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Course Details
Course Details
What You'll Learn
Topic 1: AI-Assisted Network Threat and Vulnerability Analysis
Topic 2: AI-Powered Network Risk Assessment and Management Planning
Topic 3: Designing and Implementing AI-Enhanced Network Security Measures
Topic 4: AI-Assisted Security Incident Documentation and Response
Course Info
Minimum Entry Requirement
Knowledge and Skills
- Able to operate using computer functions
- Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
- Positive Learning Attitude
- Enthusiastic Learner
Experience
- Minimum of 1 year of working experience.
Target Age Group: 21-65 years old
Minimum Software/Hardware Requirement
Software:
You can download and install the following software:
- Nmap
- Wireshark (with tshark)
- Python 3 with pandas and scikit-learn
- A generative AI assistant (Claude, ChatGPT or Copilot — the free tier is sufficient)
- A spreadsheet (Excel, Numbers or Google Sheets)
Hardware: Windows or Mac laptop with administrator rights to install software
Job Roles
Job Roles
- IT Security Specialist
- Network Administrator
- Cybersecurity Analyst
- Network Security Engineer
- Risk Management Consultant
- Systems Administrator
- Penetration Tester
- IT Infrastructure Specialist
- Security Compliance Officer
- Incident Response Analyst
- Information Security Consultant
- Cybersecurity Auditor
- SOC (Security Operations Center) Analyst
- Ethical Hacker
- Technical Support Engineer
- IT Project Manager (Cybersecurity)
- Vulnerability Analyst
- Wireless Network Engineer
- Security Operations Specialist
- Cloud Security Specialist
Trainers
Trainers
Network defence today means making sense of more traffic, logs and alerts than any team can read, and Dr. Alfred Ang approaches the problem as an engineer who builds and runs AI systems himself. He holds a PhD in Electrical Engineering from NUS, an MSc in Electrical and Electronic Engineering from NTU and a B.Sc (Hons) in Physics from NUS, and his earlier career in the defence, electronics and semiconductor industries produced more than 20 peer-reviewed papers and more than 20 US patents as co-inventor. Today he is a full-stack AI developer and Agentic AI solution architect whose work covers cloud-native platforms on AWS and Kubernetes, DevOps, security, observability and performance optimisation, and he is Managing Director, CIO, CTO and Chief Instructional Designer of Tertiary Infotech Academy Pte Ltd and the founder of Tertiary Courses. His relevant certifications include CompTIA Security+, AWS Certified Solutions Architect and Cloud Practitioner, Microsoft Certified AI Engineer Associate (AI-102) and ITIL. Among the more than 300 public repositories on his GitHub, tertiarytraining runs Docker-based Kali Linux and Ubuntu labs in the browser with role-based access, OAuth and idle auto-shutdown; wifispeedapp measures download, upload, ping and jitter using parallel streams; and itsupport demonstrates a credential-leak guard and a strict Content Security Policy in a service desk front end. He also leads digital transformation initiatives that move organisations from AI experimentation to operational AI, where protecting those systems is part of the design.
In AI for Network Security, Dr. Ang shows network and system administrators, security analysts, IT managers and engineers how AI can lighten the load without replacing their judgement. The course starts with AI-assisted network threat and vulnerability analysis, where learners use AI tools to read traffic patterns and logs, spot anomalies and suspicious behaviour, and interpret vulnerability scan results in plain language. It then moves to AI-powered network risk assessment and management planning, prioritising risks by likelihood and impact and drafting a defensible plan. The third topic covers designing and implementing AI-enhanced network security measures, such as refining detection rules, hardening configurations and deciding where automation can respond safely. The course closes with AI-assisted security incident documentation and response, using generative AI to produce clear timelines, incident reports and lessons-learned summaries. Throughout, he applies the habits he uses in his own infrastructure work: verify what the AI tells you, keep sensitive logs out of public models, and treat every automated action as something that must be auditable. He also explains how attackers are adopting the same tools, so learners understand both sides of the contest. As an ACTA-certified trainer and DACE-certified curriculum developer, he balances concepts with guided hands-on exercises, so participants leave able to apply AI-assisted analysis to their own network data with confidence. Learners also discuss which network data can safely be shared with cloud AI services and which must stay on-premises. To see the infrastructure and security projects he builds, view his GitHub portfolio at https://github.com/alfredang and connect with him on LinkedIn at https://www.linkedin.com/in/angchewhoe/
Angel Koh has over 15 years of experience in the maritime and defence industry, where he has built information systems for full-scale development programmes. He specialises in data fusion and mapping, and has worked with a wide range of programming and computing languages and tools, including C#, Java, Octave and ArcGIS. He is passionate about adopting new technologies and skills to expand his computing knowledge, and outside work he enjoys tinkering with his RigidBot 3D printer, building household objects with Adobe 123D Design and OpenSCAD. His defence-sector systems background gives him a practical understanding of complex, data-driven information systems.
In AI for Network Security, Angel helps learners apply artificial intelligence to protecting an organisation's network. Participants use AI to analyse network threats and vulnerabilities, carry out AI-powered network risk assessment and management planning, design and implement AI-enhanced network security measures, and document and respond to security incidents with AI assistance. His data fusion background is useful when learners consider how AI correlates large volumes of alerts, logs and vulnerability data into a clearer picture. Participants leave able to use AI to support defenders facing growing volumes of security information, while applying sound judgement to its findings.
Review
Customer Reviews (39)
- will recommend Review by Course Participant/Trainee
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. (Posted on 2/17/2025)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 - will recommend Review by Course Participant/Trainee
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maybe more examples for advanced java (Posted on 6/26/2022)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 - might recommend Review by Course Participant/Trainee
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Improve the projector (Posted on 6/26/2022)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 - might recommend Review by Course Participant/Trainee
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Instead of covering basics and algorithms, can focus more on training how to develop a real time website/application using Java platform (Posted on 2/8/2022)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 - might recomemnd Review by Course Participant/Trainee
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Double confirm on the content of the course (Posted on 2/8/2022)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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