Foundations of Cloud Analytics

SAS via Coursera Specialization

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Overview

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Develop practical skills in cloud computing with Microsoft Azure and data analytics with SAS Viya for entry-level careers in data, analytics, and cloud. Designed for students and career switchers, this Specialization helps you understand how cloud services and analytics platforms work together to support the data and AI life cycle to make smarter business decisions. You’ll start with Microsoft Azure fundamentals, including core cloud concepts, Azure services, architecture components, storage, virtual networking, virtual machines, scalability, and hands-on practice in the Microsoft Azure portal and sandbox environment. You’ll then build analytics skills with SAS Viya, exploring platform architecture, data management, visualization, model development, and coding in SAS or Python within an integrated analytics environment. This program is a strong fit for learners interested in roles such as junior data analyst, analytics associate, cloud support, or cloud operations–adjacent positions. You’ll gain exposure to tools and technologies including Microsoft Azure, virtual networking, cloud storage, virtual machines, SAS Viya, SAS Studio, SAS Visual Analytics, and SAS Model Studio. To be successful, learners should have basic computer literacy and familiarity with general technology concepts such as networking, storage, compute, and application support. No advanced coding is required to begin.

Syllabus

Course 1: Overview of Cloud Analytics with SAS and Microsoft
Course 2: Essentials with Azure Fundamentals
Course 3: Analytics Applications Across the Data & AI Lifecycle
Course 4: Cloud Based Analytics and AI Programming

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In this course you’ll cover the fundamentals of cloud computing, exploring key concepts, Azure services, and management tools. You’ll engage in hands-on projects, applying your knowledge to optimize resources using Azure Resource Manager (ARM) templates, Azure Policy, and Azure Monitor. You’ll also gain practical insights into automated deployment, governance, and resource optimization within the Azure ecosystem. After completing this course, you’ll be able to: • Discuss the basics and benefits of cloud computing. • Describe various cloud computing models and their applications. • Describe core Azure services, their features, and applications. • Discuss advanced features and capabilities of Azure services. • Implement comprehensive monitoring with Azure Monitor. This is also a great way to prepare for the Microsoft AZ-900 exam. By passing the AZ-900 exam, you’ll earn the Microsoft Azure Fundamentals certification.
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This course is designed for learners who are new to analytics or transitioning into a data-focused career. It provides a practical introduction to the SAS Viya platform and shows how data is transformed into insights and decisions across the full data and AI life cycle. Learners explore the core SAS Viya applications, including tools for discovering data assets, preparing and managing data, exploring and visualizing results, building predictive models, and automating decisions. Through guided demonstrations and hands-on workflows, learners gain experience working with in-memory data, creating visual process flows, developing and comparing models, and applying analytics to realistic business scenarios. The course emphasizes productivity, performance, trustworthy AI, and collaboration across technical and nontechnical roles. By the end of the course, learners understand how analytics teams use SAS Viya to solve business problems and can confidently describe their skills, tools, and workflows in job interviews or early career roles.
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This course introduces the programming capabilities of the SAS Viya platform for learners who want to work directly with code to manage, process, and analyze data. Learners use SAS Studio to write, execute, and manage programs that run in both the SAS Compute Server and the high‑performance SAS Cloud Analytic Services (CAS) environment. The course explains when and how to leverage in‑memory, parallel processing to improve performance for large or complex data workloads. Learners explore CAS‑enabled programming, understand how data is accessed and loaded through caslibs, and learn best practices for optimizing code execution. The course also highlights SAS Viya’s multi‑language architecture, showing how SAS integrates with Python, R, SQL, and REST APIs to support flexible, collaborative workflows. By the end of the course, learners can confidently describe how SAS Viya executes code, accelerates analytics, and supports modern, scalable programming practices in real‑world analytics environments.
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This course introduces learners to the foundations of cloud analytics through the strategic partnership between SAS and Microsoft. Designed for learners who are new to cloud‑based analytics or exploring data and AI career pathways, the course explains why organizations are moving analytics to the cloud and how integrated platforms help transform data into decisions. Learners explore common challenges such as disconnected tools, siloed teams, and the need for faster, more trustworthy insights. The course highlights how SAS and Microsoft address these challenges through four key focus areas: seamless integration, analytics for everyone, enterprise‑grade security and flexibility, and deep expertise in analytics and cloud technologies. Through real‑world context and guided explanations, learners see how cloud platforms support collaboration across technical and nontechnical roles, enable responsible AI, and scale analytics from exploration to decisioning. This course provides the conceptual foundation needed to understand how Microsoft Azure and SAS Viya work together to support the complete data and AI life cycle, preparing learners for the hands‑on courses that follow in the specialization.