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Google Professional Machine Learning Engineer Training

Course Information

  • Sessions 2 days
  • Duration 15 hrs
  • Level Advanced
  • Assessment NA

Venue

Kuala Lumpur: G-3A-02, Corporate Office Suite, KL Gateway, No. 2, Jalan Kerinchi, Gerbang Kerinchi Lestari, 59200 Kuala Lumpur, Malaysia

Course Brochure

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Prerequisite

You should complete Claude Certified Architect - Foundations (CCAR-F) Exam Prep (C437) before taking this course.

C437 covers the architecture foundations – agentic architecture, tool design and MCP integration, Claude Code configuration, structured output and reliability – that this course extends to governing production Claude systems at enterprise scale.

Certification

By end of the course, learners should be able to:

  • LO1: Identify AI ethics and governance principles.
  • LO2: Apply AI ethics and governance framework on AI projects.

Claude Certified Architect - Professional (CCAR-P) Exam Prep

Course Code: C740

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What's This Course About

Claude Certified Architect - Professional (CCAR-P) Exam Prep prepares you for the Claude Certified Architect - Professional exam from Anthropic, the advanced architect credential in the Claude certification programme. It validates that you can turn business problems into scalable, production-grade Claude solutions, choosing the right models, architectural patterns and API approaches, and building evaluation, security, compliance and governance into the design. The certification is intended for experienced solution architects, AI engineers and technical leads who design and deliver Claude-powered systems for real organisations.

The course follows the seven official exam domains and gives each one the time its exam weighting deserves. You will start with solution design and architecture, translating business requirements into end-to-end designs and choosing between workflow-based, agentic, augmented LLM and multi-agent patterns. You will then cover Claude models, prompting and context engineering, including model trade-offs, system prompts, guardrails, prompt caching and Skills, followed by integration, the most heavily weighted domain, covering RAG pipelines, MCP, APIs, agent-to-agent communication, least-privilege tool access and observability.

The course continues with evaluation, testing and optimisation, governance, safety and risk management, including human-in-the-loop controls and regulatory obligations such as GDPR and HIPAA, and stakeholder communication and lifecycle management, and closes with developer productivity and operational enablement with Claude Code. Each domain combines explanation, architecture case studies, hands-on labs and exam-style scenario questions. The CCAR-P exam has 63 multiple-choice and multiple-response questions in 120 minutes, delivered by Pearson VUE online or at a test centre, with a passing scaled score of 720 out of 1,000. As a member of the Claude Partner Network, Tertiary Infotech Academy aligns this course with Anthropic's official exam guide. By the end, you will be able to architect production Claude solutions with confidence and be well prepared to pass the exam.

Bonus: Free Practice Exams

Get exam-ready on our Practice Exam Portal — train in realistic Practice Mode and timed Exam Mode, then retake them as many times as you like before the real exam.

Start Practising →

Why Take This Course?

  • Hands-On Learning Learn by doing. Every topic is practised hands-on, so you leave with skills you can use at work straight away.
  • Live Coaching Experienced instructors coach you live, answer your questions and guide you step by step.
  • Free Post-Course Consultation Stuck after class? Message your trainer any time for guidance as you apply what you have learned.
  • Always-Updated Materials Materials are refreshed to stay relevant. Log in to our LMS any time to get the latest version.
HRD Corp Claimable

🏦 HRD Corp Claimable

This course is HRD Corp claimable for eligible employers. Grant approval and reimbursement remain subject to HRD Corp requirements, the employer’s available levy and the approved grant details. How the HRD Corp process works →

Course Fee

MYR6,000.00
+ 8% SST

Course Date

Course Time

Course fees are shown before SST. An 8% SST is included in the estimated total during registration.

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Disclaimer: The course dates displayed on our website are tentative and subject to trainer availability. We will confirm the final date after checking with the trainer. You are also welcome to email us your preferred date at sales@tertiarycourses.com.my, and we will do our best to coordinate with the trainer's schedule.

Post-Course Support

  • We may provide consultation related to the subject matter after the course.
  • Please email your queries to sales@tertiarycourses.com.my and we will forward your queries to the subject matter experts and get back to you as soon as possible.

Cancellation & Reschedule Policy

  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% to participants.
  • Note: the venue of the training is subject to changes due to class size and availability of the classroom. The minimum class size to start a class is 3 Pax.

Course Details

Course Details

What You'll Learn

Topic 1: Solution Design and Architecture

Topic 2: Claude Models, Prompting, and Context Engineering

Topic 3: Integration

Topic 4: Evaluation, Testing, and Optimisation

Topic 5: Governance, Safety, and Risk Management

Topic 6: Stakeholder Communication and Lifecycle Management

Topic 7: Developer Productivity and Operational Enablement

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)
  • Experience designing or building LLM-powered applications, with working knowledge of Python or TypeScript and REST APIs

Attitude

  • Positive Learning Attitude
  • Enthusiastic Learner

Experience

  • Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

You will need the following for this course:

Hardware: Windows PC or Mac laptop

How to Apply HRD Corp Funding

This course is HRD Corp claimable for employers registered with HRD Corp, under the HRD Corp Claimable Courses scheme (SBL-Khas). Your company applies for the grant before the class; we submit the training provider claim after it.

