Master the fundamental of IOT. Join now and learn how to develop IOT products.

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  • A few years back, IoT was a new concept. But with each passing year, IoT technology has taken over the market and has made our lives easier and productive. From smart homes to smart cities, from smart agriculture to smart healthcare, every modern thing we use today is based on the fundamentals of IoT. Not to mention leading industries such as IBM, Amazon, Microsoft, etc. have already switched on to IoT applications after realizing the benefits it offers to organizations.
  • Although IoT has become an indispensable part of almost any industry, still there are small-scale industries that are unsure about the huge value IoT offers to businesses and marketing. Here, IoT online training helps them to understand the technology and further assists them in all possible ways so that they can exhibit the technology in the workplace as well.
  • It would not be wrong to say that there is no field left where IoT cannot be used, making it an even more popular and most in-demand application. There are more opportunities for businesses that are adopting IoT in their workspace. More importantly, since the IoT field is expanding, the demand for trained and certified IoT professionals is also increasing. Hence this is the apt time to enroll for an IoT placement course with one of the premier IoT online training in India.

Internet of Things (IoT) Online Training

About-Us-Cources

  • The IoT certification online course is designed to help you understand the most basic and advanced concepts in IoT.
    • IoT online training course curriculum is backed up by top industry experts to help you master the craft and establish yourself as a certified IoT professional and earn more from the beginning itself.

      Learn all the IoT basics, IoT architecture, IoT decision framework, and a lot more.

      With IoT online certification course, learn to configure raspberry Pi, know about programming sensors, actuators, and much more.

      The IoT online training intends to teach you IoT networking protocols and how to design more powerful solutions.

      With one of the leading IoT online training institute, acquire substantial knowledge about cloud or Azure IoT hub, and also learn how to demonstrate hub APIs in MS azure.

      Also, learn to design end-to-end solutions using various IoT technologies and tools with the guidance of IoT online training in India.

      Master data analytics techniques onto the collected data and use prediction algorithms to get meaningful insights from it.

  • We at the Croma campus know that salary prospects and placement are important variables to look out for while planning to get trained in any course in general. As for the stats that you might be interested in, we’ve got you covered:
    • A crude figure of about 50 billion devices will be driven on IoT tech by 2022.

      IoT devices will have amassed a global market of 2 trillion by the end of 2022.

      According to the survey platform Glassdoor, an IoT professional earns an average salary of $150K. Moreover, the figure is bound to go up as you gain experience in the field as an IoT professional.

  • As a major IoT online training company in India, we have crafted an online course to help you master the practical aspects of IoT deployment in the IT sector. Thus enrolling yourself at the IoT online placement course is a great investment considering the salary prospective.

  • The exponential demand for IoT solutions is inevitable in the near future. Hence, it’s certainly a great investment to get yourself trained with the IoT online training program.
    • With more than 30 billion devices actively driven by IoT, the supply vs demand ratio is skewed towards the need for more IoT professionals in the field.

      With the leading online IoT training course, add advanced IoT skills to your arsenal and augment your job prospects in the IT domain.

      Get assured placement assistance. Moreover, build a stunning resume and advance your career in the IT industry.

  • IoT ecosystem is rapidly expanding with more and more businesses and organizations are depending on it for making better business decisions. We are using a wide array of products like desktops, laptops, smartphones, wrist bands, etc. to drive meaningful insights from the data collected by IoT devices. Sensors, vehicles, and many other devices are also growing at a rapid pace.
  • Some of the advantages of IoT include:
    • IoT helps in saving millions of dollars by reducing energy consumption and its enhanced energy efficiency.

      It also helps in achieving customer satisfaction through logistic and operation management.

      Since IoT is making lives easier and smarter, there will be a huge demand for IoT professionals making the future of IoT is bright.

  • According to a survey, more than 50 billion devices are interconnected in 2020 using IoT services. Researchers have predicted that in the upcoming years due to the increasing usage of IoT, there will be an increase in demand for IoT skilled professionals. Hence it will be wise on your part to register for the IoT online training and secure your future job opportunities.

  • IoT online training covers certain job roles and responsibilities as a part of the program that you might need to implement in the workplace. They are
    • You should acquire in-depth knowledge about basic and advanced concepts of IoT.

      You must be well aware of IoT basics, IoT architecture, IoT decision framework, and more.

      You need to be well-versed in configuring raspberry Pi and know about programming sensors, actuators, and a lot more.

      You need to have some functional idea about cloud or Azure IoT hub, and how to demonstrate hub APIs in MS azure.

      You must have in-depth idea of IoT networking protocols and thereby learn how to design more powerful solutions.

      You should be able to perform data analytics techniques on to the data collected and procure meaningful insights from it by using prediction algorithms.

  • With one of the most renowned IoT online training in India, learn to manage all the job roles and responsibilities with ease and further help the company serves better.

