IoT Training Institute in Noida

Numbers, List, Tuple & dictionaries

If else statements

Loop & Control Statements

File Handling

Understanding Functions

Raspberry Pi Programming

Interfacing Sensors with Raspberry Pi

Introduction to IoT Gateway

ESP8266 Module as Wi-Fi Gateway

Learning AT Commands of ESP8266

Programming on ESP8266 Wi-Fi Module

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

Cities

Home

Agriculture

Healthcare Industry

Transportation

Environment

Infrastructure

Security

Future Scope

Challenges

Security

Categorical Data

Numerical Data

Mean

Median

Mode

Outliers

Range

Interquartile range

Correlation

Standard Deviation

Variance

Box plot

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)

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

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 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

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

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

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

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 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 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

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

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

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

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

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

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

Cursor declaration and Life cycle

STATIC

DYNAMIC

SCROLL Cursors

FORWARD_ONLY and LOCAL Cursors

KEYSET Cursors with Complex SPs

ACID Properties and Scope

EXPLICIT Transaction types

IMPLICIT Transactions and options

AUTOCOMMIT Transaction and usage

SAVEPOINT and Query Blocking

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

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

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

Feature Selection

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

Label encoding/one hot encoding

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.)

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

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

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 Preparation

Feature Engineering

Feature Scaling

Datasets

Dimensionality Reduction

Anomaly Detection

Parameter Estimation

Data and Knowledge

Selected Applications in Data Mining

Machine Learning

Machine Learning Algorithms

Algorithmic models of Learning

Applications of Machine Learning

Large Scale Machine Learning

Computational Learning theory

Supervised Learning

Unsupervised Learning

Semi-supervised and Reinforcement Learning

Bias and variance Trade-off

Representation Learning

Regression and its Types

Logistic Regression

Linear Regression

Polynomial Regression

Meaning and Types of Classication

Probability and Bayes Theorem

Support Vector Machines

Naive Bayes

Decision Tree Classier

Random Forest Classier

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

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

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

Extracting data from various sources

Workspaces in Power BI

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

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

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

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

Why Dashboard and Dashboard vs Reports

Creating Dashboards

Conguring a Dashboard: Dashboard Tiles, Pinning Tiles

Power BI Q&A

Quick Insights in Power BI

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

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

Understanding Data Refresh

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

Replacing a Dataset and Troubleshooting Refreshing

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

Features of Tableau Desktop

Connect to data from File and Database

Types of Connections

Joins and Unions

Data Blending

Tableau Desktop User Interface

Visual Analytics

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

Hierarchies

Data Granularity

Highlighting

Sorting

Filtering

Grouping

Sets

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

Parameters

Tool tips

Trend lines

Reference lines

Forecasting

Clustering

Count Customer by Order

Profit per Business Day

Comparative Sales

Profit Vs Target

Finding the second order date

Cohort Analysis

Introduction to Geographic Visualizations

Manually assigning Geographical Locations

Types of Maps

Spatial Files

Custom Geocoding

Polygon Maps

Web Map Services

Background Images

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

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

Tableau Tips and Tricks

Choosing the right type of Chart

Format Style

Data Visualization best practices

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

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

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

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

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

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

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

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

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

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

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

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

In this module, you will learn how to migrate to cloud

• Migration to Cloud

• Migration to AWS

• Step by step process

Public DNS

Private DNS

Routing policy

Records

Register DNS

Work with third party DNS as well

Stack

Templet

Json / Ymal

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.

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

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 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 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 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 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 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)

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