TRAINNING BY UNISYS

1. Azure Synapse Analytics is an analytics service that provides functionality for data integration, enterprise data warehousing, and big data analytics. Services provided include ingesting, exploring, preparing, managing, and serving data for BI and machine learning needs. This course covers Azure Synapse Analytics platform and how it is used for data warehousing and big data analytics and how to create a Synapse Workspace, a dedicated SQL pool, and a serverless Apache Spark pool. This course even demonstrate on how to analyze data using a dedicated SQL pool, Apache Spark for Azure Synapse, Serverless SQL Pools, and a Spark database, as well as how to analyze data that is in a storage account. You'll learn how to integrate pipelines using Synapse Studio, visualize data using a Power BI workspace, and monitor a Synapse Workspace. Finally, the course covers  about the Synapse Knowledge Center and the features of Azure Synapse Analytics and Poly Base. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.


• Describe the Azure Synapse Analytics platform and how it is used for data warehousing and big data analytics

• Integrate pipelines using Synapse Studio

• Visualize data using a Power BI workspace that is linked to an Azure Synapse Workspace

• Monitor a Synapse Workspace

• Recognize features of the Synapse Knowledge Center

• Describe the features of Azure Synapse Analytics and Poly Base


https://unisys.percipio.com/courses/0a521a1a-fb7e-4096-a190-5bbbd41c2e65/videos/2baba841-a2a6-4f99-b0a3-27abbebc3ee0








2.Data ingestion and processing allows your data to be assessed, used, and analyzed. In this course, you’ll learn about Azure data ingestion and processing, including loading strategies for Synapse SQL Pools. You'll examine Azure data factory pipelines and activities, as well as how to create an Azure data factory. Next, you'll learn how to use the data factory copy data tool to copy data. Finally, you'll explore how to use SQL Server Integration Services, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake to ingest data. This course is one in a series that prepares learners for the Microsoft Azure Data Fundamentals (DP-900) exam.


• Identify loading strategies for Synapse SQL pools
• Describe Azure data factory pipelines and activities
• Create an Azure data factory
• Use the Azure data factory copy data tool to copy data
• Use Azure Synapse Analytics PolyBase to ingest data
• Use SQL Server Integration Services (SSIS) to ingest data
• Use Azure Data bricks to ingest data
• Use Azure Synapse Analytics to load data
• Use Azure Data Lake to load data

https://unisys.percipio.com/courses/629a8412-9439-4fcc-b55b-c02b6e369b93/videos/9378cccb-d772-4736-bc89-6b42cf908e20



3.Python is a beneficial language for use in a lot of development projects.This course covers basics of Python programming and introduces  to basic math and logical operations in Python by creating and assigning to variables and see how to access values stored in these variables. Further this course helps in understanding built-in functions, which are part of the core Python programming language, to perform simple calculations and operations. Finally, you'll explore strings in Python work, creating strings using single, double, and triple quotes depending on the use case and then briefly examine the use of complex data types, such as lists, tuples, sets, and dictionaries.

• Discover the key concepts covered in this course
• Execute commands on the Python shell
• Perform basic math operations
• Execute arithmetic operations on variables
• Work with built-in functions
• Use the different kinds of primitive data types, such as strings, numbers, and Booleans
• Create and use complex data types, such as lists, tuples, and sets
• Perform type conversions
• Use single, double, and triple quotes to create strings
• Perform escaping and formatting of strings

https://unisys.percipio.com/courses/17231484-de8a-440f-88e8-dd7a0d4e5e14/videos/35363426-6f38-4a67-9d4b-9a62daa32827


4.Code readability and simplicity are the primary design goals of the Python language. Add a few key APIs and it becomes a powerful data analysis tool. Examine basic data science fundamentals and how to apply them to Python.




• Perform basic data manipulation using pandas

• Create a data visualization using matplotlib and ggplot2

• Demonstrate how to set up and use Anaconda for Python in Eclipse

• Use the scikit-image package to perform image processing in Python

• Use the ArcGIS Python API in a Python app

• Use NLTk and Python to tokenize words and sentences

• Analyze an ego network using Python and Networkx

• Perform web scraping using the BeautifulSoup Parser for Python

• Perform basic data manipulation using pandas

https://unisys.percipio.com/courses/7dbfc570-52ce-11e7-ae20-ceb650f9130b/videos/7dbfc571-52ce-11e7-ae20-ceb650f9130b






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