Microsoft Data Science Online Training

This Microsoft Data Science Online Training Course includes the necessary skillset required for Data Scientists with Microsoft Platform. This Microsoft Data Science course inlcudes SQL Server & T-SQL, Excel, Power BI, with Python, R Language and Hadoop File System (HDFS), Azure Machine Learning, Spark and Scala. All our Data Science Trainings are completely practical and real-time. Resume Preperation, Job Guidance and Real-time project are a part of this course. Register Today

DATA SCIENCE TRAINING - Plans [Register Today]

  Plan A Plan B Plan C Plan D Plan E
Courses Included T-SQL + Power BI T-SQL + Power BI + Python Plan B + Hadoop Plan C + R Plan D + Azure ML
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Course Duration 5 Weeks 9 Weeks 16 Weeks 20 Weeks 25 Weeks
Total Course Fee INR 15000/-
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Data Science Training Course Contents:

Module I: SQL Server & Design, Queries, Joins

Module II: T-SQL Queries, Tuning & Programming

CHAPTER 1: SQL SERVER INSTALLATION

  • What is Data? What is Database? File Store Limitations?
  • Why Microsoft SQL Server? Advantages (Technical/Usage)
  • SQL Server - Career Options, Certifications, Projects
  • What is SQL? What is T-SQL? Differences. Why T-SQL?
  • MSBI Components and Real-time Activities
  • Versions and Editions of SQL Server - Overview
  • Session Wise Plan, Material and Real-time Project Details
  • LAB PLAN - 24x7 LIVE Server (Online Lab)
  • SQL Server Software - Server Installation Steps
  • SQL Server Tools Installation and Verification
  • SSMS in Windows OS, SOS Tool in Mac & LINUX OS
  • H/W & S/W Requirements. Server Configuration Options
  • Instance Types : Default and Named Instances. Instance IDs
  • SQL Server Tools - SQL Server Management Studio (SSMS)

CHAPTER 7: STORED PROCEDURES - LEVEL 1

  • Stored Procedures - Purpose, Syntax, Properties and Types
  • Compilation, Precompilation and Query Optimization (QO)
  • Variables - Usage and Data Types in Stored Procedures
  • Parameters - Usage and Data Types in Stored Procedures
  • Stored Procedure Executions - Syntax, Alternate Options
  • Stored Procedures for Data Validations & Missing Identity
  • Stored Procedures for Dynamic SQL Queries. Views & SPs
  • Stored Procedures for Data Reporting. Advantanges, Tuning
  • Important System Procedures For Metadata Access. Usage
  • Important Extended Procedures For Application Operations
  • IF.. ELSE, IF .. ELSE IF, IIF Conditions. PRINT statements
  • Error Handling Techniques in T-SQL: TRY, CATCH, THROW
  • Dynamic Parameters and Variables. Examples with Views
  • Default Parameter Values, Data Types and NULL Values
  • Batch Executions with Stored Procedures. Variants

CHAPTER 2: SQL BASICS - DDL, DML, SELECT

  • Basic SQL for Beginners. Introducing Databases, Tables
  • What is SQL? Why T-SQL? Basic SQL Queries in SSMS
  • DDL and DML Statements - Creating & Using Databases
  • Table Creation (Basic Level) - Columns and Data Types
  • Issues with Digital Data into Characters. Missing Values
  • INSERT / Store Data into SQL Server Tables - Options
  • Single Row and Multiple Row Inserts with NULL Values
  • SELECT Queries and Basic Operators : IN, BETWEEN
  • IS, UNION, UNION ALL, Other Basic SQL Operators
  • UPDATE Statements with / without Conditions. SET
  • DELETE Statements with Conditions. Logging Options
  • TRUNCATE Statement - DELETE Comparisons, Logging
  • SYSTEM DATABASES - Purpose and Importance. Resource
  • CLIENT - SERVER Architecture (TDS) & Client Statistics

CHAPTER 8: STORED PROCEDURES - LEVEL 2

  • Stored Procedures for Sub Queries, Dynamic Sub Queries
  • Stored Procedures for Recursive and Nested Queries
  • OUTPUT Parameters in Stored Procedures. Usage Options
  • Cursors - Benefits, Syntax. Using SProcs with Cursors
  • FORWARD_ONLY and SCROLL Cursors Types. Limitations
  • STATIC and DYNAMIC Cursors Types. ABSOLUTE Fetch
  • LOCAL and GLOBAL Cursor Types & Scope, Reusability
  • KEYSET DRIVEN Cursor Types & Performance Options
  • Embedding Cursors in Procedures and User Functions
  • SPs with Cursors @ Dynamic Data Loads, Data Formatting
  • Memory Limitations with Cursors with SP Recompilations
  • Using Extended Stored Procedures with User Procedures
  • Stored Procedures for Dynamic Values, Calendar Data
  • Unicode Data and Dynamic SQL Queries. sysname Data

CHAPTER 3: SQL SERVER DATABASE DESIGN

  • SQL Database Architecture - Logical and Physical View
  • Database Properties - Files - Types - Storage Options
  • Data Files : Purpose and Sizing. Detailed Architecture
  • Filegroups : Purpose and Grouping Options. Properties
  • Log files : Sizing, Placement & Detailed Architecture
  • Pages, Extents (Uniform, Mixed). Data Allocation Process
  • Write Ahead Log (WAL) and Log Sequence Number (LSN)
  • Virtual Log File (VLF) and MINI LSN. Operation Audits
  • Database Creation using GUI - Adding Files, Filegroups
  • Database File and Filegroup Options. GUI Limitations
  • Database Creation using T-SQL Scripts. SYNTAX Rules
  • Database with Filegrowth, Autogrowth, MAXSIZE Options
  • mdf, ndf, ldf and Custom Extensions. Dynamic Extensions
  • Planning and Designing Very Large Databases (VLDB)
  • CHAR versus VARCHAR Differences - Type, Size Allocations

CHAPTER 9: VIEWS - FUNCTIONS & QUERIES

  • Views on Tables - Stored SELECT Statements, Data Access
  • SCHEMABINDING and ENCRYPTION Options - Advantages
  • Cascaded Views and WITH CHECK OPTION, Advantages
  • Orphan Views - Scenarios and Realworld Solutions
  • Common System Views For Metadata Access, Object IDs
  • Functions: Types, Purpose and Usage. Return Values
  • Scalar Value and Inline Table Value Functions
  • Multi-Line Table Value Returning Functions - Usage
  • Table Variables and Parameters in SQL Server. Usage
  • ROLLUP and CUBE - Sub Totals, Grand Totals, Aggregates
  • ROLLUP of Table Data. Column Aggregations. ORDER BY
  • CUBE on Table Data - Purpose & Usage. Permutations
  • Queries with GROUPING() Option in SELECT, Using HAVING
  • HAVING versus WHERE Conditions - Usage Differences

