What can I expect after completing the IoT training from Croma Campus?

Here, at Croma Campus, you will get many advantages and get to understand topics like. IoT applications in different domains. IoT framework and architecture. Create a sensor network. Arduino programming. Integrate embedded devices to the cloud.

What are the modes of training offered at Croma Campus for IoT Training?

Unlike any other IoT Training Institute in Delhi, Croma Campus offers excellent online and live interactive trainer-led sessions. Thus, you will get to learn from professional trainers and clear your doubts.

Who will provide IoT Training at Croma Campus?

Croma Campus provides learners with professional trainers having years of experience in the field of IoT. So, they can help you with real-life problems and share their experiences to help you understand the roles and responsibilities of IoT professionals.

How is the IoT training structured at Croma Campus?

Croma Campus offers a promising course structure and provides you with the best IoT Training in Delhi. Here, you will get live interactive online and offline modes of classes. The course structure focuses on lively discussions and finding practical solutions using real-life projects and assignments.

Will Croma Campus help me get better job opportunities after completing IOT training?

After completing the IoT training, Croma Campus will provide you with placement assistance and help you crack interviews. Moreover, they will help you with your resume to meet the latest industry standards.

Job Based IoT Training Institute in Delhi

Name: Internet of Things (IoT) Certification Training
Item: Internet of Things (IoT) Certification Training
Rating: 4.90

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

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Since the technology continues to proliferate all aspects of our lives, the IoT skills are very much in need so as not to stagnate your organization. The IoT technology has gained momentum over the years and is continuing to shape our future by connecting devices to each other and to the internet, to help us lead a convenient lifestyle. This is the reason that most of the leading industries have adopted IoT as a part of their businesses such as IBM, Amazon, Microsoft, etc.
For some of the enterprises, those who haven’t yet incorporated IoT in their workforce and are unsure about the benefits of IoT platforms, our IoT training in Delhi comes into play. It helps those companies to significantly understand the benefits of the technology and help them to implement it in the workplace as well.
Indeed, IoT has become a major part of industries, and no wonder it is transforming business models by helping companies to produce customer desired outcomes. It is predicted that within some years almost all of the industry might have adopted IoT platforms and will emerge as the hottest market player that would help save the overall company budget. According to a survey, the IoT market can reach up to $7 trillion by 2022, and by 2025 it will nearly triple to more than $75 billion.
Undoubtedly, there are endless benefits of adopting IoT-based applications that include improving overall manufacturing efficiency, operations management effectiveness, helping customers interact seamlessly, and much more. IoT being adopted at a fast pace is the reason you should enroll for an IoT course and get to learn with one of the most premier IoT training in Delhi.

The IoT training in Delhi is designed to incorporate the most fundamental and advanced concepts in IoT.

The course has been developed by industry experts to help you understand more about IoT networking protocols and to design powerful solutions.

With the IoT certification course in Delhi, you will be able to set up Raspberry Pi and get to learn programming sensors, actuators, and a lot more.

The IoT training in Delhi has been intended to teach all about IoT basics, IoT decision framework, etc.

Procure enough understanding of cloud or Azure IoT hub, and how to exhibit hub APIs in MS azure.

Also, get proficient in designing end-to-end solutions using various IoT technologies and tools as per the need with the help of the IoT training institute in Delhi.

Acquire substantial knowledge about performing data analytic techniques and get meaningful insights from the collected data by using prediction algorithms.

Designed by well-experienced and accredited industry experts, our IoT training course covers major concepts such as IoT framework, IoT ecosystem, IoT architecture, IoT implementation, IoT tools, etc. Also, with one of the leading IoT placement course in Delhi, get to work on real-time projects and case studies so as to hone your skills in the desired domain and implement them in the workplace as well.

It is expected that by 2022, more than 50 billion devices will be connected by IoT.

By the end of 2022, the global market will reach from 700 billion to 2 trillion.

According to Glassdoor, an IoT certified developer can earn up to $150K in basic level and can earn even more with experience.

Once you complete the course with one of the prominent IoT training institute in Delhi, you can establish yourself as an IoT expert and leverage the benefits of a certified IoT professional. This course also helps you to practice implementing big data tools and techniques in IoT. Needless to say, IoT is one of the emerging and the most promising technologies that will be creating a lot of opportunities in near future.

IoT training in Delhi is helping learners to create better life-saving devices worldwide.

