"
  • 22.11How to Use For Loop for Set of Other Things Besides Numbers
  • 22.12Break Statements, Continue Statement, Enumerate Function for For Loop
  • 22.13Practical Example: How to Use For Loop to Repeat the Same Statement Over and Again
  • 22.14Break, Continue Statements
23Chapter-23 Python Functions What Is A Function?
  • 23.01How to define and call a function in Python
  • 23.02Types of Functions
  • 23.03Significance of Indentation (Space) in Python
  • 23.04How Function Return Value?
  • 23.05Types of Arguments in Functions
  • 23.06Default Arguments and Non-Default Arguments
  • 23.07Keyword Argument and Non-keyword Arguments
  • 23.08Arbitrary Arguments
  • 23.09Rules to define a function in Python
  • 23.10Various Forms of Function Arguments
  • 23.11Scope and Lifetime of Variables
  • 23.12Nested Functions
  • 23.13Call By Value, Call by Reference
  • 23.14Anonymous Functions/Lambda Functions
  • 23.15Passing functions to function
  • 23.16map(), filter(), reduce() functions
  • 23.17What is a Docstring?
  • 23.18Lambda function
  • 23.19Filter function
  • 23.20Reduce function
  • 23.21Map function
24Chapter-24 List Comprehension
  • 24.01Introduction
  • 24.02Generator Comprehension
  • 24.03Set Comprehension
  • 24.04Importing module
  • 24.05Math module
  • 24.06Random module
  • 24.07Packages
  • 24.08Composition
  • 24.09Printing on screen
  • 24.10Reading data from keyboard
  • 24.11Opening and closing file
  • 24.12Reading and writing files
  • 24.13Functions
25Chapter-25 Exception Handling
  • 25.01Exception
  • 25.02Exception Handling
  • 25.03Except clause
  • 25.04Try...finally clause
  • 25.05User Defined Exceptions
  • 25.06Match function
  • 25.07Search function
  • 25.08Matching VS Searching
  • 25.09Modifiers
  • 25.10Patterns
26Chapter-26 Packages
  • 26.01Predefined Packages
  • 26.02User Defined
  • 26.03Text Files
  • 26.04Binary Files
  • 26.05Zip and Unzip Files
  • 26.06Pickling
  • 26.07Unpickling
  • 26.08Reading Program from Another Program in Command Prompt
  • 26.09Python File Handling
  • 26.10Python Read Files
  • 26.11Python Write/Create Files
  • 26.12Python Delete Files
27Chapter-27 Object Oriented Programming
  • 27.01What are Constructors
  • 27.02Is Constructor Mandatory in Python?
  • 27.03Can a Constructor be Called Explicitly?
  • 27.04How Many Parameters Can a Constructor Have?
  • 27.05Parameterized and Non-Parameterized Constructors in Python
  • 27.06Difference Between a Method and Constructor in Python
  • 27.07Difference Between a Method and a Function
  • 27.08Types of Class Variables
  • 27.09Instance Variables
  • 27.10Where Instance Variables Can Be Declared?
  • 27.11Accessing Instance Variables
  • 27.12Static Variables
  • 27.13Declaring Static Variables
  • 27.14Accessing a Static Variable
  • 27.15Local Variables
  • 27.16Types of Methods in a Class
  • 27.17Instance Methods
  • 27.18Setter and Getter Methods
  • 27.19Class Methods
  • 27.20Static Methods
  • 27.21Nested Classes
  • 27.22Garbage Collection
  • 27.23Super() Function in Python
  • 27.24Which Scenarios Super() Function is Required?
  • 27.25Different Approaches for Calling Method of a Specific Super Class
  • 27.26Different Cases for Super() Function
  • 27.27Polymorphism
  • 27.28Types of Polymorphism
  • 27.29Overloading
  • 27.30Operator Overloading
  • 27.31Method Overloading
  • 27.32How We Can Handle Overloaded Method Requirements
  • 27.33Constructor Overloading
  • 27.34Overriding
  • 27.35Method Overriding
  • 27.36Constructor Overriding
  • 27.37Abstract Classes
  • 27.38What is an Abstract Class in Python?
  • 27.39Types of Methods in Python Based on the Implementation
  • 27.40How to Declare an Abstract Method in Python
  • 27.41Abstract Classes in Python
28Chapter-28 Exception Handling & Files
  • 28.01Types of Error
  • 28.02Syntax and Runtime Errors
  • 28.03What is an Exception?