CHAPTER 4: TABLE DESIGN & QUERIES

  • Table Design - Creation. Columns - Data Types, Length
  • Routing Tables to Database File Groups, Advantages
  • Schemas - Purpose, Creation and Usage with Tables
  • Table Design using T-SQL Scripts - Syntax, Examples
  • Data Types, Length, NULLs and Naming Conventions
  • UNION, UNION ALL Operators. Differences, Row Order
  • CREATE, ALTER, DROP -- INSERT, UPDATE, DELETE
  • SELECT Queries with Schema on Tables, Column Aliases
  • T-SQL Data Types and NULL Values. Computed Columns
  • Comparing DELETE and TRUNCATE - TLog Files
  • T-SQL Operators: IN, BETWEEN, IS, AND, OR, EXISTS
  • Default Schema and Default Filegroup for Table Design
  • Basic Sub Queries - SELECT, MIN/ MAX. Column Aliases
  • Temporary Tables : Purpose and Types. Local and Global
  • Synonyms : Purpose. Alternate Object Reference, Queries

CHAPTER 10: TRANSACTIONS & TRIGGERS

  • Need for Transactions, Transaction Scenarios
  • ACID Properties and Transaction Types. Atomic Property
  • EXPLICIT, IMPLICIT Transactions - Query Blocking
  • IMPLICIT Transactions - Usage, Database Settings
  • AUTOCOMMIT Transactions - Advantages, Examples
  • OPEN Transactions and Audits. OPENTRAN commands
  • Nested Transactions and COMMIT / ROLLBACK Rules
  • SavePoint Options with Explicit Transactions, Rollbacks
  • LOCK HINTS : READPAST, NOLOCK, HOLDLOCK - Usage
  • Triggers - Purpose and Types. Scope Of Usage
  • DML Triggers - Events, Types and Practical Usage
  • FOR / AFTER Triggers and INSTEAD OF Triggers
  • INSERTED & DELETED Memory Tables with DML Triggers
  • Triggers for DML Operation Audits and Data Sampling
  • Database Triggers and Server Level Triggers

CHAPTER 5: CONSTRAINTS and KEYS

  • Constraints and Keys - Ensuring Table Data Integrity
  • Normal Forms - Types, Relational Database (RDB) Design
  • OLTP Database Model & BCNF - Relations with PK / UQ
  • NULL, NOT NULL and Default Nullability for Columns
  • UNIQUE KEY Constraints: Importance, Uniqueness, Nulls
  • PRIMARY KEY Constraint: Properties, Priority, Limitations
  • FOREIGN KEY Constraint: References, Relations & Usage
  • CHECK Constraints: Properties, Conditions and Usage
  • DEFAULT Constraints: Properties, Usage and Limitations
  • Relations with Tables across Multiple Schemas, Usage
  • Identity Property with / without PRIMARY KEY, Usage
  • Naming Conventions For Constraints, Columns and Tables
  • Normal Forms - Types, Purpose and Usage. With Examples
  • BCNF: Boycee-Codd Normal Form and Practical Usage

CHAPTER 11: INDEXES and QUERY TUNING OPTIONS

  • Indexes: Architecture (Page Level), Purpose and Types
  • Clustered Indexes - Architecture, Fragmentation Issues
  • Non Clustered Indexes - Architecture, Column References
  • Execution Plans and Query Optimization (QO) Techniques
  • Execution Plan - Table Scan, Index Scan and Index Seek
  • INCLUDED INDEXES - Index Seeks, Query Tuning
  • COLUMNSTORE Indexes - Advantages, Usage Examples
  • FILTERED Indexes & Online Indexes
  • Materialized Views / Indexed Views - Tuning Options
  • Query Optimizer (QO) Options for Index Pages, Data Pages
  • Limitations of Indexes - Impact on DML and SELECT
  • Primary Key Index, Composite Indexes and Precautions
  • RID and Index Key Concepts. Index Page - Data Page Arch"
  • Real-world Considerations For Indexes (Tables, Views)

CHAPTER 6: JOINS, SUB QUERIES & NESTED QUERIES

  • JOINS - Purpose and Types, Use Case Scenarios
  • JOIN - Types, Queries and Importance of Reports
  • CROSS JOIN in detail. Examples and Conditions @ WHERE
  • INNER JOIN in detail. Examples with WHERE and ON
  • Comparing INNER JOIN with CROSS JOIN for Conditions
  • OUTER JOINS in detail. LEFT, RIGHT and FULL Joins
  • SELF JOINS with INNER / OUTER Joins. Usage Scenarios
  • Working with Self Joins on non key columns, advantages
  • JOINS with more than 2 tables. Syntax, Precedence Order
  • Query Optimization Considerations with Schema References
  • Deciding the best Join Type, Order and Query Options
  • JOIN Queries with Options and UNION, UNION ALL Operators
  • Basic Sub Queries and Joins. Alternate Syntax & Queries
  • Using ON and WHERE for Join Conditions. Working with NULLs
  • Using SubQueries for Self Joins and Outer Joins
  • Working with Nested Queries and Nested Sub Queries
  • Using Sub Queries and Nested Sub Queries with Outer Joins
  • End User Access to SQL Databases - Reporting Tools, Options
  • A Real-world Case Study understanding Joins & Queries

CHAPTER 12: SQL SERVER ARCHITECTURE

  • Client - Server Architecture of SQL Server
  • SQL Server Tools - Connection Options, TDS Packets
  • Protocols : TCP / IP, Named Pipes, Shared Memory
  • SQL Native Client (SNAC) and OLE DB Drivers / Providers
  • ISO - OSI Model of Data Connections, Encrypted Data
  • Query Processing and Query Optimizer (QO) Components
  • SQL Server Architecture For Database Engine, LCM Options
  • Architecture - Query Processor and Storage Engine
  • Architecture - Query Parser, Optimizer, Mini LSN, MDAC
  • Architecture - SQL Engine, SQL Manager and Query Buffers
  • Architecture - Write Ahead Log (WAL), Lazy Writer Threads
  • Architecture - SQLOS Threads and Task Schedulers, CLR
  • SQL Database Architecture - RAID Levels (S/W, H/W)
  • Log Sequence Numbers (LSN) and Time Mapping. Audits
  • Log File Architecture - Virtual Log Files and Usage
  • Log File Architecture - Mini LSN & Degree Of Parallelism
  • DB Catalogs, CLR Integration and MDAC Components
  • LSN Timestamps and MINILSN. Background Threads @ SQL

