15 cloud tech courses you can take from Coursera, edX, and Udemy that are cheap or available for free for a limited time

This course will teach students methods for managing cloud computing projects and build an understanding of the various risks and compliance issues involved. Students who enroll are also eligible for $25 in Amazon Web Services (AWS) promotional credit to cover the cost of the hands-on labs.

It's recommended that students complete Cloud Computing for Enterprises prior to enrolling. It's also part of the edX Cloud Computing MicroMasters program. You can learn more about MicroMasters here.

Altogether, the course should take eight weeks to complete.

This introductory course teaches the fundamentals of building and managing cloud technologies directly from The Linux Foundation, the non-profit that supports open-source projects and ecosystems.

Students will master the basics of cloud computing from terminology to tools and technologies used in popular contemporary cloud platforms.

Altogether, the course should take students 14 weeks to complete.

This introductory machine learning course is a starting place for non-technical business professionals. Learn to formulate machine learning solutions to real-world problems, identify whether the data you have is sufficient for ML, be familiar with ML use cases, perform AI responsibly and avoid reinforcing an existing bias, and bring a project through various ML phases including training, evaluation, and deployment.

You'll need a desktop web browser to run this course's interactive labs via Qwiklabs and Google Cloud Platform.

Altogether, it should take 12 hours to complete.

This Google course covers the entire Industrial IoT network architecture ranging from sensors and devices to analysis — though the emphasis is on the cloud side.

You'll learn about the importance of scaling, device communication, and processing streaming data. The course labs use simulated devices so you concentrate on learning the cloud side of IIoT. It should take students about 15 hours to complete.

Unlike many Coursera courses, this one has little video. Most of the learning is done with short readings, quizzes, and labs.

This beginner-level course provides a deep dive into how to create a chatbot using Dialogflow, augment it with Cloud Natural Language API, and operationalize it using Google Cloud tools.

It should take about eight hours to complete.

This course introduces AWS professionals to the core capabilities of Google Cloud Platform (GCP) in the four technology pillars: networking, compute, storage, and database.

The class is designed specifically for AWS Solution Architects and SysOps Administrators familiar with AWS features and setup who are looking to gain experience in configuring GCP products quickly.

This accelerated course should only take students about 13 hours to complete.

This course provides an overview of Computer Vision (CV), Machine Learning (ML) with Amazon Web Services (AWS), and how to build and train a CV model using the Apache MXNet and GluonCV toolkit.

Students will explore artificial neural networks and other deep learning concepts, and walk through how to combine neural network building blocks into complete computer vision models and train them.

It should take students about 29 hours to complete.

This is an introduction to cloud identity for identity/access management/mobile device management admins who are tasked with managing and establishing security and access management best practices for their organization.

It should take students 15-30 hours to complete.

Students will be introduced to artificial intelligence and machine learning, and work with Azure APIs, including those for vision, language, and search.

They'll create, train, test and deploy an AI model in the cloud; learn to describe AI tools and roles, and the Microsoft Team Data Science Process.

It should take students about 16 hours to complete.

In this course, students will learn the operational functions of Internet technologies, including IPv4, IPv6, TCP, UDP, addressing, routing, domain names, and more, specifically about their own PC/laptop's security and gateway Internet setup and basic principles.

In a simple Wireshark experiment, students will also see the TCP/IP packets and security systems in action that are serving their PC/laptop and thereby them.

It should take students approximately five hours to complete.

Students will learn the basics of cloud computing in this Cloud 101 course, including what it is, what it supports, and how it's delivered.

Students will pay attention to storage services, Cloud economics, levels of managed infrastructure, and Azure services.

This course should take students approximately nine hours to complete.

This course teaches students how to get started with AWS Machine Learning, including key problems that ML can address and help solve.

Students will learn how to build intelligent applications using Amazon AI services as well as how to build, train, and deploy a model using Amazon SageMaker with built-in algorithms and Jupyter Notebook instance.

It should take students about eight hours to complete.

This course aims to build a complete understanding of Amazon Web Services Networking from scratch in seven hours. The course is split up into two sections, the first emphasizing understanding AWS Networking, and the second uses hands-on exercises to teach AWS Networking — from the basics to more advanced processes.

This class teaches students the basics of Cloud Computing and how to prepare for the CompTIA Cloud+ Certification Exam.

It's recommended to have at least 24–36 months of work experience in IT networking, network storage, or datacenter administration for this course.

Learn the fundamentals of cloud computing including the types of cloud, cloud platforms, models, concepts, and considerations for moving an application from traditional IT to Cloud.