Cloud: Platform as a Service - Bachelor's (Coursera)

Offered by Illinois Tech,
Cloud: Platform as a Service - Bachelor's (Coursera)

This course is aimed at preparing individuals to gain knowledge, skills, and abilities to demonstrate the knowledge for managing Platform as a Service (PaaS) in the Cloud. Students will learn to deploy, operate, and maintain cloud platforms for storing, processing, and transferring information with architecture design principles and a structured approach. Students will also learn the shared responsibility model and cloud security best practices to secure PaaS platforms for the application-hosting environments.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

What you'll learn
To create, deploy, operate, and communicate the strategies and operational considerations to deploy and manage cloud-based technology platforms.

Syllabus

Module 1: Introduction to Platform as a Service (PaaS)
Welcome to Introduction to Platform as a Service (PaaS)! In Module 1, we will define the PaaS and differentiate it from all other cloud services. We will also define scope and boundaries of platform as a service which will guide us for topics covered in rest of the modules of the course. The benefits of using PaaS and recognize the limitations are discussed in this module. Students will also compare, contrast, and understand the best fit for PaaS to help make informed decisions for selecting appropriate cloud implementation strategy. Students will explore various PaaS offerings from various vendors for making the best choice decisions for solving business problems. Finally, students will explore several ways to manage PaaS offering.

Module 2: Containers and Containerization Services Platform
In this module we will explore and understand the concepts related to containerization. We will compare containers with virtual machines and learn the benefits of using containers in cloud environments. Building blocks and innerworkings of container infrastructure will be explored. Furthermore, we will compare the benefits and limitations of various containerization strategies for effective decision making. To experience containerization operation, we will also create and run a container using Docker on AWS and discuss advanced concepts for containerization management. Finally, we will discuss operational management challenges and discuss effective release and deployment strategies.

Module 3: Serverless Computing Platforms
In this module we will explore and understand the challenges with containerization and applicability of serverless and microservices approaches. We will discuss the benefits and limitations of using Serverless Computing Platforms in cloud environments. We will further explore the building blocks and innerworkings of Serverless Infrastructure. Furthermore, we will discuss the process of developing and deploying Serverless Solutions. To experience Serverless Platform operation, we will also create a Serverless Platform and run a Serverless Function on AWS Lambda. Finally, we will discuss advanced concepts for effective and efficient operating and management of Serverless Computing Environment.

Module 4: Information Management Platforms as a Service
This module delves into the complexities and solutions for managing databases in the cloud platform for handling and processing large datasets, with the focus on design consideration and implementation of scalable DBMS Platform. Through the series of lessons, students will explore challenges and considerations associated with handling large datasets and learn how Platform as a Service can facilitate the storage and processing of data with built-in scalability and high availability features. Students will gain insights into relational and non-relational database use cases and selection criteria for advanced functionality based on the needs.

Module 5: Development and Deployment Management Platforms
This module provides a comprehensive exploration of DevOps principles and practices within the context of Platform as a Service (PaaS). Starting with the basics of Development and Deployment concepts and approaches. Students will learn about the methodologies and cultural philosophies that drive efficient application development and deployment. The module then delves into the advantages of adopting a DevOps culture and how PaaS can streamline and enhance the DevOps lifecycle, from continuous integration to continuous delivery. Finally, Students will learn about API and API management methods in the cloud. By understanding the architecture of development and deployment pipelines facilitated by PaaS providers, students will be equipped to design and implement efficient, scalable, and reliable software delivery processes.

Module 6: Machine Learning Platforms
This module serves as a comprehensive guide to understanding and applying machine learning (ML) concepts, processes, and platforms. Starting with the basics of artificial intelligence and machine learning, students will learn how prediction and decision-making algorithms are implemented in the cloud platforms as a service. Additionally, students will become familiarized with commonly used machine learning platforms and learn how to deploy, operate, and optimize ML models effectively. By covering the challenges and limitations of machine learning, this module aims to equip learners with the skills needed to navigate the ML landscape confidently. Whether for forecasting, recognition systems, or decision-making processes, students will leave with a solid foundation in managing and implementing machine learning solutions across various applications.

Module 7: Security Services Platforms
This module introduces students to the critical concepts of cloud security, emphasizing the shared responsibility model that delineates the security obligations of cloud providers and users. Learners will explore common threats and vulnerabilities specific to cloud environments and analyze the security features and controls offered by Platform as a Service (PaaS) solutions. This module culminates with practical lessons on architecting and implementing robust security measures for IAM, Network and Data security using Security as a Platform (SaaP). Finally, students will also learn about Audit and security Monitoring Platforms empowering students to design comprehensive security solutions for cloud-based systems.

Module 8: Designing and Implementing Cloud Platforms for High Level of Operational Maturity
This module focuses on the principles and practices necessary for creating cloud platforms that exhibit high reliability, scalability, operational maturity, and content delivery. Beginning with architecting auto-scaling solutions, students will learn to enhance application performance dynamically. The module progresses to cover high-availability and load balancing methods for various computing and data management platforms ensuring that students are equipped with best known methods for implementing high-performing scalable and reliable cloud platforms. A critical look at cost-effectiveness teaches strategies for efficient cloud resource utilization. Lastly, the module anticipates the future of Platform as a Service (PaaS) by exploring its secured content delivery network platforms preparing students to adapt to and capitalize on emerging trends in cloud platform development.

