This course is an introduction to large-scale data analytics. Big Data analytics is the study of how to extract actionable, non-trivial knowledge from massive amount of data sets.
DurationThis course is an introduction to large-scale data analytics. Big Data analytics is the study of how to extract actionable, non-trivial knowledge from massive amount of data sets. This class will focus both on the cluster computing software tools and programming techniques used by data scientists, as well as the important mathematical and statistical models that are used in learning from large-scale data processing.
On the tools side, we will cover the basics systems and techniques to store large-volumes of data, as well as modern systems for cluster computing based on Map-Reduce pattern such as Hadoop MapReduce, Apache Spark and Flink.
Students will implement data mining algorithms and execute them on real cloud systems like Amazon AWS, Google Cloud or Microsoft Azure by using educational accounts. On the data mining models side, this course will cover the main standard supervised and unsupervised models and will introduce improvement techniques on the model side.
To remain competitive in rapidly evolving industries such as commercial real estate, financial services, fundraising, law, and genealogy—among others—you need to be aware of current and emerging best practices, obtain industry-standard credentials and certifications, and master changing technology.
Companies rely on data to help identify challenges, capitalize on opportunities and make timely business decisions that could materially affect their bottom line.
This three-day instructor-led course will teach how to use the entire Power BI and Power BI Desktop toolset as your business intelligence platform. You'll learn how to implement solutions using the Power Query
This two-day course provides students with the knowledge and skills to analyze data with Power BI.
The business intelligence training offers Business Intelligence (BI) Concepts, Microsoft Power BI, Power BI Architecture, Connecting Power BI with Different Data Sources, and many more
Students learn how to connect to a data source, transform data, organize a data model, create measures to summarize their data, and express their data using Power BI visualizations.
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