CHAPTER 1 : INTRODUCTION TO POWER BI (Free Demo)

  • Introduction to Power BI - Need, Imprtance
  • Power BI - Advantages and Scalable Options
  • History - Power View, Power Query, Power Pivot
  • Power BI Data Source Library and DW Files
  • Cloud Colloboration and Usage Scope
  • Business Analyst Tools, MS Cloud Tools
  • Power BI Installation and Cloud Account
  • Power BI Cloud and Power BI Service
  • Power BI Architecture and Data Access
  • OnPremise Data Acces and Microsoft On Drive
  • Power BI Desktop - Instalation, Usage
  • Sample Reports and Visualization Controls
  • Power BI Cloud Account Configuration
  • Understanding Desktop & Mobile Editions
  • Report Rendering Options and End User Access
  • Power View and Power Map. Power BI Licenses
  • Course Plan - Power BI Online Training

CHAPTER 8 : DAX EXPRESSIONS - Level 1

  • Purpose of Data Analysis Expresssions (DAX)
  • Scope of Usage with DAX. Usabilty Options
  • DAX Context : Row Context and Filter Context
  • DAX Entities : Calculated Columns and Measures
  • DAX Data Types : Numeric, Boolean, Variant, Currency
  • Datetime Data Tye with DAX. Comparison with Excel
  • DAX Operators & Symbols. Usage. Operator Priority
  • Parenthesis, Comparison, Arthmetic, Text, Logic
  • DAX Functions and Types: Table Valued Functions
  • Filter, Aggregation and Time Intelligence Functions
  • Information Functions, Logical, Parent-Child Functions
  • Statistical and Text Functions. Formulas and Queries
  • Syntax Requirements with DAX. Differences with Excel
  • Naming Conventions and DAX Format Representation
  • Working with Special Characters in Table Names
  • Attribute / Column Scope with DAX - Examples
  • Measure / Column Scope with DAX - Examples

CHAPTER 2 : CREATING POWER BI REPORTS, AUTO FILTERS

  • Report Design with Legacy & .DAT Files
  • Report Design with Databse Tables
  • Understanding Power BI Report Designer
  • Report Canvas, Report Pages: Creation, Renames
  • Report Visuals, Fields and UI Options
  • Experimenting Visual Interactions, Advantages
  • Reports with Multiple Pages and Advantages
  • Pages with Multiple Visualizations. Data Access
  • PUBLISH Options and Report Verification in Cloud
  • "GET DATA" Options and Report Fields, Filters
  • Report View Options: Full, Fit Page, Width Scale
  • Report Design using Databases & Queries
  • Query Settings and Data Preloads
  • Navigation Options and Report Refresh
  • Stacked bar chart, Stacked column chart
  • Clustered bar chart, Clustered column chart
  • Adding Report Titles. Report Format Options
  • Focus Mode, Explore and Export Settings

CHAPTER 9 : DAX EXPRESSIONS - Level 2

  • YTD, QTD, MTD Calculations with DAX
  • DAX Calculations and Measures
  • Using TOPN, RANKX, RANK.EQ
  • Computations using STDEV & VAR
  • SAMPLE Function, COUNTALL, ISERROR
  • ISTEXT, DATEFORMAT, TIMEFORMAT
  • Time Intelligence Functions with DAX
  • Data Analysis Expressions and Functions
  • DATESYTD, DATESQTD, DATESMTD
  • ENDOFYEAR, ENDOFQUARTER,ENDOFMONTH
  • FIRSTDATE, LASTDATE, DATESBETWEEN
  • CLOSINGBALANCEYEAR,CLOSINGBALANCEQTR
  • SAMEPERIOD and PREVIOUSMONTH,QUARTER
  • KPIs with DAX. Vertipaq Queries in DAX
  • IF..ELSEIF.. Conditions with DAX
  • Slicing and Dicing Options with Columns, Measures
  • DAX for Query Extraction, Data Mashup Operations
  • Calcualted COlumns and Calculated Measures with DAX

CHAPTER 3 : REPORT VISUALIZATIONS and PROPERTIES

  • Power BI Design: Canvas, Visualizations and Fileds
  • Import Data Options with Power BI Model, Advantages
  • Direct Query Options and Real-time (LIVE) Data Access
  • Data Fields and Filters with Visualizations
  • Visualization Filters, Page Filters, Report Filters
  • Conditional Filters and Clearing. Testing Sets
  • Creating Customised Tables with Power BI Editor
  • General Properties, Sizing, Dimensions, and Positions
  • Alternate Text and Tiles. Header (Column, Row) Properties
  • Grid Properties (Vertical, Horizontal) and Styles
  • Table Styles & Alternate Row Colors - Static, Dynamic
  • Sparse, Flashy Rows, Condensed Table Reports. Focus Mode
  • Totals Computations, Background. Boders Properties
  • Column Headers, Column Formatting, Value Properties
  • Conditional Formatting Options - Color Scale
  • Page Level Filters and Report Level Filters
  • Visual-Level Filters and Format Options
  • Report Fields, Formats and Analytics
  • Page-Level Filters and Column Formatting, Filters
  • Background Properties, Borders and Lock Aspect

CHAPTER 10 : POWERBI DEPLOYMENT & CLOUD

  • PowerBI Report Validation and Publish
  • Understanding PowerBI Cloud Architecture
  • PowerBI Cloud Account and Workspace
  • Reports and DataSet Items Validation
  • Dashboards and Pins - Real-time Usage
  • Dynamic Data Sources and Encryptions
  • Personal and Organizational Content Packs
  • Gateways, Subscriptions, Mobile Reports
  • Data Refresh with Power BI Architecture
  • PBIX and PBIT Files with Power BI - Usage
  • Visual Data Imprts and Visual Schemas
  • Cloud and On-Premise Data Sources
  • How PowerBI Supports Data Model?
  • Relation between Dashbaords to Reports
  • Relation between Datasets to Reports
  • Relation between Datasets to Dashbaords
  • Page to Report - Mapping Options
  • Publish Options and Data Import Options
  • Need for PINS @ Visuals and PINS @ Reports
  • Need for Data Streams and Cloud Intergration