  • Since IoT has helped enterprises to work in a better way, there are many companies that are on the lookout for IoT skilled professionals. Some of the top-notch industries hiring IoT experts are Honeywell, Intel, Amdocs, Microsoft, and IBM, etc. According to Cisco, there are more than 50 million devices that are working on IoT and shortly the number will rise to billions.
  • The use of IoT technology has found its niche in almost every field, ranging from the healthcare sector, aviation, logistics, IT to everywhere, and thus has opened opportunities for job seekers who want to get into the IoT domain. It has been predicted to be the next best thing in the IT industry. Even more, reasons to enroll yourself in the IoT online training program!

  • The IoT online training in India program has been meticulously designed to help you master all the key concepts with ease. It covers a wide range of topics, from IoT applications to physical layer protocol and other standard IoT frameworks included. The primary focus being to be able to deploy powerful IoT solutions on-demand in real-world scenarios.

Why should you learn the Internet of Things?

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Plenary for Internet of Things (IoT) Certification Training

TrackWeek DaysWeekendsFast Track
Course Duration 40-45 Days 7 Weekends 8 Days
Hours 1 Hrs. Per Day 2 Hrs. Per Day 6+ Hrs. Per Day
Training ModeClassroom/OnlineClassroom/OnlineClassroom/Online
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CURRICULUM & PROJECTS

Internet of Things (IoT) Certification Training

  • In this program you will learn:
    • Internet of Things (IoT) Introduction

      IoT Architecture

      Understanding IoT Ecosystems

      Raspberry Pi

      IoT Gateways

      Cloud Platforms for IoT

      IoT Implementations [Applications]

      Future & Security Concerns

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  • Internet of Things (IoT) Introduction
    • Background and Development

      Three waves of Internet

      Why IoT

      Market Analysis & Investment In IoT

      Industrial & Consumer IoT

      M2M communication and automation history

      Relation with embedded systems

      General introduction to Arduino , Raspberry Pi and SmartWifi boards

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  • IoT Architecture
    • How IoT Works

      High level Data Flow in IoT

      Technical Architecture

      Description of all layers of IoT Architecture

      Technologies for IoT

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  • Understanding IoT Ecosystems
    • What is IoT application

      What are basic elements / building blocks of IoT app

      How are these blocks connected together

      The systematic method to design IoT application

      Architecting our hands-on project

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  • Raspberry Pi
    • Learning fundamentals of Raspberry Pi

      Different types of pi boards.

      Installation of OS in Raspberry Pi

      Programming Raspberry Pi Using Python

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  • Python Introduction
    • Numbers, List, Tuple & dictionaries

      If else statements

      Loop & Control Statements

      File Handling

      Understanding Functions

      Raspberry Pi Programming

      Interfacing Sensors with Raspberry Pi

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  • IoT Gateways
    • Introduction to IoT Gateway

      ESP8266 Module as Wi-Fi Gateway

      Learning AT Commands of ESP8266

      Programming on ESP8266 Wi-Fi Module

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  • Cloud Platforms for IoT
    • Introduction to Cloud

      It’s different models of Cloud

      Overview different IoT cloud platforms

      How to get Access to Cloud Platforms

      Sending Data to IoT Cloud Platform

      Sending Creating Alerts Using Cloud Platform

      Developing IoT Prototype

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  • IoT Implementations [Applications]
    • Cities

      Home

      Agriculture

      Healthcare Industry

      Transportation

      Environment

      Infrastructure

      Security

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  • Future & Security Concerns
    • Future Scope

      Challenges

      Security

  • Data Analysis and Visualization using Pandas.
  • Statistics
    • Categorical Data

      Numerical Data

      Mean

      Median

      Mode

      Outliers

      Range

      Interquartile range

      Correlation

      Standard Deviation

      Variance

      Box plot

  • Pandas
    • Read data from Excel File using Pandas More Plotting, Date Time Indexing and writing to les

      How to get record specic records Using Pandas Adding & Resetting Columns, Mapping with function

      Using the Excel File class to read multiple sheets More Mapping, Filling Nonvalue’s

      Exploring the Data Plotting, Correlations, and Histograms

      Getting statistical information about the data Analysis Concepts, Handle the None Values

      Reading les with no header and skipping records Cumulative Sums and Value Counts, Ranking etc

      Reading a subset of columns Data Maintenance, Adding/Removing Cols and Rows

      Applying formulas on the columns Basic Grouping, Concepts of Aggre gate Function

      Complete Understanding of Pivot Table Data Slicing using iLoc and Loc property (Setting Indices)

      Under sting the Properties of Pivot Table in Pandas Advanced Reading CSVs/HTML, Binning, Categorical Data

      Exporting the results to Excel Joins:

