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This program prepares you to design, deploy and manage modern cloud?based and AI?enabled systems that meet real?world business and organizational needs. The program emphasizes the technologies, architecture and security practices required to build scalable, resilient and ethically responsible digital solutions.

The Cloud Computing and Artificial Intelligence Infrastructure program is a one-year (two semesters) post-graduate certificate program offered full time.

When you enter the program, you are expected to have foundational digital literacy skills gained through an undergraduate degree in information and communication technology. This post-graduate certificate expands your knowledge from conducting online research, collaborating online and practising responsible digital behaviour to developing advanced competencies in cloud infrastructure, AI services, system modernization and secure digital operations.

You will study cloud computing in the following areas:

• Business continuity planning, disaster recovery and resilience engineering.
• Design and evaluation of cloud-based solutions that optimize resources and reduce operational costs. 
• Design of hybrid, scalable, highly available and fault-tolerant cloud architectures.
• Implementation of continuous integration, continuous delivery and automated cloud workflows.
• Migration of on?premises infrastructure, databases and applications to cloud environments.
• Monitoring, auditing and cost?optimization strategies for cloud workloads.
• Principles of the DevOps culture, including shared responsibility, collaboration and continuous improvement.
• Provision and management of cloud computing, storage and networking services.
• Security of cloud-based systems using zero-trust principles and shared responsibility models.

You will also be trained in the following: 

• Core concepts of AI infrastructure, cloud AI platforms and deployment pipelines.
• Fundamentals of decentralized systems that reduce reliance on central authorities.
• Secure design of cloud-based data engineering pipelines and AI data services.
• Implementation and maintenance of cloud-based AI services, including monitoring, model integration and API?based workflows.
• Integration of AI models, data services, and cloud applications to support intelligent, secure and ethical automation.
• Security and governance of AI systems, including data protection, responsible AI and emerging AI regulatory frameworks.