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Microsoft

Summarizing data: Aggregate functions and grouping

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Analyze data in PostgreSQL with aggregate functions and grouping. Learn COUNT, SUM, AVG, and filter results using GROUP BY and HAVING.

Units in this learning path:

• Introduction
• Sample Database Overview
• Aggregate Functions
• Group by Having
• Summary

Products: Azure Database Postgresql

Roles: Database Administrator, Developer

Level: Beginner

Subjects: Databases

Duration: 15 minutes

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Microsoft

Train a machine learning model in Azure Databricks

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Learn how to train machine learning models using Spark and the MLlib library in Azure Databricks.

Units in this learning path:

• Introduction
• Understand Machine Learning
• Machine Learning Azure Databricks
• Prepare Data for Machine Learning
• Train Model
• Evaluate Model
• Exercise Machine Learning Databricks
• Knowledge Check
• Summary

Products: Azure Databricks

Roles: Data Scientist

Level: Intermediate

Subjects: Data Management, Machine Learning

Duration: 84 minutes

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Microsoft

Train and track machine learning models with MLflow in Microsoft Fabric

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Learn how to train machine learning models in notebooks and track your work with MLflow experiments in Microsoft Fabric.

Units in this learning path:

• Introduction
• Train Model
• Mlflow
• Fabric Models
• Exercise
• Knowledge Check
• Summary

Products: Fabric

Roles: Data Analyst, Data Engineer, Data Scientist

Level: Beginner

Subjects: Data Management, Machine Learning

Duration: 54 minutes

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Microsoft

Train deep learning models in Azure Databricks

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Learn how to use deep learning libraries like PyTorch in Azure Databricks, and to distribute training by using TorchDistributor

Units in this learning path:

• Introduction
• Deep Learning
• Pytorch
• Horovod
• Exercise Deep Learning
• Knowledge Check
• Summary

Products: Azure Databricks

Roles: Data Scientist

Level: Advanced

Subjects: Data Management, Machine Learning

Duration: 70 minutes

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Microsoft

Transfer and transform data with Azure Synapse Analytics pipelines

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Learn how to use Azure Synapse Analytics pipelines to automate and orchestrate data transfer and transformation activities.

Modules in this learning path:

• Build Data Pipeline Azure Synapse Analytics
• Use Spark Notebooks Azure Synapse Pipeline

Products: Azure Synapse Analytics

Roles: Data Engineer

Level: Intermediate

Subjects: Data Engineering

Duration: 119 minutes

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Microsoft

Transform and load event log data for process mining

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Learn how to transform and load event log data for process mining.

Units in this learning path:

• Introduction
• Normalize Event Log Data
• Filter Event Log Data
• Load Event Log Data
• Exercise
• Check
• Summary

Products: Power Automate

Roles: Functional Consultant, Developer

Level: Beginner

Subjects: Data Management

Duration: 43 minutes

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Microsoft

Transform data with Spark in Azure Synapse Analytics

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Learn how to use Apache Spark pools in Azure Synapse Analytics to transform data.

Units in this learning path:

• Introduction
• Transform Dataframe
• Partition Data
• Tramsform SQL
• Exercise Transform Data Spark Azure Synapse Analytics
• Knowledge Check
• Summary

Products: Azure Synapse Analytics

Roles: Data Engineer

Level: Intermediate

Subjects: Data Engineering

Duration: 50 minutes

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Microsoft

Try Azure Cosmos DB for NoSQL

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Try Azure Cosmos DB for NoSQL

Units in this learning path:

• Introduction
• Explore Resources
• Review Basic Operations
• Exercise Create Account
• Knowledge Check
• Summary

Products: Azure Cosmos Db

Roles: Developer

Level: Intermediate

Subjects: Databases

Duration: 32 minutes

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Microsoft

Tune hyperparameters in Azure Databricks

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Learn how to use the Optuna library in Azure Databricks to tune machine learning hyperparameters.

Units in this learning path:

• Introduction
• Hyperopt
• Review Hyperopt Trials
• Scale Hyperopt
• Exercise Use Mlflow
• Knowledge Check
• Summary

Products: Azure Databricks

Roles: Data Scientist

Level: Intermediate

Subjects: Data Management, Machine Learning

Duration: 68 minutes

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Microsoft

Tune queries in Azure Database for PostgreSQL

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Relational databases store many different types of data for many different types of applications. Some databases have thousands of users and some have just one user. Some tables have tens of rows while others have millions of rows. Some data is unique while other data is duplicated. All of these variables mean that database management systems (DBMSs) need systems to understand the data and the queries that are running against this data to ensure optimum performance. When you perform tune a database, it's important to understand how performance tuning works and how you can assess performance metrics.

Units in this learning path:

• Introduction
• Understand Statistics
• Assess Query Performance Query Store
• Exercise Assess Query Performance Query Store
• Knowledge Check
• Summary

Products: Azure Database Postgresql

Roles: Database Administrator

Level: Intermediate

Subjects: Databases

Duration: 31 minutes

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Microsoft

Understand PostgreSQL query processing

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The Azure Database for PostgreSQL server receives SQL queries and returns the relevant results. Each SQL query goes through several stages in order to return the correct results as quickly as possible. In this module, you learn about the different stages of processing a query, and the EXPLAIN statement.

Units in this learning path:

• Introduction
• Identify Components
• Understand Explain
• Exercise Execute Explain
• Knowledge Check
• Summary

Products: Azure Database Postgresql

Roles: Database Administrator

Level: Intermediate

Subjects: Databases

Duration: 20 minutes

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Microsoft

Understand client-server communication in MySQL

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Learn about connection handling in MySQL, back up and restore, and the client interrace options available for MySQL.

Units in this learning path:

• Introduction
• Understand Connection Handle
• Describe Client Interfaces
• Understand Mysql Query Interface Options
• Exercise Explore Mysql Workbench
• Knowledge Check
• Summary

Products: Azure Database Mysql

Roles: Database Administrator

Level: Intermediate

Subjects: Databases

Duration: 31 minutes

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