      Python | Pandas Data Frame Inner Join

      Under sting the properties of Data Frame Left Join (Left Outer Join)

      Indexing and Selecting Data with Pandas Right Join (Right Outer Join)

      Pandas | Merging, Joining and Concatenating Full Join (Full Outer Join)

      Pandas | Find Missing Data and Fill and Drop NA Appending Data Frame and Data

      Pandas | How to Group Data How to apply Lambda / Function on Data Frame

      Other Very Useful concepts of Pandas in Python Data Time Property in Pandas (More and More)

  • Data Analysis and Visualization using NumPy and MatPlotLib
  • NumPy
    • Introduction to NumPy: Numerical Python

      Importing NumPy and Its Properties

      NumPy Arrays

      Creating an Array from a CSV

      Operations an Array from a CSV

      Operations with NumPy Arrays

      Two-Dimensional Array

      Selecting Elements from 1-D Array

      Selecting Elements from 2-D Array

      Logical Operation with Arrays

      Indexing NumPy elements using conditionals

      NumPy’s Mean and Axis

      NumPy’s Mode, Median and Sum Function

      NumPy’s Sort Function and More

  • MatPlotLib
    • Bar Chart using Python MatPlotLib

      Column Chart using Python MatPlotLib

      Pie Chart using Python MatPlotLib

      Area Chart using Python MatPlotLib

      Scatter Plot Chart using Python MatPlotLib

      Play with Charts Properties Using MatPlotLib

      Export the Chart as Image

      Understanding plt. subplots () notation

      Legend Alignment of Chart using MatPlotLib

      Create Charts as Image

      Other Useful Properties of Charts.

      Complete Understanding of Histograms

      Plotting Different Charts, Labels, and Labels Alignment etc.

  • Introduction to Data Visualization with Seaborn
  • Introduction to Seaborn
    • Introduction to Seaborn

      Making a scatter plot with lists

      Making a count plot with a list

      Using Pandas with seaborn

      Tidy vs Untidy data

      Making a count plot with a Dataframe

      Adding a third variable with hue

      Hue and scattera plots

      Hue and count plots

  • Visualizing Two Quantitative Variables
    • Introduction to relational plots and subplots

      Creating subplots with col and row

      Customizing scatters plots

      Changing the size of scatter plot points

      Changing the style of scatter plot points

      Introduction to line plots

      Interpreting line plots

      Visualizing standard deviation with line plots

      Plotting subgroups in line plots

  • Visualizing a Categorical and a Quantitative Variable
    • Current plots and bar plots

      Count plots

      Bar plot with percentages

      Customizing bar plots

      Box plots

      Create and interpret a box plot

      Omitting outliers

      Adjusting the whisk

      Point plots

      Customizing points plots

      Point plot with subgroups

  • Customizing Seaborn Plots
    • Changing plot style and colour

      Changing style and palette

      Changing the scale

      Using a custom palette

      Adding titles and labels: Part 1

      Face Grids vs. Axes Subplots

      Adding a title to a face Grid object

      Adding title and labels: Part 2

      Adding a title and axis labels

      Rotating x-tics labels

      Putting it all together

      Box plot with subgroups

      Bar plot with subgroups and subplots

      Well done! What’s next

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  • SQL Server Fundamentals
    • SQL Server 2019 Installation

      Service Accounts & Use, Authentication Modes & Usage, Instance Congurations

      SQL Server Features & Purpose

      Using Management Studio (SSMS)

      Conguration Tools & SQLCMD

      Conventions & Collation

  • SQL Server 2019 Database Design
    • SQL Database Architecture

      Database Creation using GUI

      Database Creation using T-SQL scripts

      DB Design using Files and File Groups

      File locations and Size parameters

      Database Structure modications

  • SQL Tables in MS SQL Server
    • SQL Server Database Tables

      Table creation using T-SQL Scripts

      Naming Conventions for Columns

      Single Row and Multi-Row Inserts

      Table Aliases

      Column Aliases & Usage

      Table creation using Schemas

      Basic INSERT

      UPDATE

      DELETE

      SELECT queries and Schemas

      Use of WHERE, IN and BETWEEN

      Variants of SELECT statement

      ORDER BY

      GROUPING

      HAVING

      ROWCOUNT and CUBE Functions

  • Data Validation and Constraints
    • Table creation using Constraints

      NULL and IDENTITY properties

      UNIQUE KEY Constraint and NOT NULL

      PRIMARY KEY Constraint & Usage

      CHECK and DEFAULT Constraints

      Naming Composite Primary Keys

      Disabling Constraints & Other Options

  • Views and Row Data Security
    • Benets of Views in SQL Database

      Views on Tables and Views

      SCHEMA BINDING and ENCRYPTION

      Issues with Views and ALTER TABLE

      Common System Views and Metadata

      Common Dynamic Management views

      Working with JOINS inside views

  • Indexes and Query tuning
    • Need for Indexes & Usage

      Indexing Table & View Columns

      Index SCAN and SEEK

      INCLUDED Indexes & Usage

      Materializing Views (storage level)