CHAPTER 4 : CHART AND MAP REPORT PROPERTIES

  • CHART Report Types and Properties
  • STACKED BAR CHART, STACKED COLUMN CHART
  • CLUSTERED BAR CHART, CLUSTERED COLUMN CHART
  • 100% STACKED BAR CHART, 100% STACKED COLUMN CHART
  • LINE CHARTS, AREA CHARTS, STACKED AREA CHARTS
  • LINE AND STACKED ROW CHARTS
  • LINE AND STACKED COLUMN CHARTS
  • WATERFALL CHART, SCATTER CHART, PIE CHART
  • Field Properties: Axis, Legend, Value, Tooltip
  • Field Properties: Color Saturation, Filters Types
  • Formats: Legend, Axis, Data Labels, Plot Area
  • Data Labels: Visibility, Color and Display Units
  • Data Labels: Precision, Position, Text Options
  • Analytics: Constant Line, Position, Labels
  • Working with Waterfall Charts and Default Values
  • Modifying Legends and Visual Filters - Options
  • Map Reports: Working with Map Reports
  • Hierarchies: Grouping Multiple Report Fields
  • Hierarchy Levels and Usages in Visualizations
  • Preordered Attribute Collection - Advantages
  • Using Field Hierarchies with Chart Reports
  • Advanced Query Mode @ Connection Settings - Options
  • Direct Import and In-memory Loads, Advantages

CHAPTER 11 : POWER BI CLOUD OPERATIONS

  • Report Publish Options and Verifications
  • Working with Power BI Cloud Interface & Options
  • Navigation Paths with "My Workspace" Screens
  • FILE, VIEW, EDIT REPORTS, ACCESS, DRILLDOWN
  • Saving Reports into pdf, pptx, etc. Report Embed
  • Report Rendering and EDIT, SAVE, Print Options
  • Report PIN and individual Visual PIN Options
  • Create and Use Dashboards. Menu Options
  • Goto Dashboard and Goto LIVE Page Options
  • Operations on Pinned Reports and Visuals
  • TITLE, MEDIA, USAGE METRICS & FAVOURITES
  • SUBSCRIPTION Options and Reports with Mobile View
  • Options with Report Page : Print and Subscribe
  • Report Actions: USAGE METRICS, ANALYSE IN EXCEL
  • Report Actions: RELATED ITEMS, RENAME, DELETE
  • Dashboard Actions: METRICS, RELATED ITEMS
  • Dashboard Actions: SETTINGS FOR Q & A, DELETE
  • PIN Actions: METRICS, SHARE, RELATED ITEMS
  • PIN Actions: SETTINGS FOR Q & A, DELETE
  • EDIT DASHBOARD (CLOUD), On-The-Fly Reports
  • Dataset Actions: CREATE REPORT, REFRESH
  • SCHEDULED REFRESH & RELATED ITEMS
  • Dashboard Integration with Apps in Power BI

CHAPTER 5 : HIERARCHIES and DRILLDOWN REPORTS

  • Hierarchies and Drilldown Options
  • Hierarchy Levels and Drill Modes - Usage
  • Drill-thru Options with Tree Map and Pie Chart
  • Higher Levels and Next Level Navigation Options
  • Aggregates with Bottom/Up Navigations. Rules
  • Multi Field Aggregations and Hierarchies in Power BI
  • DRILLDOWN, SHOWNEXTLEVEL, EXPANDTONEXTLEVEL
  • SEE DATA and SEE RECORDS Options. Differences
  • Toggle Options with Tabular Data. Filters
  • Drilldown Buttons and Mouse Hover Options @ Visuals
  • Dependant Aggregations, Independant Aggregations
  • Automated Records Selection with Tabular Data
  • Report Parameters : Creation and Data Type
  • Available Values and Default values. Member Values
  • Parameters for Column Data and Table / Query Filters
  • Parameters Creation - Query Mode, UI Option
  • Linking Parameters to Query Columns - Options
  • Edit Query Options and Parameter Manage Entries
  • Connection Parameters and Dynamic Data Sources
  • Synonyms - Creation and Usage Options

CHAPTER 12 : IMPROVING POWER BI REPORTS

  • Publish PowerBI Report Templates
  • Import and Export Options with Power BI
  • Dataset Navigations and Report Navigations
  • Quick Navigation Options with "My Workspace"
  • Dashboards, Workbooks, Reports, Datasets
  • Working with MY WORK SPACE group
  • Installing the Power BI Personal Gateway
  • Automatic Refresh - Possible Issues
  • Adding images to the dashboards
  • Reading & Editing Power BI Views
  • Power BI Templates (pbit)- Creation, Usage
  • Managing report in Power BI Services
  • PowerBI Gateway - Download and Installation
  • Personal and Enterprise Gateway Features
  • PowerBI Settings : Dataset - Gateway Integration
  • Configuring Dataset for Manual Refresh of Data
  • Configuring Automatic Refresh and Schdules
  • Workbooks and Alerts with Power BI
  • Dataset Actions and Refresh Settings with Gateway
  • Using natural Language Q&A to data - Cortana

CHAPTER 6 : POWER QUERY & M LANGUAGE - Part 1

  • Understanding Power Query Editor - Options
  • Power BI Interface and Query / Dataset Edits
  • Working with Empty Tables and Load / Edits
  • Empty Table Names and Header Row Promotions
  • Undo Headers Options. Blank Columns Detection
  • Data Imports and Query Marking in Query Editor
  • JSON Files & Binary Formats with Power Query
  • JavaScript Object Notation - Usage with M Lang.
  • Applied Steps and Usage Options. Revert Options
  • creating Query Groups and Query References. Usage
  • Query Rename, Load Enable and Data Refresh Options
  • Combine Queries - Merge Join and Anti-Join Options
  • Combine Queries - Union and Union All as New Dataset
  • M Language : NestedJoin and JoinKind Functions
  • REPLACE, REMOVE ROWS, REMOVE COL, BLANK - M Lang
  • Column Splits and FilledUp / FilledDown Options
  • Query Hide and Change Type Options. Code Generation

CHAPTER 13 : INSIGHTS AND SUBSCRIPTIONS

  • Data Navigation Paths and Data Splits
  • Getting data from existing systems
  • Data Refresh and LIVE Connections
  • pbit and pbix : differences. Usage Options
  • Quick Insights For Power BI Reports
  • Quick Insights For PowerBI Dashboads
  • Generating Insights with Cloud Datasets
  • Generarting Reports with Cloud Datasets
  • Using relational databases on-premises
  • Using relational databases in the cloud
  • Consuming a service content pack
  • Creating a custom data set from a service
  • Creating a content pack for your organization
  • Consuming an organizational content pack
  • Updating an organizational content pack
  • Adding Tiles : Images, Videos, DataStreams
  • Creating New Reports from Cortana, Advantages