While IoT is in a nascent stage and still being used almost everywhere, it is estimated that the jobs in the IoT world will continue to increase as the industry expands.

Since there are more than 30 billion devices powered by IoT, there is a huge demand for trained and certified IoT experts as so as to manage workloads efficiently.

With the premium IoT training institute in Delhi, prepare yourself for global certification and cement your position in the IT sector.

Build an impressive resume along with 100% placement assistance and escalate in your career journey.

IoT has been more ubiquitous in our daily lives with each passing year. From using a wide range of products like desktops, laptops, smartphones, wrist bands, etc, IoT technology has connected through the internet to produce meaningful insights. Even sensors, vehicles, and many such devices are also growing at a fast pace. There has been increased productivity across the enterprises, so as to create actionable data and to drive efficiency in the workplace.
Here are some of the advantages of the IoT platform.

It reduces the risk of a thunderstorm by amplifying data analytic capabilities. It also saves millions of dollars as well.

It helps in achieving maximum customer satisfaction through logistics and operations management in enterprises.

According to research, there have been more than 50 billion devices interconnected in 2020 using IoT services.

Some of the major roles and responsibilities that are covered as a part of IoT training in Delhi are:

You should have in-depth knowledge of IoT basic and advanced concepts.

You must have a functional idea about IoT basics, IoT architecture, IoT decision framework, and more.

You need to know to configure raspberry Pi, know about programming sensors, actuators, etc.

You must be able to end-to-end solutions using various IoT technologies and tools as per need.

You should have some idea about cloud or Azure IoT hub and should be able to demonstrate hub APIs in MS azure.

You must be proficient in IoT networking protocols and must be able to design powerful solutions as such.

You need to know all about performing data analytics techniques on to the collected data and should know how to use prediction algorithms to get meaningful insights from it.

With one of the most leading IT training company in India, get yourself ready to manage all the roles and responsibilities with utmost ease and confidence.

Major companies like Honeywell, Intel, Amdocs, Microsoft, and IBM, etc., are already hiring IoT professionals. Since IoT is the next big thing after the discovery of the web, it has become a buzzword in the IT world. According to Cisco, there have been 50 million devices working on IoT at present and it will soon change to billions.
Furthermore, IoT is not only confined to a single domain but has been used everywhere such as in the healthcare sector, aviation, logistics, IT, and a lot more. Since it is so widely used, it has opened a huge career option for learners who are steadfast to build their careers in this IoT domain. Hence to start your career in this field, it is requisite to complete the IoT training course in Delhi and fly higher in your career.

With an IoT training in Delhi course, you will get to learn all the basic and advanced concepts with utmost ease. The course also ensures that you get to learn IoT applications, physical layer protocol, and other standard IoT frameworks as well. It intuitively focuses on providing insights to build and deploy powerful IoT solutions to enterprises.
Just after the completion of the course, you will be provided with a training certificate which will embellish your resume and will make you stand out from the rest. The best part of this training certificate it is recognized across the globe and can help professionals land jobs anywhere in the world in the IoT domain.

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Why should you learn the Internet of Things?

You can easily become Data Scientist or Data Analyst.

User-friendly programming language & highly demanded.

Affordable option of learning & budget-oriented course.

Multi-dimensional course. Consist out various modules.

Safe & Secure learning environment which ensure reliability.

Not just learning

we train you to get hired.

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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

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,

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,

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

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

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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+ More Lessons

Course Design By

Nasscom & Wipro

Course Offered By

Croma Campus

Real

Stories

success

inspiration

Abhishek

career upgrad

Upasana Singh

career upgrad

Shashank

career upgrad

Abhishek Rawat

career upgrad

Course Duration

30 Hrs.

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Flexible Batches For You

18-Oct-2025*
Weekend
SAT - SUN
Mor | Aft | Eve - Slot

20-Oct-2025*
Weekday
MON - FRI
Mor | Aft | Eve - Slot

22-Oct-2025*
Weekday
MON - FRI
Mor | Aft | Eve - Slot

18-Oct-2025*
Weekend

SAT - SUN

Mor | Aft | Eve - Slot

20-Oct-2025*
Weekday

MON - FRI

Mor | Aft | Eve - Slot

22-Oct-2025*
Weekday

MON - FRI

Mor | Aft | Eve - Slot

Course Price :

For Indian

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This Course

Program fees are indicative only* Know more

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