      Composite Indexed Columns & Keys

      Indexes and Table Constraints

      Primary Keys & Non-Clustered Indexes

  • Stored Procedures and Benets
    • Why to use Stored Procedures

      Types of Stored Procedures

      Use of Variables and parameters

      SCHEMABINDING and ENCRYPTION

      INPUT and OUTPUT parameters

      System level Stored Procedures

      Dynamic SQL and parameterization

  • System functions and Usage
    • Scalar Valued Functions

      Types of Table Valued Functions

      SCHEMABINDING and ENCRYPTION

      System Functions and usage

      Date Functions

      Time Functions

      String and Operational Functions

      ROW_COUNT

      GROUPING Functions

  • Triggers, cursors, memory limitations
    • Why to use Triggers

      DML Triggers and Performance impact

      INSERTED and DELETED memory tables

      Data Audit operations & Sampling

      Database Triggers and Server Triggers

      Bulk Operations with Triggers

  • Cursors and Memory Limitations
    • Cursor declaration and Life cycle

      STATIC

      DYNAMIC

      SCROLL Cursors

      FORWARD_ONLY and LOCAL Cursors

      KEYSET Cursors with Complex SPs

  • Transactions Management
    • ACID Properties and Scope

      EXPLICIT Transaction types

      IMPLICIT Transactions and options

      AUTOCOMMIT Transaction and usage

      SAVEPOINT and Query Blocking

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  • Introduction to Data Science
    • What is Analytics & Data Science

      Common Terms in Data Science

      What is data

      Classication of data

      Relevance in industry and need of the hour

      Types of problems and business objectives in various industries

      How leading companies are harnessing the power of analytics

      Critical success drivers.

      Overview of Data Science tools & their popularity.

      Data Science Methodology & problem-solving framework.

      List of steps in Data Science projects

      Identify the most appropriate solution design for the given problem statement

      Project plan for Data Science project & key milestones based on effort estimates

      Build Resource plan for Data Science project

      Why Python for data science

  • Accessing/Importing and Exporting Data
    • Importing Data from various sources (Csv, txt, excel, access etc)

      Database Input (Connecting to database)

      Viewing Data objects - sub setting, methods

      Exporting Data to various formats

      Important python modules: Pandas

  • Data Manipulation: Cleansing - Munging Using Python Modules
    • Cleansing Data with Python

      Filling missing values using lambda function and concept of Skewness.

      Data Manipulation steps (Sorting, ltering, duplicates, merging, append ing, sub setting, derived variables, sampling, Data type conversions, renaming, formatting.

      Normalizing data

  • Feature Engineering in Data Science
    • Feature Engineering

      Feature Selection

      Feature scaling using Standard Scaler/Min-Max scaler/Robust Scaler.

      Label encoding/one hot encoding

  • Data Analysis: Visualization Using Python
    • Introduction exploratory data analysis

      Descriptive statistics, Frequency Tables and summarization

      Univariate Analysis (Distribution of data & Graphical Analysis)

      Bivariate Analysis (Cross Tabs, Distributions & Relationships, Graphical Analysis)

      Creating Graphs- Bar/pie/line chart/histogram/ boxplot/ scatter/ densi ty etc.)

      Important Packages for Exploratory Analysis (NumPy Arrays, Matplotlib, seaborn, Pandas etc.)

  • Introduction to Statistics
    • Descriptive Statistics

      Sample vs Population Statistics

      Random variables

      Probability distribution functions

      Expected value

      Normal distribution

      Gaussian distribution

      Z-score

      Spread and Dispersion

      Correlation and Co-variance

  • Introduction to Predictive Modelling
    • Concept of model in analytics and how it is used

      Common terminology used in Analytics & Modelling process

      Popular Modelling algorithms

      Types of Business problems - Mapping of Techniques

      Different Phases of Predictive Modelling

  • EDA (Exploratory Data Analysis)
    • Need for structured exploratory data

      EDA framework for exploring the data and identifying any problems with the data (Data Audit Report)

      Identify missing data

      Identify outliers’ data

      Imbalanced Data Techniques

  • Data Pre-Processing & Data Mining
    • Data Preparation

      Feature Engineering

      Feature Scaling

      Datasets

      Dimensionality Reduction

      Anomaly Detection

      Parameter Estimation

      Data and Knowledge

      Selected Applications in Data Mining

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  • Introduction to Machine Learning
    • Machine Learning

