Looking for Microsoft Azure Freelance Trainer

We are looking for a Microsoft Azure trainer freelance trainer with good experience in training the students and for corporates as well. This is an immediate vacancy.

CLOUD COMPUTING BASICS
l Why Cloud Computing?
l What is Cloud Computing ?
l What is Azure and How to Create Free Azure Account ?
- Azure Regions

AZURE SQL DATABASE
l Overview of Azure SQL Database
Azure SQL Security, Backup and Recovery
l Lab: Create Azure SQL Database
l Lab: Pricing Tiers
l Lab: Azure SQL Virtual Machine
l Lab: Connect and execute queries on Azure SQL Database
l Lab: Elastic Pools
l Quiz
l Lab: Active Geo Replication
l Lab: Failover Group
l Lab: Dynamic Data Masking
l Lab: Auditing

AZURE DATA FACTORY
l Introducing & Creating a Data Factory
- Different types of Triggers
- Connect and manage Datafactory with Github
- When to use different Integration runtimes (Azure, Self hosted, Azure-SSIS)
- Copy activity performance and scalability guide
- Secure credentials within Linked services
l Lab: Building Blocks of Data Factory
l Quiz
- questions
l Lab: Copy Data Activity - Scenario 1
l Lab: Copy Data Activity - Scenario 2
l Copy files from local filesystem to Azure SQL Database
l Lab: Get Metadata Activity
l Lab: Filter Activity
l Lab: If - Else Activity
l Lab: Append Activity
l Lab: Wait Activity
l Lab: For Each Loop Activity
l Lab: Lookup Activity
l Load a table from one db to another db based on a condition
l Lab: Data Flow - Source
l Lab: Data Flow - Sink
l Lab: Data Flow - Conditional Split
l Lab: Data Flow - Derived Column
l Lab: Data Flow - Lookup
l Lab: Data Flow - Select
l Lab: Data Flow - Filter
l Lab: Data Flow - Join
l Lab: Data Flow - Exists
l Load records in respective tables based on their department
l Lab: Parameters - Linked Services Parameters
l Lab: Parameters - Pipeline Parameters
l Lab: Parameters - Data Flow Parameters
l Lab: Monitoring - Visually Monitor
l Lab: Monitoring - Azure Monitoring

REAL WORLD USE CASE
l Introduction to Incremental Data Load
l Lab: Implementing in Azure Data Factory V2
l Artifacts for Tables used in the Lab session
l Introduction to Slowly Changing Dimension Type I
l Lab: Implementing Slowly Changing Dimension Type I in ADFv2
l Artifacts for Tables used in the Lab session of SCD Type 1
l Introduction to Slowly Changing Dimension Type 2
l Artifacts for Tables used in the Lab Session of SCD Type II
l Lab: Implementing Slowly Changing Dimension Type 2 in ADFv2
- Best practices for Code migration between NPE and Production Data factory instances

AZURE DATA LAKE STORAGE GEN 2
l Introduction to Azure Data Lake Storage Gen2
- Data Redundancy options
- Access tier and life cycle management
l Lab: Create Azure Data Lake Storage Gen2
l Lab: Storage Explorer
l Lab: Access Control and Data Transfer
l Lab: Shared Access Signatures (SAS)
- Lab: Control Access using Access Control Lists
l Lab: Encryption
l Lab: Monitoring Azure Data Lake Storage
l Lab: Security

AZURE SYNAPSE ANALYTICS (FORMERLY SQL DATA WAREHOUSING)
l Introduction to Azure Synapse Analytics
l Lab: Synapse Workspace & Synapse Studio
l Understanding Synapse SQL Pool Architecture
l Lab: Create Synapse SQL Pool in Azure Portal
l Lab: Setting up & Loading data using Polybase
Lab: Analyze data with Apache Spark and PowerBI
Lab: Read/Write ADLS

Azure Data Engineering
l Lab: Load Data using CTAS
l Lab: Load Data using Copy Into Statement
l Lab: Load Data using Azure Data Factory
l Lab: Restore Synapse SQL Pool from Restore Point
l Lab: Geo Backups
l Lab: Encryption and Auditing
l Lab: Monitoring Synapse SQL Pool

AZURE COSMOS DB
l Why CosmosDB? Problem Statement
l Introduction to CosmosDB
l CosmosDB - Pricing Structure
l Create CosmosDB in Azure Portal
l Concepts - Multi API Support
l Concepts - Database, Container, Items
l Concepts - Partitions: Physical & Logical
l Concepts - Consistency
l Lab: Create Container, Items, Unique Keys, Partition Key, Indexing
l Lab: Replicate data globally
l Lab: Set Consistency
l Lab: Monitor Cosmos DB
l Lab: Build C# app to connect and read data from cosmos db

AZURE STREAM ANALYTICS
l Introduction to Azure Stream Analytics
l Create a ASA Job
l Implement a end to end scenario using reference data, event hub, sql database
l Built in Window Functions
l Monitor and Troubleshoot a Stream Analytics Job

AZURE DATA BRICKS
l Introduction
l Lab: Create Azure Databricks Workspace
l How to download resources like source code or source files?
l Lab: Components of Azure Databricks
- Notebook features - multiple languages, tabular and visual output, parameters
- Explore databases and tables
- Lab: Standard, High Concurrency and Job Clusters
- Data Engineering and Data Analytical workloads
- Lab: Databricks Delta Lake
- Lab: Code integration with Git
- Lab: Connect with ADLS
- Lab: Install libraries and use in notebooks
- Lab: Table Access Control and Credential Passthrough options
- Best practices for cost and performance management
- Lab: Transform data using Spark SQL
- Lab: Transform data using Pyspark / Scala