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Course Details
Course Details
What You'll Learn
Topic 1: Identifying Business Innovation Opportunities with Agentic AI and AI Agents
Topic 2: Designing Digital Architectures and AI Agent Implementation Plans
Topic 3: Managing AI-Driven Innovation, Governance and Stakeholder Collaboration
Course Info
Prerequisite
Participants should already understand basic cloud computing, networking and the relevant data or application discipline. 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
- Innovation Manager
- Product Development Manager
- R&D Specialist
- Business Strategist
- Digital Transformation Lead
- AI Solutions Architect
- Design Thinking Facilitator
- Marketing Innovation Specialist
- Brand Experience Designer
- Creative Director
- New Ventures Manager
- Content Strategy Specialist
- UX/UI Designer (exploring AI-driven design)
- Growth Hacker
- Technology Evangelist
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 in production is about far more than training a model, and Dr. Alfred Ang approaches this certification from the engineering side of that equation. Dr. Ang is a full-stack AI developer, Agentic AI solution architect and corporate trainer, and the CTO of Tertiary Infotech Academy Pte Ltd in Singapore, the training organisation behind Tertiary Courses, building intelligent agents and business systems end-to-end across front end, back end, databases, cloud deployment and native mobile apps. More than 300 public repositories on GitHub document the work. The portfolio does not include projects built specifically on Google Cloud's managed machine learning services, and Dr. Ang is open about that; the relevant experience lies in the adjacent skills the exam rewards. Interactive Python and Streamlit labs teach data mining and machine learning step by step. Gemini models power several builds, including a Telegram agent that answers questions from uploaded documents, a course chatbot on n8n, a logo maker using Gemini image generation, and a digital-human service trained on a brand's own content through retrieval. An inventory forecasting agent runs on a local language model, a deliberate trade-off of cost, latency and data privacy that mirrors the choices the exam asks about. Native mobile apps run vision models on the device for text recognition and background removal. On the operations side, Dr. Ang packages and deploys applications with Docker and automated pipelines, and maintains the course-registration platform that serves the Tertiary Courses sites in Singapore, Malaysia and Ghana.
This preparation course is structured around the official exam domains and their weightings. In architecting low-code AI solutions, learners build models with BigQuery ML and AutoML for classification, regression, forecasting and clustering, engineer features and generate predictions in BigQuery ML, fine-tune Gemini models, select models from Model Garden, build applications on industry APIs such as Document AI, Vision and Translate, and optimise Gemini-based applications for cost, latency and availability. The data and model collaboration domain covers organising tabular, text and image data, choosing preprocessing tools from BigQuery SQL, Dataflow and Apache Spark to in-memory Python frameworks, building and consolidating features in a feature store while protecting personal data, prototyping in Workbench or Colab Enterprise notebooks with PyTorch, scikit-learn and JAX, and choosing the right environment for experiments and pipelines, including Kubeflow Pipelines. The remaining domains on scaling, serving, automating and monitoring models are covered with the same rigour. Dr. Ang connects each objective to a practical decision, such as when a managed service beats a self-hosted model or why personal data must be handled before features are shared, and works through scenario-based practice questions in detail, explaining why each distractor is wrong. Learners are encouraged to sketch architectures for their own use cases and test them against the exam objectives. Data scientists and engineers leave with a clear map of the exam and a stronger instinct for production trade-offs. To see the machine learning labs and AI projects that inform this course, visit Dr. Ang's portfolio at https://github.com/alfredang
Review
Customer Reviews (9)
- Worth every cent Review by Course Participant/Trainee
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Very engaging session. The trainer patiently answered all our questions and gave useful tips. (Posted on 5/24/2026)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 - Very informative 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 4/10/2025)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 practical training 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 3/26/2025)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 - Very useful course 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 10/16/2024)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 - Highly recommended Review by Course Participant/Trainee
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Very engaging session. The trainer patiently answered all our questions and gave useful tips. (Posted on 9/10/2024)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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