  • 28.04Exception Handling in Python
  • 28.05Why do We Need Finally Block?
  • 28.06Finally Block in Python
  • 28.07Why Not ‘try except’ Block for Clean-up Activities?
  • 28.08Different Control Flow Cases of try except finally in Python
  • 28.09Nested try-except-finally Blocks in Python
  • 28.10Different Cases and Scenarios
  • 28.11Else Block in Python
  • 28.12Possible Combinations with try-except-else-finally
  • 28.13What is a File?
  • 28.14Types of Files
  • 28.15File Modes
  • 28.16Opening and Closing a File
  • 28.17Properties of File Object
  • 28.18Writing Data to a File
  • 28.19Reading Data from a File
  • 28.20With Keyword
29Chapter-29 Multithreading
  • 29.01What is Multitasking?
  • 29.02Process-based and Thread-based Multitasking
  • 29.03Applications of Multithreading
  • 29.04How to Implement Multithreading?
  • 29.05Different Ways to Create a Thread
  • 29.06Creating a Thread Using Thread Class
  • 29.07Creating a Thread by Inheriting Thread Class
  • 29.08active_count()
  • 29.09enumerate()
  • 29.10isAlive()
  • 29.11join()
  • 29.12join(seconds)
  • 29.13Synchronization
  • 29.14How to Implement Synchronization?
  • 29.15Synchronization by Using Lock Concept
  • 29.16Synchronization by Using RLock Concept
  • 29.17Difference Between Lock and RLock
  • 29.18Synchronization by Using Semaphore
  • 29.19Bounded Semaphore
  • 29.20What is Inter Thread Communication?
  • 29.21Inter Thread Communication by Using Event Objects
  • 29.22Inter Thread Communication by Using Condition Object
  • 29.23Inter Thread Communication by Using Queue in Python
  • 29.24Types of Queues
  • 29.25FIFO Queue
  • 29.26LIFO Queue
  • 29.27Priority Queue
30Chapter-30 Base Communication And Networking
  • 30.01What is XML?
  • 30.02Difference between XML and HTML, XML, JSON, Gson
  • 30.03How to Parse XML and Create XML Node
  • 30.04Python vs JAVA
  • 30.05XML and HTML
  • 30.06What is Database?
  • 30.07Types of Databases
  • 30.08What is DBMS? RDBMS?
  • 30.09What is Big Data?
  • 30.10Types of Data
  • 30.11Oracle MySQL
  • 30.12SQL Server
  • 30.13Postgres SQL
  • 30.14Executing the Queries
  • 30.15Bind Variables
  • 30.16Installing Oracle Python Modules
  • 30.17What is Testing?
  • 30.18Types of Testing and Methods
  • 30.19What is Unit Testing?
  • 30.20What is PyUnit?
  • 30.21Test Scenarios, Test Cases, Test Suites
  • 30.22Socket
  • 30.23Socket Module
  • 30.24Methods
  • 30.25Client and Server
  • 30.26Internet Modules
31Chapter-31 Packages
  • 31.01Introduction to Numpy
  • 31.02Creating Arrays and Indexing Arrays
  • 31.03Array Transposition
  • 31.04Universal Array Function
  • 31.05Array Processing
  • 31.06Array Input and Output
  • 31.07What are Pandas?
  • 31.08Where it is Used?
  • 31.09Series in Pandas
  • 31.10Index Objects
  • 31.11Reindex
  • 31.12Drop Entry
  • 31.13Selecting Entries
  • 31.14Data Alignment
  • 31.15Rank and Sort
  • 31.16Summary Statistics
  • 31.17Index Hierarchy
  • 31.18Data Visualization
  • 31.19Python for Data Visualization
  • 31.20Welcome to the Data Visualization Section
  • 31.21Introduction to Matplotlib
32Chapter-32 Data Science
  • 32.01What is Data Science?
  • 32.02Data Science Life Cycle
  • 32.03What is Data Analysis, Data Mining?
  • 32.04Analytics vs Data Science
  • 32.05Impact of the Internet
  • 32.06What is IoT?
  • 32.07History of IoT
  • 32.08What is Network, Protocol, Smart?
  • 32.09How IoT Works?
  • 32.10The Future of IoT

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