Organizations that rely on instinct often miss key opportunities. The ones that trust their data? They win more customers, keep them longer, and earn more in the process. In fact, data-driven organizations are 23 times more likely to acquire customers, six times more likely to retain them, and 19 times more likely to be profitable.

This course shows you how to use Microsoft Excel to make sense of data and communicate it clearly. You’ll learn how to organize, clean, and analyze datasets, build dashboards that update with a click, and present insights using tools like PivotTables, Power Pivot, and geospatial charts. For professionals responsible for reporting, forecasting, or decision support, this training delivers practical, real-world skills you can apply right away.

In the future, organizations that succeed will be those that put data at the forefront of their business strategy. This Data Literacy training is designed to give you a high level overview of the key topics in Data Science and Machine Learning. Designed exclusively for students who want to learn about the basics of data science and machine learning at a high level, without needing to learn how to code or cover complex mathematics. In this course you’ll learn the fundamental concepts relating to data, allowing you to understand what makes data suitable for data analysis, visualization and machine learning. Then we’ll give you a quick overview of important statistical topics, such as mean, standard deviation, and the normal distribution. Afterwards you will learn the different ways data scientists are able to visualize data to convey their ideas in a clear manner. We’ll also teach you about the machine learning process, acquiring data, cleaning data, and an overview of the train/test split philosophy that supervised learning adheres to. Then we’ll show you some examples of regression and classification algorithms, as well as how to evaluate their results. We’ll also explore what the future holds by taking a peek at the bleeding edge of AI and ML, including DALLE-2 and GPT-3!

This course will teach the basics of Microsoft’s dialect of the standard SQL language: Transact-SQL. Topics include both querying and modifying data in relational databases that are hosted in Microsoft SQL Server-based database systems, including: Microsoft SQL Server, Azure SQL Database and, Azure Synapse Analytics.

Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.

In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.

Did you know that over 95% of Fortune 500 companies use Microsoft Azure to manage their cloud infrastructure? Are you equipped to administer critical SQL workloads in the cloud?

In this course, you’ll learn to administer SQL Server databases across IaaS, Azure SQL Database in PaaS, and hybrid environments. You’ll configure high availability, secure sensitive data, migrate workloads, and fine-tune performance, skills that directly support>real-world database administration success.

This course also gets you ready for the DP-300 exam, a key step toward earning your Microsoft Certified Azure Database Administrator Associate credential, which proves you have the skills to manage modern database solutions on the Microsoft data platform.

Organizations today rely on data-driven decision-making, but managing massive datasets across cloud platforms can be complex. DP-3011 Implementing a Data Analytics Solution with Azure Databricks equips data professionals to prepare, analyze, and govern data at scale using Apache Spark’s distributed computing capabilities.

In this one-day training, you’ll gain hands-on experience with Delta Lake for versioning and data integrity, automate data pipelines with Delta Live Tables, and implement governance with Unity Catalog. You’ll also explore Spark for large-scale data analysis, orchestrate workflows for production deployments, and collaborate in Python and SQL notebooks to deliver high-quality analytics-ready data.