CHAPTER 7 : POWER QUERY & M LANGUAGE - Part 2

  • Invoke Function and Freezing Columns
  • Creating Reference Tables and Queries
  • Detection and Removal of Query Datasets
  • Custom Columns with Power Query
  • Power Query Expressions and Usage
  • Blank Queries and Enumuration Value Generation
  • M Language Sematics and Syntax. Tranform Types
  • IF..ELSE Conditions, TransformColumn() Types
  • RemoveColumns(), SplitColumns(),ReplaceValue()
  • Table.Distinct Options and GROUP BY Options
  • Table.Group(), Table.Sort() with Type Conversions
  • PIVOT Operation and Table.Pivot(). List Functions
  • Using Parameters with M Language (Power Query Editor)
  • Advanced Query Editor and Parameter Scripts
  • List Generation and Table Conversion Options
  • Aggregations using PowerQuery & Usage in Reports
  • Report Generation using Web Pages & HTML Tables
  • Reports from Page collection with Power Query
  • Aggregate and Evaluate Options with M Language
  • Creating high-density reports, ArcGIS Maps, ESRI Files
  • Generating QR Codes for Reports
  • Table Bars and Drill Thru Filters

CHAPTER 14 : POWERBI INTEGRATION ELEMENTS

  • SSRS Integration with Power BI
  • SSRS Report Portal URL to Power BI Cloud
  • Power BI KPI Reports Vs SSRS KPI Reports
  • Convering and Working with Mobile Reports
  • Report Buidler Reports to Powert BI
  • Generating QR Codes and Report Security
  • Reporting JSON Files, Bulk Data Loads
  • Creating high-density Reports in Power BI
  • OLAP DataSources in Power BI
  • Using MDX Queries with PowerBI Queries
  • MDX SELECT and Perspective Access
  • KPIs and MDX Expressions with Power BI
  • MDX Queries and Filters with Power BI
  • Linked Servers and T-SQL SPROCs with MDX
  • YTD, PARALLELPERIOD,SCOPE, ALLMEMBERS
  • WHERE, EXCEPT, RANGE, NONEMPTY
  • CURRENT & EMPTY, AND / OR, LEFT / RIGHT
  • Implementing Row Level Security (RLS)
  • Security Roles and Role Members. Tests
  • Using R for Power BI, Streaming DataSets
  • Azure Connections with PowerBI Desktop
  • PowerBI Reports using SQL Azure DBs

Module I - Core Python

Module II - Advanced Python

CHAPTER 1 : Introduction to Script

  • What is Script
  • What is a program?
  • Types of Scripts
  • Difference between Script
  • Programming Languages
  • Features of Scripting
  • Limitation of Scripting
  • Types of programming Language Paradigms
  • Basic understanding of Python
  • Python and Other programming languages

CHAPTER 2 : Introduction to Python

  • What is Python?
  • Why Python?
  • Who Uses Python?
  • Characteristics of Python
  • History of Python
  • What is PSF?
  • Python Versions
  • How to Download Python
  • How to Install Python
  • Install Python with Diff IDEs
  • Features of Python
  • Limitations of Python
  • Python Applications
  • Creating Your First Python Program
  • Printing to the Screen
  • Reading Keyboard Input
  • Using Command Prompt and GUI or IDE
  • Python Distributions
  • Python first program
  • Compilers VS interpreters

CHAPTER 3 : Different Modes in PYTHON

  • Execute the Script
  • Interactive Mode
  • Script Mode
  • Python File Extensions
  • SETTING PATH IN Windows
  • Clear screen inside python
  • Learn Python Main Function
  • Python Comments
  • Quit the Python Shell
  • Shell as a Simple Calculator
  • Order of operations
  • Multiline Statements
  • Quotations in Python
  • Python Path Testing
  • Joining two lines
  • Python Implementation Alternatives
  • Python Sub Packages
  • Uses of Python in Data Science
  • USES OF PYTHON IN IOT
  • Working with Python in
  • Unix/Linux/Windows/Mac/Android..!!

CHAPTER 4 : PYTHON NEW IDEs

  • PyCharm IDE
  • How to Work on PyCharm
  • PyCharm Components
  • Debugging process in PyCharm
  • PYTHON Install Anaconda
  • What is Anaconda?
  • Coding Environments
  • Spyder Components
  • General Spyder Features
  • Spyder Shortcut Keys
  • Jupyter Notebook
  • What is Conda?
  • Conda List?
  • Jupyter and Kernels
  • What is PIP?

CHAPTER 5 : Variables in Python

  • What is Variable?
  • Variables in Python
  • Constants in Python
  • Variable and Value
  • Variable names
  • Mnemonic Variable Names
  • Values and Types
  • What Does “Type” Mean?
  • Multiple Assignment
  • Python different numerical types
  • Standard Data Types
  • Operators and Operands
  • Order of Operations
  • Swap variables
  • Python Mathematics
  • Type Conversion
  • Mutable Versus Immutable Objects

CHAPTER 6 : String Handling

  • What is string?
  • String operations
  • String indices
  • Basic String Operations
  • String Functions, Methods
  • Delete a string
  • String Multiplication and concatenation
  • Python Keywords
  • Python Identifiers
  • Python Literals
  • String Formatting Operator
  • Structuring with indentation in Python
  • Built-in String Methods
  • Define Data Structure?
  • Data Structures in PYTHON

CHAPTER 7: Python Operators and Operands

  • Arithmetic Operators
  • Relational Operators
  • Comparison Operators
  • Python Assignment Operators
  • Short hand Assignment Operators
  • Logical Operators or Bitwise Operators
  • Membership Operators
  • Identity Operators
  • Operator precedence
  • Evaluating Expressions

CHAPTER 8 : Python Conditional

  • Statements
  • How to use “if condition” in conditional
  • Structures
  • if statement (One-Way Decisions)
  • if .. else statement (Two-way Decisions)
  • How to use “else condition”
  • if .. elif .. else statement (Multi-way)
  • When “else condition” does not work
  • How to use “elif” condition
  • How to execute conditional statement with
  • minimal code
  • Nested IF Statement

CHAPTER 9 : Python LOOPS

  • How to use “While Loop”
  • How to use “For Loop”
  • How to use For Loop for set of other things besides numbers
  • Break statements in For Loop
  • Continue statement in For Loop
  • Enumerate function for For Loop
  • Practical Example
  • How to use for loop to repeat the same
  • statement over and again
  • Break, continue statements

CHAPTER 10 : Learning Python Strings

  • Accessing Values in Strings
  • Various String Operators
  • Some more examples
  • Python String replace() Method
  • Changing upper and lower case strings
  • Using “join” function for the string
  • Reversing String
  • Split Strings

