Cloud Computing and Security Essentials

Eight weeksUp to six hours per week

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Online course with hands-on lab activities

$995.00 + applicable taxesView available early bird and alumni discounts

Cloud computing is transforming the IT landscape, offering unparalleled opportunities for innovation and scalability as well as new challenges in ensuring robust security and reliable infrastructure. As organizations migrate to cloud environments, the demand for skilled cloud security professionals continues to grow.

Developed by faculty from the Cheriton School of Computer Science at the University of Waterloo and a senior cybersecurity specialist working in the industry, this course equips you with foundational knowledge of modern cloud infrastructure, along with practical, hands-on activities in a simulated environment.

Designed for early to mid-career professionals in the software industry interested in upskilling in cloud cybersecurity, this eight-week course will provide you with the technical skills and competencies needed for designing and deploying cloud infrastructure in today’s market while increasing your awareness and resiliency in digital security.

You’ll gain foundational knowledge of cloud infrastructure and hands-on experience in cloud security through weekly labs and real-world scenarios. The curriculum covers key topics including virtualization, networking, and application management, before diving into cloud-specific cybersecurity tools and techniques.

Through practical labs, you will explore how to deploy and secure cloud environments, from using cryptographic keys and firewalls to managing identity and access control. By the end of the course, you will have the technical knowledge and practical experience needed to confidently design and secure cloud systems, positioning yourself as a valuable asset in the rapidly evolving IT industry.

NEW: Enhanced virtual labs with guided validation

Get detailed feedback as you complete hands-on cloud computing and security exercises. Instead of a simple pass or fail result, the lab environment shows which steps are complete and which still need attention, so you can quickly identify what to fix and keep progressing.

It’s the same kind of feedback loop you’ll find on modern DevOps and cloud platforms, helping you build real-world troubleshooting skills as you learn. In technical work, understanding why something didn’t work is often just as valuable as getting it right.

Explain the key concepts of cloud computing infrastructure and its use cases.
Discuss the design and management of cloud solutions, including storage, networks, and applications.
Deploy a range of cloud instances and services, including web services, cloud storage instances, and networks.
Identify common threats to cloud environments and strategies to increase security.
Secure cloud data, networks, and applications using a variety of tools and techniques.

Module Title	Main Topics / Learning Outcomes
Module 1: Introduction to Cloud Infrastructure	Overview of cloud computing Roles and interactions in cloud computing Cloud service models Regulation and governance
Module 2: Virtualization	Virtualization in the cloud Server virtualization Virtual machines and containers
Module 3: Cloud Storage	Cloud storage Cloud storage management Storage tiers
Module 4: Networking	Networking and network protocols Building modern networks (OSI and TCP/IP models) Network virtualization Network devices
Module 5: Application Management in the Cloud	Business requirements analysis Cloud administration Application migration Backup in the cloud Disaster recovery
Module 6: Cybersecurity	Cybersecurity and cloud security Dimensions of security Data privacy Threat models Introduction to cryptography
Module 7: Data and Network Security	Securing data in the cloud Confidentiality Securing cloud networks Incident response Cloud security operations
Module 8: Cloud Application Security	Secure software development life cycle Secure operations Identity and access management (IAM) IAM standards and operations

This course is ideal for early and mid-career IT professionals and engineers:

Aspiring Cloud and Security Specialists: Individuals looking to understand cloud technologies and security to take the first step toward roles in cloud security.
Current Cloud and Security Specialists: Individuals seeking a refresher in the basics of designing secure, cost-effective cloud architectures for their projects or clients, with hands-on practice and expert feedback.
Software Developers and Data Engineers: Those looking to leverage cloud platforms for scalable application development or data storage solutions.
Mid-Level Managers and Decision-Makers: Professionals responsible for overseeing IT infrastructure and ensuring secure cloud implementations.

Prerequisites

There is no specific prerequisite education or work experience needed.
A working literacy of computing devices, operating systems, and the internet will help in this course.

Learn alongside your team!

WatSPEED provides custom learning experiences tailored for large groups from any single organization. Register three or more employees from the same organization and receive 15 per cent off. Contact our team at watspeed@uwaterloo.ca for details.

Practical lab-based learning: Apply concepts in a virtual lab environment with guided tasks simulating real-world scenarios.
NEW: Guided validation feedback: See which lab steps are complete and which still need attention, so you can troubleshoot and keep progressing with confidence.
Comprehensive curriculum: Cover the design and deployment of cloud infrastructure, followed by essential cloud security tools and techniques.
Expert support: Access a live orientation session, weekly drop-in Q&A sessions, and active instructor participation in discussion forums.
Flexible learning experience: Progress through content at your own pace while supported by live sessions.
No prerequisites: Start your cloud security journey without needing prior experience or specialized knowledge. A working literacy of computing devices, operating systems, and the internet will help in this course.

System requirements

Learners will use an online platform to complete the hands-on labs.
No software installation is required for this course.

Receive a certificate from the University of Waterloo

Upon successful completion of this course, you will receive a professional education certificate from the University of Waterloo.

Headshot of Samer Al-Kiswany

Samer Al-Kiswany

Associate Professor, David R. Cheriton School of Computer Science, University of Waterloo | Course Author

Samer Al-Kiswany is an Associate Professor at the David R. Cheriton School of Computer Science at the University of Waterloo, Canada. His research interests are in cloud, distributed systems, networking, and data management and processing engines. In particular, his work focuses on reconsidering systems design in light of recent changes in cloud applications and platforms. Samer received his PhD from the University of British Columbia in 2013 under the supervision of Matei Ripeanu. After earning his PhD, he joined the University of Wisconsin–Madison as a postdoctoral fellow working with Remzi and Andrea Arpaci-Dusseau.

Samer has diverse industry experience. He was the Research Lead for Next Generation Networking at Acronis Research Labs and a research intern at Microsoft Azure, IBM Almaden Research Center, NEC, and Argonne National Lab. Samer is the recipient of ten national and international awards, including the Killam Doctoral Fellowship and the NSERC Postdoctoral Fellowship.

Headshot of Emin Mammadov

Emin Mammadov

Senior Software Engineer, Geotab | Course Instructor

Emin Mammadov is a Senior Software Engineer on the AI Platform team at Geotab, where he designs and manages large-scale ML infrastructure on Google Cloud Platform (GCP). His work spans building scalable compute platforms, deploying AI systems, and enabling teams to move efficiently from experimentation to production. He holds a Master of Applied Science in Electrical Engineering from the University of Waterloo, where he also served as a Teaching Assistant, leading tutorial sessions and supporting students through office hours.

Mammadov has also worked as a data science mentor and part-time instructor at Lighthouse Labs, teaching machine learning, linear algebra, statistics, and cloud computing to multiple bootcamp cohorts.