      Machine Learning Algorithms

      Algorithmic models of Learning

      Applications of Machine Learning

      Large Scale Machine Learning

      Computational Learning theory

  • Techniques of Machine Learning
    • Supervised Learning

      Unsupervised Learning

      Semi-supervised and Reinforcement Learning

      Bias and variance Trade-off

      Representation Learning

  • Regression
    • Regression and its Types

      Logistic Regression

      Linear Regression

      Polynomial Regression

  • Classication
    • Meaning and Types of Classication

      Probability and Bayes Theorem

      Support Vector Machines

      Naive Bayes

      Decision Tree Classier

      Random Forest Classier

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  • Introduction to Deep Learning
    • What are the Limitations of Machine Learning

      What is Deep Learning

      Advantage of Deep Learning over Machine learning

      Reasons to go for Deep Learning

      Real-Life use cases of Deep Learning

  • Deep Learning Networks
    • What is Deep Learning Networks

      Why Deep Learning Networks

      How Deep Learning Works

      Feature Extraction

      Working of Deep Network

      Training using Backpropagation

      Variants of Gradient Descent

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  • Introduction to Power BI
    • Overview of BI concepts

      Why we need BI

      Introduction to SSBI

      SSBI Tools

      Why Power BI

      What is Power BI

      Building Blocks of Power BI

      Getting started with Power BI Desktop

      Get Power BI Tools

      Introduction to Tools and Terminology

      Dashboard in Minutes

      Interacting with your Dashboards

      Sharing Dashboards and Reports

  • Power BI Desktop
    • Power BI Desktop

      Extracting data from various sources

      Workspaces in Power BI

  • Power BI Data Transformation
    • Data Transformation

      Query Editor

      Connecting Power BI Desktop to our Data Sources

      Editing Rows

      Understanding Append Queries

      Editing Columns

      Replacing Values

      Formatting Data

      Pivoting and Unpivoting Columns

      Splitting Columns

      Creating a New Group for our Queries

      Introducing the Star Schema

      Duplicating and Referencing Queries

      Creating the Dimension Tables

      Entering Data Manually

      Merging Queries

      Finishing the Dimension Table

      Introducing the another DimensionTable

      Creating an Index Column

      Duplicating Columns and Extracting Information

      Creating Conditional Columns

      Creating the FACT Table

      Performing Basic Mathematical Operations

      Improving Performance and Loading Data into the Data Model

  • Modelling with Power BI
    • Introduction to Modelling

      Modelling Data

      Manage Data Relationship

      Optimize Data Models

      Cardinality and Cross Filtering

      Default Summarization & Sort by

      Creating Calculated Columns

      Creating Measures & Quick Measures

  • Data Analysis Expressions (DAX)
    • What is DAX

      Data Types in DAX

      Calculation Types

      Syntax, Functions, Context Options

      DAX Functions

      • Date and Time
      • Time Intelligence
      • Information
      • Logical
      • Mathematical
      • Statistical
      • Text and Aggregate

      Measures in DAX

      Measures and Calculated Columns

      ROW Context and Filter Context in DAX

      Operators in DAX - Real-time Usage

      Quick Measures in DAX - Auto validations

      In-Memory Processing: DAX Performance

  • Power BI Desktop Visualisations
    • How to use Visual in Power BI

      What Are Custom Visuals

      Creating Visualisations and Colour Formatting

      Setting Sort Order

      Scatter & Bubble Charts & Play Axis

      Tooltips and Slicers, Timeline Slicers & Sync Slicers

      Cross Filtering and Highlighting

      Visual, Page and Report Level Filters

      Drill Down/Up

      Hierarchies and Reference/Constant Lines

      Tables, Matrices & Conditional Formatting

      KPI's, Cards & Gauges

      Map Visualizations

      Custom Visuals

      Managing and Arranging

      Drill through and Custom Report Themes

      Grouping and Binning and Selection Pane, Bookmarks & Buttons

      Data Binding and Power BI Report Server

  • Introduction to Power BI Dashboard and Data Insights
    • Why Dashboard and Dashboard vs Reports

      Creating Dashboards

      Conguring a Dashboard: Dashboard Tiles, Pinning Tiles

      Power BI Q&A

      Quick Insights in Power BI

  • Direct Connectivity
    • Custom Data Gateways

      Exploring live connections to data with Power BI

      Connecting directly to SQL Server

      Connectivity with CSV & Text Files

      Excel with Power BI: Connect Excel to Power BI, Power BI Publisher for Excel

      Content packs

      Update content packs

  • Publishing and Sharing
    • Introduction and Sharing Options Overview

      Publish from Power BI Desktop and Publish to Web

      Share Dashboard with Power BI Service

      Workspaces (Power BI Pro) and Content Packs (Power BI Pro)

      Print or Save as PDF and Row Level Security (Power BI Pro)

      Export Data from a Visualization

      Export to PowerPoint and Sharing Options Summary

  • Refreshing Datasets
    • Understanding Data Refresh

      Personal Gateway (Power BI Pro and 64-bit Windows)

