The advent of cloud computing and storage has ushered in the era of „big data.“ With the abundance of computational power and storage, organizations and employees with many different roles and responsibilities can benefit from analyzing data to find timely insights and gain competitive advantage. Data-backed visualizations allow anyone to explore, analyze, and report insights and trends from data. Tableau® software is designed for this purpose. Tableau was built to connect to a wide range of data sources, and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Beyond the fundamental capabilities of creating data driven visualizations, Tableau allows users to manipulate data with calculations to show insights, make visualizations interactive, and perform statistical analysis. This gives users the ability to create and share data driven insights with peers, executives and clients.
The era of „big data“ has exploded due to the rise of cloud computing, which provides an abundance of computational power and storage allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and competitive advantage. This course will introduce you to Tableau, which was built to connect to a wide range of data sources and allow users to quickly create visualizations of connected data to gain insights, show trends, and create reports. You will learn Tableau’s data connection capabilities and visualization features which go far beyond those that can be found in spreadsheets, allowing you to create compelling and interactive worksheets, dashboards, and stories, that bring your data to life and allow you to take thoughtful action.
This course covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases.
In this course, you’ll learn the fundamentals of programming in Python, and you’ll develop applications to demonstrate your grasp of the language.
An introductory and beyond-level practical, hands-on Python training course that leads the student from the basics of writing and running Python scripts to more advanced features.
In this course, students will learn general strategies for planning, designing, developing, implementing, and maintaining an IoT system through various case studies and by assembling and configuring an IoT device to work in a sensor network. Students will create an IoT device based on an ESP8266 microcontroller, implementing various common IoT features, such as analog and digital sensors, a web-based interface, MQTT messaging, and data encryption.
Gain the necessary knowledge about how to use Azure services to develop, train, and deploy, machine learning solutions. The course starts with an overview of Azure services that support data science. From there, it focuses on using Azure’s premier data science service, Azure Machine Learning service, to automate the data science pipeline.
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