I'm an international student in Australia studying for a bachelor's degree in IT, and I need to choose my major next semester. One option is a combined Cloud Engineering and IoT major. I'm genuinely interested in the field, but I'm unsure whether it's a sensible choice given the current job market and rapid developments in AI.
I've completed the AZ-900 certification and considered taking AZ-104, but stopped after hearing that cloud certifications may not be useful. I'm now uncertain whether certifications are worth pursuing and whether this major would actually improve my employment prospects. I've applied for many jobs and internships without success, so I'd also like advice on how to build a stronger profile while I'm still studying.
Cybersecurity is another possible major, but as an international student I'm concerned that many internships and entry-level roles may require security clearance. If I choose cloud computing, I would appreciate a practical roadmap covering certifications, projects, scripting, networking, identity, and the kinds of experience employers expect. There are many conflicting roadmaps online, so I'm hoping to hear from people who work in cloud, IoT, or related areas. I'm especially interested in knowing whether Cloud Engineering and IoT is a worthwhile direction, how AI may affect these careers, and what I should do next after AZ-900.
4 Answers
Certifications are useful early in your career, but they are not a substitute for practical experience. AZ-900 is a good introduction, while AZ-104 is much more focused on real Azure administration, including networking, identity, storage, compute, monitoring, and access control. If cloud genuinely interests you, it can be a sensible next step rather than something to abandon because of general online advice.
Try to build projects while studying instead of only preparing for the exam. Create virtual networks and subnets, deploy VMs, configure NSGs and Entra ID/RBAC, use storage and Key Vault, set up monitoring, experiment with private endpoints, and deliberately troubleshoot things when they break. Add scripting and automation as you go. That combination of a certification, demonstrable projects, and some work experience is much stronger than any one of those alone.
Cloud and cybersecurity also overlap significantly. Cloud security and identity-focused roles could remain options later, even if some government or defence positions are unavailable because of clearance requirements. Private-sector security jobs do not all require clearance.
At this stage, certifications can help get your application noticed and give an interviewer a way to assess your baseline knowledge. They also provide structured learning and show that you can follow through on a technical goal. They will not guarantee an interview or job, though, so try to connect every certification to something you have built or administered.
The IoT side may involve services such as messaging, queues, event processing, and integration, so learning some development concepts could be useful alongside administration skills. Depending on the role, an application-development-oriented Azure certification may be relevant too. If you later move toward AI, the same principle applies: learn the underlying cloud and engineering fundamentals rather than collecting credentials without practical experience.
Look at several real job postings for the roles you would want after graduation. Check whether they mention AZ-104, other certifications, scripting, networking, support experience, or particular cloud services. That will give you a more reliable direction than following a generic roadmap and will show you which skills employers in your area actually value.
You do not need a perfect five-year roadmap before starting. If you enjoy cloud engineering and IoT, choosing that major is reasonable. A practical sequence would be to strengthen networking and Linux fundamentals, continue with AZ-104 if the exam objectives match your target jobs, build two or three documented Azure projects, learn PowerShell or Python, and apply for support, systems administration, cloud operations, and junior infrastructure roles—not only jobs with “cloud engineer” in the title.
AI may change the tools people use, but companies will still need people who understand infrastructure, identity, networking, reliability, security, and how to operate systems in production. Focus on those fundamentals and use AI as a productivity tool rather than treating it as a reason to avoid the field.

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