      Replacing a Dataset and Troubleshooting Refreshing

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  • Introduction to Data Preparation using Tableau Prep
    • Data Visualization

      Business Intelligence tools

      Introduction to Tableau

      Tableau Architecture

      Tableau Server Architecture

      VizQL Fundamentals

      Introduction to Tableau Prep

      Tableau Prep Builder User Interface

      Data Preparation techniques using Tableau Prep Builder tool

  • Data Connection with Tableau Desktop
    • Features of Tableau Desktop

      Connect to data from File and Database

      Types of Connections

      Joins and Unions

      Data Blending

      Tableau Desktop User Interface

  • Basic Visual Analytics
    • Visual Analytics

      Basic Charts: Bar Chart, Line Chart, and Pie Chart

      Hierarchies

      Data Granularity

      Highlighting

      Sorting

      Filtering

      Grouping

      Sets

  • Calculations in Tableau
    • Types of Calculations

      Built-in Functions (Number, String, Date, Logical and Aggregate)

      Operators and Syntax Conventions

      Table Calculations

      Level of Detail (LOD) Calculations

      Using R within Tableau for Calculations

  • Advanced Visual Analytics
    • Parameters

      Tool tips

      Trend lines

      Reference lines

      Forecasting

      Clustering

  • Level of Detail (LOD) Expressions in Tableau
    • Count Customer by Order

      Profit per Business Day

      Comparative Sales

      Profit Vs Target

      Finding the second order date

      Cohort Analysis

  • Geographic Visualizations in Tableau
    • Introduction to Geographic Visualizations

      Manually assigning Geographical Locations

      Types of Maps

      Spatial Files

      Custom Geocoding

      Polygon Maps

      Web Map Services

      Background Images

  • Advanced charts in Tableau
    • Box and Whisker’s Plot

      Bullet Chart

      Bar in Bar Chart

      Gantt Chart

      Waterfall Chart

      Pareto Chart

      Control Chart

      Funnel Chart

      Bump Chart

      Step and Jump Lines

      Word Cloud

      Donut Chart

  • Dashboards and Stories
    • Introduction to Dashboards

      The Dashboard Interface

      Dashboard Objects

      Building a Dashboard

      Dashboard Layouts and Formatting

      Interactive Dashboards with actions

      Designing Dashboards for devices

      Story Points

  • Get Industry Ready
    • Tableau Tips and Tricks

      Choosing the right type of Chart

      Format Style

      Data Visualization best practices

  • Exploring Tableau Online
    • Publishing Workbooks to Tableau Online

      Interacting with Content on Tableau Online

      Data Management through Tableau Catalog

      AI-Powered features in Tableau Online (Ask Data and Explain Data)

      Understand Scheduling

      Managing Permissions on Tableau Online

      Data Security with Filters in Tableau Online

  • Placement Guide
    • Tips to clear an Interview

      Common Interview questions and answers

      Tableau Interview Questions and Answers

      Resume Building Guide

      Attempt for the related Global Certification Exam

      Earn Credentials and Start applying for Jobs

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  • Introduction to Cloud Computing
    • In this module, you will learn what Cloud Computing is and what are the different models of Cloud Computing along with the key differentiators of different models. We will also introduce you to virtual world of AWS along with AWS key vocabulary, services and concepts.

      • A Short history
      • Client Server Computing Concepts
      • Challenges with Distributed Computing
      • Introduction to Cloud Computing
      • Why Cloud Computing
      • Benefits of Cloud Computing
  • Amazon EC2 and Amazon EBS
    • In this module, you will learn about the introduction to compute offering from AWS called EC2. We will cover different instance types and Amazon AMIs. A demo on launching an AWS EC2 instance, connect with an instance and host ing a website on AWS EC2 instance. We will also cover EBS storage Architecture (AWS persistent storage) and the concepts of AMI and snapshots.

      • Amazon EC2
      • EC2 Pricing
      • EC2 Type
      • Installation of Web server and manage like (Apache/ Nginx)
      • Amazon EBS
      • Demo of AMI Creation
      • Backup, Restore
      • Exercise
      • Mock
      • Hands on both Linux and Windows
  • Amazon Storage Services S3 (Simple Storage Services)
    • In this module, you will learn how AWS provides various kinds of scalable storage services. In this module, we will cover different storage services like S3, Glacier, Versioning, and learn how to host a static website on AWS.

      • Versioning
      • Static website
      • Policy
      • Permission
      • Cross region Replication
      • AWS-CLI
      • Mount Point with S3
      • Life cycle
      • Classes of Storage
      • AWS CloudFront
      • Real scenario Practical
      • Hands-on all above
  • Cloud Watch & SNS
    • In this module, you will learn how to monitoring AWS resources and setting up alerts and notifications for AWS resources and AWS usage billing with AWS CloudWatch and SNS.