CHAPTER 11 : Sequence or Collections in PYTHON

  • Strings
  • Unicode Strings
  • Lists
  • Tuples
  • Buffers
  • Xrange

CHAPTER 12 : Python Lists

  •  Lists are mutable
  • Getting to Lists
  • List indices
  • Traversing a list
  • List operations
  • List slices
  • List methods
  • Map, filter and reduce
  • Deleting elements
  • Lists and strings

CHAPTER 13 : Python TUPLE

  • Advantages of Tuple over List
  • Packing and Unpacking
  • Comparing tuples
  • Creating nested tuple
  • Using tuples as keys in dictionaries
  • Deleting Tuples
  • Slicing of Tuple
  • Tuple Membership Test
  • Built-in functions with Tuple
  • Dotted Charts

CHAPTER 14 : Python Sets

  • How to create a set?
  • Iteration Over Sets
  • Python Set Methods
  • Python Set Operations
  • Union of sets
  • Built-in Functions with Set
  • Python Frozenset

CHAPTER 15 : Python Dictionary

  • How to create a dictionary?
  • PYTHON HASHING?
  • Python Dictionary Methods
  • Copying dictionary
  • Updating Dictionary
  • Delete Keys from the dictionary
  • Dictionary items() Method
  • Sorting the Dictionary
  • Python Dictionary in-built Functions
  • Dictionary len() Method
  • Variable Types
  • Python List cmp() Method
  • Dictionary Str(dict)

CHAPTER 16 : Python Functions

  • What is a function?
  • How to define and call a function in Python
  • Types of Functions
  • Significance of Indentation (Space) in Python
  • How Function Return Value?
  • Types of Arguments in Functions
  • Default Arguments
  • Non-Default Arguments
  • Keyword Arguments
  • Non-keyword Arguments
  • Arbitrary Arguments
  • Rules to define a function in Python
  • Various Forms of Function Arguments
  • Scope and Lifetime of variables
  • Nested Functions
  • Call By Value, Call by Reference
  • Anonymous Functions/Lambda functions

CHAPTER 17 : Python Modules

  • What is a Module?
  • Types of Modules
  • The import Statement
  • The from…import Statement
  • ..import * Statement
  • Underscores in Python
  • The dir( ) Function
  • Creating User defined Modules
  • Command line Arguments
  • Python Module Search Path

CHAPTER 18 : Packages in Python

  • What is a Package?
  • Introduction to Packages?
  • py file
  • Importing module from a package
  • Creating a Package
  • Creating Sub Package
  • Importing from Sub-Packages
  • Popular Python Packages

CHAPTER 19 : Python Date and Time

  • How to Use Date & DateTime Class
  • How to Format Time Output
  • How to use Timedelta Objects
  • Calendar in Python
  • datetime classes in Python
  • How to Format Time Output?
  • The Time Module
  • Python Calendar Module
  • Python Text Calendar
  • Python HTML Calendar Class
  • Unix Date and Time Commands

CHAPTER 20 : File Handling

  • What is a data, Information File?
  • File Objects
  • File Different Modes
  • file Object Attributes
  • How to create a Text File
  • How to Append Data to a File
  • How to Read a File
  • Closing a file
  • Read, read line ,read lines, write, write lines…!!
  • Renaming and Deleting Files
  • Directories in Python
  • Working with CSV files
  • Working with CSV Module
  • Handling IO Exceptions

CHAPTER 21 : Python OS Module

  • Shell Script Commands
  • Various OS operations in Python
  • Python File System Shell Methods
  • Different Python Modules
  • os
  • math
  • cmd
  • csv
  • random
  • Numpy ( numerical python )
  • Pandas
  • Sys
  • Matplotlib
  • Datetime
  • Time

CHAPTER 22 : Python Exception Handling

  • Python Errors
  • Common RunTime Errors in PYTHON
  • Abnormal termination
  • Chain of importance Of Exception
  • Exception Handling
  • Try … Except
  • Try .. Except .. else
  • Try … finally
  • Argument of an Exception
  • Python Custom Exceptions
  • Ignore Errors
  • Assertions
  • UsingAssertionsEffectively

CHAPTER 23 : More Advanced PYTHON

  • Python Iterators
  • Python Generators
  • Python Closures
  • Python Decorators
  • Python @property

CHAPTER 24 : Python Class and Objects

  • Introduction to OOPs Programming
  • Object Oriented Programming System
  • OOPS Principles
  • Define Classes
  • Creating Objects
  • Class variables and Instance Variables
  • Constructors
  • Basic concept of Object and Classes
  • Access Modifiers
  • How to define Python classes
  • Python Namespace
  • Self-variable in python
  • Garbage Collection
  • What is Inheritance? Types of Inheritance?
  • How Inheritance works?
  • Python Multiple Inheritance
  • Overloading and Over Riding
  • Polymorphism
  • Abstraction
  • Encapsulation
  • Built-In Class Attributes

CHAPTER 25 : Python Regular Expressions

  • What is Regular Expression?
  • Regular Expression Syntax
  • Understanding Regular Expressions
  • Regular Expression Patterns
  • Literal characters
  • Repetition Cases
  • Example of w+ and ^ Expression
  • Example of \s expression in re.split function
  • Using regular expression methods
  • Using re.match()
  • Finding Pattern in Text (re.search())
  • Using re.findall for text
  • Python Flags
  • Methods of Regular Expressions

CHAPTER 26 : Python XML Parser

  • What is XML?
  • Difference between XML and HTML
  • Difference between XML and JSON and Gson
  • How to Parse XML
  • How to Create XML Node
  • Python vs JAVA
  • XML and HTML

CHAPTER 27 : Python-Data Base Communication

  • What is Database? Types of Databases?
  • What is DBMS?
  • What is RDBMS?
  • What is Big Data? Types of data?
  • Oracle
  • MySQL
  • SQL server
  • DB2
  • Postgre SQL
  • Executing the Queries
  • Bind Variables
  • Installing of Oracle Python Modules
  • Executing DML Operations..!!

