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Course Details
Course Details
What You'll Learn
Topic 1: Design and Implement an MLOps Infrastructure
Topic 2: Implement Machine Learning Model Lifecycle and Operations
Topic 3: Design and Implement a GenAIOps Infrastructure
Topic 4: Implement Generative AI Quality Assurance and Observability
Topic 5: Optimize Generative AI Systems and Model Performance
Course Info
Prerequisite
Participants should already understand basic cloud computing and the relevant data, application or security concepts. Review the fundamentals before attending this course.
Software Requirement
Install and test the listed software before class. Confirm the required version and account or licence access in your joining instructions. Cloud and AI services may charge subscription or usage fees.
Hardware Requirement
Bring a Windows or Mac laptop supported by the listed software, with a working keyboard and sufficient storage for course exercises.
Bring your own computer and charger, with a reliable internet connection and permission to install the required software. For live online classes, also prepare a microphone or headset.
If you need help arranging a suitable device, contact us before the class to confirm availability.
Job Roles
Job Roles
- Dynamics 365 Business Central Developer
- ERP Developer
- Business Systems Consultant
- Dynamics 365 Administrator
- Systems Integration Specialist
- Power Apps Developer
- Power Automate Specialist
- ERP Implementation Consultant
- Financial Systems Analyst
- Warehouse Management Specialist
- Supply Chain Management Specialist
- IT Project Manager
- Data Analyst for Business Central
- Business Intelligence Developer
- Reporting Specialist
- Dynamics 365 Functional Consultant
- Procurement and Inventory Specialist
- Business Process Automation Specialist
- Dynamics 365 Security Administrator
- Technical Support Engineer
Trainers
Trainers
Dr. Muhammed Siraj is a cybersecurity specialist and academic with 15 years of experience, serving as Senior Lecturer in the Department of Informatics and Director of Graduate and Continuous Education at Academic City University in Accra. He holds a PhD in Security in Computing from Universiti Putra Malaysia, where his research focused on blockchain security, an MSc in Information and Communication Technology from Aalborg University in Denmark, and a degree from the University of Ghana. He is a licensed independent assessor with Ghana's Cyber Security Authority, holds leadership roles in national cybersecurity and privacy professional bodies, and is certified as a Certified Ethical Hacker (CEH), Computer Hacking Forensic Investigator (CHFI) and Certified Data Protection Supervisor (CDPS). Before joining Academic City, he served as Acting Director of ICT and Data Protection Supervisor at Wisconsin International University College. His expertise spans penetration testing, digital forensics, incident response, malware analysis, cryptography, cloud and IoT security, zero trust architecture, cyber threat intelligence, data protection, and governance, risk and compliance.
Dr. Siraj's research interests cover blockchain, cybersecurity, distributed computing, consensus protocols and machine learning, with published work on blockchain consensus security, smart-contract privacy preservation for sensitive records in the cloud, and new consensus mechanisms. This background gives him a distinctive perspective on artificial intelligence: as organisations adopt AI tools, agents and data-driven automation, he helps learners understand how to protect the data these systems depend on, recognise new attack surfaces, and put sound governance, privacy and access controls in place so that AI can be used safely and responsibly. In the classroom he connects technical practice with regulation, privacy and human factors, drawing on real-world security and data-protection cases to show how concepts apply in professional settings, and his experiential, hands-on teaching style has made him a trusted trainer for students and working professionals alike.
Machine learning operations is where models meet the realities of production, and Dr. Alfred Ang spends a great deal of time on exactly that boundary. Dr. Ang is a full-stack AI developer, Agentic AI solution architect, corporate trainer and CTO of Tertiary Infotech Academy Pte Ltd in Singapore, building intelligent agents and scalable EdTech and business systems end-to-end across front end, back end, databases, cloud deployment and native mobile apps. The public portfolio on GitHub runs to more than 300 repositories. Dr. Ang operates ai-mms, the containerised course-registration platform that runs the Tertiary Courses sites in Singapore, Malaysia and Ghana from a single codebase, with automated builds, database migrations and deployment on every release, which makes versioning, rollback and monitoring a daily concern rather than a theory. On the model side, data-mining-ml-labs offers interactive Python and Streamlit labs covering the machine learning lifecycle for beginners, and n8n-inventorycontrol runs a forecasting agent on a local large language model served through Ollama. Generative AI systems feature heavily as well: retrieval-augmented chatbots built with n8n, a voice-cloned avatar grounded in an organisation's own content, and ai-exams, a certification practice-exam platform that uses AI-assisted question generation and therefore needs careful quality checks on every output. Dr. Ang has also built a tool for searching Microsoft Learn course content, keeping close to the official learning paths. This mix of infrastructure, model and generative work mirrors the scope of the modern MLOps engineer role that the certification is designed to validate.
The AI-300 Microsoft Certified Machine Learning Operations Engineer Associate Exam Prep course benefits directly from that operational background. Dr. Ang works through all five exam areas: designing and implementing an MLOps infrastructure, implementing the machine learning model lifecycle and operations, designing and implementing a GenAIOps infrastructure, implementing generative AI quality assurance and observability, and optimising generative AI systems and model performance. For each one, the official concepts on Azure Machine Learning and related services are linked to concrete situations, such as why a deployment pipeline needs automated tests, how to track experiments and model versions, what to log when a generative application starts to drift, and how to evaluate groundedness and safety before release. Learners practise with guided demonstrations and exam-style questions, and Dr. Ang explains not only which answer is correct but why the other options would cause trouble in a real deployment. Cost, latency and reliability trade-offs receive particular attention, because they are the issues that surface first once real users arrive. The class suits data scientists, ML engineers, DevOps practitioners and developers who want a structured path to the certification along with skills they can apply at work. Participants are encouraged to bring questions from their own projects for discussion. To explore the deployment, retrieval and evaluation projects referenced in class, visit Dr. Practical tips on study planning and on navigating Microsoft Learn resources help participants continue preparing efficiently after the class ends. Ang's portfolio at https://github.com/alfredang.
Review
Customer Reviews (6)
- Fantastic experience Review by Course Participant/Trainee
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Great course materials and well-paced lessons. The exercises really helped me understand the topic. (Posted on 6/22/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Great practical training Review by Course Participant/Trainee
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Solid content and a supportive trainer. I would definitely sign up for more courses here. (Posted on 4/8/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Knowledgeable trainer Review by Course Participant/Trainee
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I found the course extremely useful and relevant to my job. Highly recommend it to others. (Posted on 12/4/2025)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Great learning experience Review by Course Participant/Trainee
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A very practical course. The trainer made a complex topic simple and enjoyable to learn. (Posted on 11/17/2024)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Practical and relevant Review by Course Participant/Trainee
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The trainer was knowledgeable and explained the concepts clearly with real-world examples. (Posted on 10/12/2024)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
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