      • Amazon Cloud Watch
      • SNS - Simple Notification Services
      • SQS
      • Cloud Watch with Agent
      • Cloud Watch with System Manager
  • Scaling and Load Distribution in AWS
    • In this module, you will learn about 'Scaling' and 'Load distribution techniques' in AWS. This module also includes a demo of Load distribution & Scaling your resources horizontally based on time or activity.

      • Amazon Auto Scaling
      • Auto scaling policy with real scenario based
      • Type of Load Balancer
      • Path Based load balancer
      • Hands on with scenario based
      • Routing policy on Load balancer
  • AWS VPC
    • In this module, you will learn introduction to Amazon Virtual Private Cloud. We will cover how you can make public and private subnet with AWS VPC. A demo on creating VPC. We will also cover overview of AWS Route 53.

      • Amazon VPC with subnets
      • Gateways
      • Route Tables
      • Subnet
      • Cross region Peering
      • Endpoint Creation with VPC
  • Identity and Access Management Techniques (IAM)
    • In this module, you will learn how to achieve distribution of access control with AWS using IAM.

      Amazon IAM

      • add users to groups,
      • manage passwords,
      • log in with IAM-created users.

      User

      Group

      Role

      Policy

  • Amazon Relational Database Service (RDS)
    • In this module, you will learn how to manage relational database service of AWS called RDS.

      • Amazon RDS
      • Type of RDS
      • RDS Failover
      • RDS Subnet
      • RDS Migration
      • Dynamo DB (No SQL DB)
      • Redshift Cluster
      • SQL workbench
      • JDBC / ODBC
  • Multiple AWS Services and Managing the Resources' Lifecycle
    • In this module, you will get an overview of multiple AWS services. We will talk about how do you manage life cycle of AWS resources and follow the DevOps model in AWS. We will also talk about notification and email service of AWS along with Content Distribution Service in this module.

      • Cloud Trail,
      • SQS
  • AWS Architecture and Design
    • In this module, you will cover various architecture and design aspects of AWS. We will also cover the cost planning and optimization techniques along with AWS security best practices, High Availability (HA) and Disaster Recovery (DR) in AWS.

      • AWS Backup and DR Setup
      • AWS High Availability Design
      • AWS Best Practices (Cost +Security)
      • AWS Calculator & Consolidated Billing
  • Migrating to Cloud & AWS
    • In this module, you will learn how to migrate to cloud

      • Migration to Cloud
      • Migration to AWS
      • Step by step process
  • Router S3 DNS
    • Public DNS

      Private DNS

      Routing policy

      Records

      Register DNS

      Work with third party DNS as well

  • Cloud Formation
    • Stack

      Templet

      Json / Ymal

  • Elastic Beanstalk
  • EFS / NFS (hands-on practice)
  • Hands-on practice on various Topics
    • ECS, EKS (Kubernetes), Docker

      • Comprehensive hands-on with Dockers & Kubernetes Components
      • Docker & Kubernetes Architecture & Components and installation
      • Get introduced to deploy stateful and stateless apps on the cluster
      • Learn how to expose the app outside the cluster and to auto scale apps
      • Expertise learning with use cases of Containers and Docker
      • Installation of Linux
      • Configuration
      • Manage
      • Installation of app on Linux (apache / Nginx etc)
      • AWS cli configuration on Linux
      • Complete hands-on on Linux.
  • Linux
    • Python

      Boto

      DMS

      System Manager

      Mock

      Interview preparation

      Scenario based lab and practical

      Each topic and services will be cover with lab and theory.

      Security: KMS / SSM/ WAF

      Storage: EFS, NFS, FSX, Storage Gateway

  • These topics will be covered with this AWS course with real scenario based
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  • Describe Cloud Concepts
    • Identify the benefits and considerations of using cloud services Cloud Computing Basics.

      • Identify the benefits of cloud computing, such as High Availability,Scalability, Elasticity,
      • Agility, and Disaster Recovery
      • Identify the differences between Capital Expenditure (Cap Ex) and Operational.
      • Expenditure (Op Ex)
      • Describe the consumption-based model

      Describe the differences between categories of cloud services

      • Describe the shared responsibility model
      • Describe Infrastructure-as-a-Service (IaaS),
      • Describe Platform-as-a-Service (PaaS)
      • Describe server less computing
      • Describe Software-as-a-Service (SaaS)
      • Identify a service type based on a use case

      Describe the differences between types of cloud computing

      • Define cloud computing
      • Describe Public cloud
      • Describe Private cloud
      • Describe Hybrid cloud
      • Compare and contrast the three types of cloud computing Describe Core Azure Services
  • Describe Core Azure Services
    • Describe the core Azure architectural components