CHAPTER 28 : Multi-Threading

  • What is Multi-Threading
  • Threading Module
  • Defining a Thread
  • Thread Synchronization

CHAPTER 29 : Multi-Threading

  • What is Multi-Threading
  • Threading Module
  • Defining a Thread
  • Thread Synchronization

CHAPTER 30 : Web Scrapping

  • The components of a web page
  • BeautifulSoup
  • Urllib2
  • HTML,CSS,JS,jQuery
  • Dataframes
  • PIP
  • Installing External Modules Using PIP

CHAPTER 31 : Unit Testing with PyUnit

  • What is Testing?
  • Types of Testings and Methods?
  • What is Unit Testing?
  • What is PyUnit?
  • Test scenarios, Test Cases, Test suites

CHAPTER 32 : Introduction to Python Web

  • Frameworks
  • Django – Design
  • Advantages of Django
  • MVC and MVT
  • Installing Django
  • Designing Web Pages
  • HTML5, CSS3, AngularJS
  • PYTHON Flask
  • PYTHON Bottle
  • PYTHON Pyramid
  • PYTHON Falcon

CHAPTER 33 : GUI Programming-Tkinter

  • Introduction
  • Components and Events
  • Adding Controls
  • Entry Widget, Text Widget, Radio Button,
  • Check Button
  • List Boxes, Menus, ComboBox

CHAPTER 34 : Data Analytics

  • Introduction to data Big Data?
  • Introduction to NumPY and SciPY
  • Introduction to Pandas and MatPlotLib

CHAPTER 35 : Introduction to Machine

  • Learning with PYTHON  
  • What is Machine learning?
  • Machine Learning Methods
  • Predictive Models
  • Descriptive Models
  • What are the steps used in Machine Learning?
  • What is Deep Learning?

CHAPTER 36 : Data Science

  • What is Data Science?
  • Data Science Life Cycle?
  • What is Data Analysis
  • What is Data Mining
  • Analytics vs Data Science

CHAPTER 37 : Internet of Things

  • IMPACT OF THE INTERNET
  • What is IOT
  • History of IoT
  • What is Network?
  • What is Protocol?
  • What is smart?
  • How IoT Works?
  • The Future of IoT

Module I

Module II

CHAPTER 1 : INTRODUCTION

  • What is Cloud Computing
  • What is Grid Computing
  • What is Virtualization
  • How above three are inter-related to each other
  • What is Big Data
  • Introduction to Analytics and the need for big data analytics
  • Hadoop Solutions - Big Picture
  • Hadoop distributions
  • Comparing Hadoop Vs. Traditional systems
  • Volunteer Computing
  • Data Retrieval - Radom Access Vs. Sequential Access
  • NoSQL Databases

CHAPTER 2 : THE MOTIVATION FOR HADOOP

  • Problems with traditional large-scale systems
  • Data Storage literature survey
  • Data Processing literature Survey
  • Network Constraints
  • Requirements for a new approach

CHAPTER 3 : HADOOP BASIC CONCEPTS

  • What is Hadoop?
  • The Hadoop Distributed File System
  • How MapReduce Works
  • Anatomy of a Hadoop Cluster

CHAPTER 4 : HADOOP DEMONS

  • Master Daemons
  • Name node
  • Job Tracker
  • Secondary name node
  • Slave Daemons
  • Job tracker
  • Task tracker

CHAPTER 5 : HDFS (HADOOP DISTRIBUTION FILE SYSTEM)

  • Blocks and Splits
  • Input Splits
  • HDFS Splits
  • Data Replication
  • Hadoop Rack Aware
  • Data high availability
  • Data Integrity
  • Cluster architecture and block placement
  • Accessing HDFS
  • JAVA Approach
  • CLI Approach

CHAPTER 6 : PROGRAMMING PRACTICES & PERFORMING TUNING

  • Developing MapReduce Programs in
  • Local Mode
  • Running without HDFS and Mapreduce
  • Pseudo-distributed Mode
  • Running all daemons in a single node
  • Fully distributed mode
  • Running daemons on dedicated nodes

CHAPTER 7: HADOOP ADMINISTATIVE TASKS - Setup Hadoop cluster of Apache, Cloudera and HortonWorks

  • Install and configure Apache Hadoop
  • Make a fully distributed Hadoop cluster on a single laptop/desktop (Psuedo Mode)
  • Install and configure Cloudera Hadoop distribution in fully distributed mode
  • Install and configure HortonWorks Hadoop distribution in fully distributed mode
  • Monitoring the cluster
  • Getting used to management console of Cloudera and Horton Works
  • Name Node in Safe mode
  • Meta Data Backup
  • Integrating Kerberos security in Hadoop
  • Ganglia and Nagios Cluster monitoring
  • Benchmarking the Cluster
  • Commissioning/Decommissioning Nodes.

CHAPTER 8 : HAOOP DEVELOPER TASKS-Writing a Map Reduce Program

  • Examining a Sample Map Reduce Program
  • With Several Examples
  • Basic API Concepts
  • The Driver Code
  • The Mapper
  • The Reducer
  • Hadoop's Streaming API

CHAPTER 9 : Performing several Hadoop Jobs

  • The configure and close Methods
  • Sequence Files
  • Record Reader
  • Record Writer
  • Role of Reporter
  • Output Collector
  • Processing video files and audio files
  • Processing image files
  • Processing XML files
  • Processing Zip files
  • Counters
  • Directly Accessing HDFS
  • Tool Runner
  • Using The Distributed Cache.

CHAPTER 10 : Common Map Reduce Algorithms

  • Sorting and Searching
  • Indexing
  • Classification/Machine Learning
  • Term Frequency - Inverse Document Frequency
  • Word Co-Occurrence
  • Hands-On Exercise: Creating an Inverted Index
  • Identify Mapper
  • Identify Reducer
  • Exploring well known problems using
  • Map Reduce applications.

CHAPTER 11 : Debugging Map Reduce Programs

  • Testing with MR Unit
  • Logging
  • Other Debugging Strategies.

CHAPTER 12 : Advanced Map Reduce Programming

  • A Recap of the Map Reduce Flow
  • Custom Writables and Writable Comparables
  • The Secondary Sort
  • Creating Input Formats and Output Formats
  • Pipelining Jobs With Oozie
  • Map-Side Joins
  • Reduce-Side Joins.