Summative Course Assessment
This module contains the summative course assessment that has been designed to evaluate your understanding of the course material and assess your ability to apply the knowledge you have acquired throughout the course.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Machine Learning Algorithms (Coursera) Coursera
Sungkyunkwan University - SKKU

Machine Learning Algorithms (Coursera)

In this course you will: understand the naïve Bayesian algorithm; understand the Support Vector Machine algorithm; understand the Decision Tree algorithm; understand the Clustering. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability.

Aug 3rd 2026
4 Weeks
Machine Learning and Human Learning (Coursera) Coursera
University of Illinois at Urbana-Champaign

Machine Learning and Human Learning (Coursera)

This course examines the differences between machine and human learning and the ways in which machines can complement human learning. It examines technical definitions of supervised and unsupervised machine learning, as well as broader views of mechanical intelligence able to replicate or exceed human intelligence.

Aug 3rd 2026
4 Weeks
Machine Learning (Coursera) Coursera
Stanford University

Machine Learning (Coursera)

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

Jul 27th 2026
5-12 Weeks
Machine Learning in Retail (Coursera) Coursera
Coursera Project Network

Machine Learning in Retail (Coursera)

Who are your customers? What are they like? How do they interact with your business? This Short Course was created to help analysts better understand their customer behaviour through the power of machine learning. In this course, you will apply two different machine learning techniques to segment customers according to their purchasing behaviour and provide actionable insights for each group. Along the way, you'll also examine some other retail case studies, including web visitor analysis for marketing and store clustering for logistics.

Aug 3rd 2026
1 Week
Getting Started with Machine Learning at the Edge on Arm (Coursera) Coursera
Arm

Getting Started with Machine Learning at the Edge on Arm (Coursera)

The age of machine learning has arrived! Arm technology is powering a new generation of connected devices with sophisticated sensors that can collect a vast range of environmental, spatial and audio/visual data. Typically this data is processed in the cloud using advanced machine learning tools that are enabling new applications reshaping the way we work, travel, live and play.

Aug 3rd 2026
5-12 Weeks
Cloud: Platform as a Service - Master's (Coursera) Coursera
Illinois Tech

Cloud: Platform as a Service - Master's (Coursera)

This course is aimed at preparing individuals to gain knowledge, skills, and abilities to demonstrate the knowledge for managing Platform as a Service (PaaS) in the Cloud. Students will learn to deploy, operate, and maintain cloud platforms for storing, processing, and transferring information with architecture design principles and a structured approach. Students will also learn the shared responsibility model and cloud security best practices to secure PaaS platforms for the application-hosting environments.

Aug 3rd 2026
5-12 Weeks
Remote Sensing Image Acquisition, Analysis and Applications (Coursera) Coursera
UNSW Sydney - University of New South Wales

Remote Sensing Image Acquisition, Analysis and Applications (Coursera)

Welcome to Remote Sensing Image Acquisition, Analysis and Applications, in which we explore the nature of imaging the earth's surface from space or from airborne vehicles. This course covers the fundamental nature of remote sensing and the platforms and sensor types used. It also provides an in-depth treatment of the computational algorithms employed in image understanding, ranging from the earliest historically important techniques to more recent approaches based on deep learning.

Aug 17th 2026
13-24 Weeks
Machine Learning Basics (Coursera) Coursera
Sungkyunkwan University - SKKU

Machine Learning Basics (Coursera)

In this course, you will: understand the basic concepts of machine learning; understand a typical memory-based method, the K nearest neighbor method; understand linear regression; understand model analysis. Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability.

Aug 3rd 2026
4 Weeks
AI Materials (Coursera) Coursera
Korea Advanced Institute of Science and Technology - KAIST

AI Materials (Coursera)

Learn about the materials that have advanced the performance of artificial intelligence, and the machine learning models that could help accelerate the design and development of novel materials. This course defines artificial intelligence (AI) as a machine to which some or all of the functions of the human brain have been delegated. It highlights the need, and explains in an easy-to-understand way how machine learning from artificial intelligence can dramatically accelerate the development of new materials.

Aug 10th 2026
5-12 Weeks
Google Cloud Product Fundamentals en Español (Coursera) Coursera
Google Cloud

Google Cloud Product Fundamentals en Español (Coursera)

Este curso, que es una continuación de Business Transformation with Google Cloud, le permitirá conocer la perspectiva tecnológica de la transformación de una organización. Para ser más específicos, explicaremos cómo la tecnología de Google Cloud puede transformar digitalmente una organización en los siguientes aspectos: modernizar la infraestructura de TI; mejorar la forma en que los equipos desarrollan las aplicaciones que utiliza la empresa; saber cómo aprovechar el aprendizaje automático y la inteligencia artificial para generar más valor; advertir el rol fundamental de las herramientas de productividad basadas en la nube, como G Suite, para cumplir con el trabajo, y comprender los desafíos y las oportunidades de la administración de costos que trae aparejados una infraestructura de TI cambiante basada en la nube.

Aug 3rd 2026
5-12 Weeks