      • Describe the benefits and usage of Regions and Region Pairs
      • Describe the benefits and usage of Availability Zones
      • Describe the benefits and usage of Resource Groups
      • Describe the benefits and usage of Subscriptions
      • Describe the benefits and usage of Management Groups
      • Describe the benefits and usage of Azure Resource Manager
      • Explain Azure resources

      Describe core resources available in Azure

      • Describe the benefits and usage of Virtual Machines, Azure App Services, Azure Container Instances (ACI), Azure Kubernetes Service (AKS), and Azure Virtual Desktop.
      • Describe the benefits and usage of Virtual Networks, VPN Gateway, Virtual Network peering, and ExpressRoute
      • Describe the benefits and usage of Container (Blob) Storage, Disk Storage,File Storage, and storage tiers
      • Describe the benefits and usage of Cosmos DB, Azure SQL Database, Azure Database for MySQL, Azure Database for PostgreSQL, and SQL Managed Instance.
      • Describe the benefits and usage of Azure Marketplace
  • Describe core solutions and management tools on Azure
    • Describe core solutions available in Azure

      • Describe the benefits and usage of Internet of Things (IoT) Hub, IoT Central, and Azure Sphere
      • Describe the benefits and usage of Azure Synapse Analytics, HDInsight, and Azure Data bricks
      • Describe the benefits and usage of Azure Machine Learning, Cognitive Services and Azure Bot Service
      • Describe the benefits and usage of server less computing solutions that include Azure Functions and Logic Apps
      • Describe the benefits and usage of Azure DevOps, GitHub, GitHub Actions, and Azure Dev Test Labs

      Describe Azure management tools

      • Describe the functionality and usage of the Azure Portal, Azure PowerShell, Azure CLI, Cloud Shell, and Azure Mobile App
      • Describe the functionality and usage of Azure Advisor
      • Describe the functionality and usage of Azure Resource Manager (ARM) templates.
      • Describe the functionality and usage of Azure Monitor
      • Describe the functionality and usage of Azure Service Health
  • Describe general security and network security features
    • Describe Azure security features

      • Describe basic features of Azure Security Center, including policy compliance, security alerts, secure score, and resource hygiene.
      • Describe the functionality and usage of Key Vault
      • Describe the functionality and usage of Azure Sentinel
      • Describe the functionality and usage of Azure Dedicated Hosts

      Describe Azure network security

      • Describe the concept of defence in depth
      • Describe the functionality and usage of Network Security Groups (NSG)
      • Describe the functionality and usage of Azure Firewall
      • Describe the functionality and usage of Azure DDoS protection
  • Describe identity, governance, privacy, and compliance features
    • Describe core Azure identity services

      • Explain the difference between authentication and authorization
      • Define Azure Active Directory
      • Describe the functionality and usage of Azure Active Directory
      • Describe the functionality and usage of Conditional Access, Multi-Factor Authentication
      • MFA), and Single Sign-On (SSO)

      Describe Azure governance features

      • Describe the functionality and usage of Role-Based Access Control (RBAC)
      • Describe the functionality and usage of resource locks
      • Describe the functionality and usage of tags
      • Describe the functionality and usage of Azure Policy
      • Describe the functionality and usage of Azure Blueprints
      • Describe the Cloud Adoption Framework for Azure

      Describe privacy and compliance resources

      Describe the Microsoft core tenets of Security, Privacy, and Compliance

      Describe the purpose of the Microsoft Privacy Statement, Online Services Terms (OST) and Data Protection Amendment (DPA)

      Describe the purpose of the Trust Centre

      Describe the purpose of the Azure compliance documentation

      Describe the purpose of Azure Sovereign Regions (Azure Government cloud services and Azure China cloud services)

  • Describe Azure cost anagement and Service Level Agreements
    • Describe methods for planning and managing costs

      • Identify factors that can affect costs (resource types, services, locations,ingress and egress traffic)
      • Identify factors that can reduce costs (reserved instances, reserved capacity,hybrid use benefit, spot pricing)
      • Describe the functionality and usage of the Pricing calculator and the Total Cost of Ownership (TCO) calculator
      • Describe the functionality and usage of Azure Cost Management

      Describe Azure Service Level Agreements (SLAs) and service lifecycles

      • Describe the purpose of an Azure Service Level Agreement (SLA)
      • Identify actions that can impact an SLA (i.e. Availability Zones)
      • Describe the service lifecycle in Azure (Public Preview and General Availability)
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  • Data Science Professionals - Live Projects
    • Managing credit card Risks

      Bank Loan default classification

      YouTube Viewers prediction

      Super store Analytics (E-commerce)

      Buying and selling cars prediction (like OLX process)

      Advanced House price prediction

      Analytics on HR decisions

      Survival of the fittest

      Twitter Analysis

      Flight price prediction

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