CHAPTER 13 : Monitoring and debugging on a Production Cluster

  • Counters
  • Skipping Bad Records
  • Rerunning failed tasks with Isolation Runner

CHAPTER 14 : Tuning for Performance

  • Reducing network traffic with combiner
  • Reducing the amount of input data
  • Using Compression
  • Running with speculative execution
  • Refactoring code and rewriting algorithms Parameters affecting Performance
  • Other Performance Aspects

CHAPTER 15 : Hadoop Ecosystem- Hive

  • Hive concepts
  • Hive architecture
  • Install and configure hive on cluster
  • Create database, access it console
  • Buckets,Partitions
  • Joins in Hive
  • Inner joins
  • Outer joins
  • Hive UDF
  • Hive UDAF
  • Hive UDTF
  • Develop and run sample applications in Java to access hive
  • Load Data into Hive and process it using Hive

CHAPTER 16 : PIG

  • Pig basics
  • Install and configure PIG on a cluster
  • PIG Vs MapReduce and SQL
  • PIG Vs Hive
  • Write sample Pig Latin scripts
  • Modes of running PIG
  • Running in Grunt shell
  • Programming in Eclipse
  • Running as Java program
  • PIG UDFs
  • PIG Macros
  • Load data into Pig and process it using Pig

CHAPTER 17 : SQOOP

  • Install and configure Sqoop on cluster
  • Connecting to RDBMS
  • Installing Mysql
  • Import data from Oracle/Mysql to hive
  • Export data to Oracle/Mysql
  • Internal mechanism of import/export
  • Import millions of records into HDFS from RDBMS using Sqoop

Chapter 18 : HBASE

  • HBase concepts
  • HBase architecture
  • Region server architecture
  • File storage architecture
  • HBase basics
  • Cloumn access
  • Scans
  • HBase Use Cases
  • Install and configure HBase on cluster
  • Create database, Develop and run sample applications
  • Access data stored in HBase using clients like Java
  • Map Resuce client to access the HBase data
  • HBase and Hive Integration
  • HBase admin tasks
  • Defining Schema and basic operation

CHAPTER 19 : CASSANDRA

  • Cassandra core concepts
  • Install and configure Cassandra on cluster
  • Create database, tables and access it console
  • Developing applications to access data in Cassandra through Java
  • Install and Configure OpsCenter to access Cassandra data using browser

CHAPTER 20 : OOZIE

  • Oozie architecture
  • XML file specifications
  • Install and configure Oozie on cluster
  • Specifying Work flow
  • Action nodes
  • Control nodes
  • Oozie job coordinator
  • Accessing Oozie jobs command line and using web console
  • Create a sample workflows in oozie and run them on cluster

CHAPTER 21 : Zookeeper, Flume, Chukwa, Avro, Scribe,Thrift, HCatalog

  • Flume and Chukwa Concepts
  • Use cases of Thrift ,Avro and scribe
  • Install and Configure flume on cluster
  • Create a sample application to capture logs from Apache using flume

CHAPTER 22 : ANALYTICS BASIC

  • Analytics and big data analytics
  • Commonly used analytics algorithms
  • Analytics tools like R and Weka
  • R language basics
  • Mahout

CHAPTER 23 : CDH4 ENHANCEMENTS

  • Name Node High – Availability
  • Name Node federation
  • Fencing
  • YARn

Scala Introduction &Environment Setup:

  • Scala is object-oriented, Scala is functional,Scala runs on the JVM
  • Installing Scala

Scala Basic Syntax

  • First Scala Program
  • Interactive Mode Programming
  • Script Mode Programming

Scala Data TYPES:

  • Literals
  • Strings
  • Escape Sequences

Scala Variables:

  • Declaration
  • Data Types
  • Type Inference
  • Multiple assignments
  • Variable Types

Scala Operators:

  • Arithmetic
  • Relational
  • Logical
  • Operator Precedence in Scala
  • Scala Conditions

  • Scala Loops

  • Scala Strings:

Scala Regular Expressions:

  • Forming regular expressions
  • Matching Literals and Constants
  • Matching Tuples and Lists
  • Matching with Types and Guards
  • Pattern Variables and Constants in case Expressions
  • Regular-expression Examples
  • Pattern matching with Extractors

Scala Functions:

  • Declarations
  • Definitions
  • Calling 
  • Function Literals
  • Anonymous
  • Currying

Scala Arrays

  • Declaring
  • Processing
  • Multi-Dimensional
  • Create Array with Range
  • Scala Arrays Methods

Scala Collections

  • Basic Operations on List,
  • Concatenating Lists
  • Creating Uniform Lists
  • Tabulating a Function
  • Scala List Methods
  • Concatenating Sets, Find max, min elements in Set
  • Find common values in Sets
  • Scala Set Methods
  • Basic Operations on Map
  • Check for a Key in Map

Scala Classes & Objects:

  • Oops Basics
  • Defining Fields,Methods,Constructors

Introduction to Apache Spark:

  • What is Spark?
  • Spark Ecosystem, &modes of Spark
  • overview of Spark on a cluster
  • Spark Standalone cluster
  • Spark Web UI &
  • Spark Common Operations

Spark Core

  • performing basic Operations on files in Spark Shell and Overview of SBT
  • building a Spark project with SBT
  • running Spark project with SBT
  • Playing with RDDs:
  • RDDs, transformations in RDD, actions in RDD
  • loading data in RDD
  • saving data through RDD
  • Key-Value Pair RDD
  • MapReduce and Pair RDD Operations
  • Spark and Hadoop Integration-Yarn

Spark SQL

  • SparkSQL and Performance Tuning in Spark:
  • Analyze Hive and Spark SQL architecture, SQLContext in Spark SQL
  • working with Data Frames
  • implementing an example for Spark SQL
  • integrating hive and Spark SQL
  • support for JSON and Parquet File Formats
  • implement data visualization in Spark
  • loading of data
  • Hive queries through Spark
  • performance tuning tips in Spark

Spark Streaming

  • A Simple Example
  • Architecture and Abstraction
  • Transformations
  • Stateless Transformations
  • Stateful Transformations
  • Output Operations
  • Input Sources
  • Additional Sources
  • Multiple Sources and Cluster Sizing
  • Worker Fault Tolerance
  • Receiver Fault Tolerance
  • Processing Guarantees
  • Streaming UI
  • Batch and Window Sizes
  • Level of Parallelism

Spark GraphX

  • Edges
  • Vertices
  • Types of Graphs
  • Usages
  • Simple Program

SPARK Mlib

  • Vectors
  • Labledpoints
  • Lables
  • Features
  • RDD with Vectors
  • Matrices, Stats, Maths
  • Algorithms with Spark Mlib

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

Python

  • Python Basics
  • Python Lists
  • Functions and Packages
  • Numpy
  • Control flow and Pandas

Probability

  • Counting Combinations, Generating Combinations
  • Generating Random Numbers
  • Generating Reproducible Random Numbers
  • Generating a Random Sample
  • Generating Random Sequences
  • Randomly Permuting a Vector
  • Probabilities for Discrete Distributions
  • Probabilities for Continuous Distributions, Converting
  • Probabilities to Quantiles, Plotting a Density Function

Graphics

  • Edges
  • Vertices
  • Graphs
  • Programs
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