  1. Check your levy balance - your company must be registered with HRD Corp and have enough levy balance to cover the course fee.
  2. Request a quotation - contact us for the quotation, course content and trainer profile; you attach these to the grant application.
  3. Apply for the grant in eTRiS before the class - log in to your employer eTRiS account, go to Application > Grant > Apply Grant, choose the scheme HRD Corp Claimable Courses (SBL-Khas), select us as the training provider and this course, add your trainees, attach the quotation, course content and trainer profile, and submit.
  4. Submit in time - for public classes, submit at least 3 calendar days before the class (15 June to 31 December 2026) and at least 14 days before from 1 January 2027; in-house classes need 14 days. The training must start within 90 days of that advance submission period.
  5. Send us the grant approval - once HRD Corp approves the application, email us the grant ID so we can confirm your seats.
  6. Attend the class - trainees sign the daily attendance (T3) form.
  7. Claim after the class - we submit the training provider claim in eTRiS with the attendance and invoice; you then complete the employer claim and sign the JD/14 form (manager level or above). Claims must be submitted within 6 months of the training.

More details: our HRD Corp Claimable Courses page and the HRD Corp employer guidelines.

Job Roles

Job Roles

  • AI Solutions Architect
  • Solutions Architect
  • Enterprise Architect
  • Technical Architect
  • Cloud Architect
  • AI Engineer
  • Senior Software Engineer
  • Machine Learning Engineer
  • Generative AI Lead
  • Forward Deployed Engineer
  • Solutions Engineer
  • Platform Engineer
  • Technical Lead
  • Engineering Manager
  • AI Consultant
  • AI Product Manager
  • AI Governance Lead
  • Head of AI

Trainers

Trainers

Dr. Alfred Ang approaches machine learning engineering from the perspective of someone who has to put models and AI services into products people actually use. A full-stack AI developer, Agentic AI solution architect, corporate trainer and CTO of Tertiary Infotech Academy Pte Ltd in Singapore, Dr. Ang builds intelligent agents and scalable solutions end-to-end across front end, back end, databases, cloud deployment and native mobile apps, with more than 300 public repositories on GitHub. Google technology appears throughout that portfolio. The n8n-ragdemo project feeds uploaded PDFs into a vector store and answers questions through a Telegram AI agent powered by Google Gemini, while a bakery training lead-magnet site uses an n8n and Gemini chatbot to compare context-stuffing with retrieval. The logomaker app generates logos with Gemini image models, and native Android apps use Google Maps and on-device ML Kit features such as document edge detection, optical character recognition and background removal. For core machine learning, data-mining-ml-labs provides interactive Python and Streamlit labs covering data preparation, feature selection and model training for beginners, and n8n-inventorycontrol runs a demand-forecasting agent on Google's open Gemma model served locally through Ollama. Dr. Ang also built ai-exams, a full-stack certification practice-exam platform with timed exam modes and AI-assisted question generation, reflecting a strong interest in how professionals prepare for cloud certifications. This combination of practical deployment and exam-preparation experience gives Dr. Ang a clear view of what the certification expects.

Google Professional Machine Learning Engineer Training uses that practical grounding to make a broad syllabus manageable. The course moves through Google Cloud big data and machine learning fundamentals, how Google does machine learning, launching into machine learning, TensorFlow on Google Cloud, feature engineering, machine learning in the enterprise, and production machine learning systems. Dr. Ang links each area to decisions an engineer actually faces: choosing between pre-built APIs, AutoML and custom training, designing data pipelines that will not leak information into evaluation, selecting and engineering features, tuning and validating models, and serving, monitoring and retraining them on Vertex AI once they are live. Responsible AI, fairness and explainability are treated as design requirements rather than afterthoughts. Learners work through demonstrations, guided notebooks and scenario-based questions in the style of the certification exam, and Dr. Ang explains why each wrong option fails, which tends to be where real understanding forms. Examples from deploying Gemini-based chatbots and on-device ML features help illustrate trade-offs between accuracy, latency, cost and maintainability that the exam likes to test. The course suits data scientists, ML engineers, developers and cloud practitioners preparing for the certification, ideally with some Python and basic statistics. Learners who would like to explore the machine learning labs and Gemini projects mentioned during the course can visit Dr. A structured revision plan and guidance on official practice resources help learners continue preparing confidently after the course. Ang's portfolio at https://github.com/alfredang.

Review

Customer Reviews (9)

Hands-on and practical Review by Course Participant/Trainee
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 course materials and well-paced lessons. The exercises really helped me understand the topic. (Posted on 05/09/2024)
Clear and easy to follow Review by Course Participant/Trainee
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
Excellent delivery and good balance between theory and practice. Learned a lot in a short time. (Posted on 16/07/2024)
Learned a lot Review by Course Participant/Trainee
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
Well organised course with clear objectives. The step-by-step approach made it easy to follow. (Posted on 11/02/2024)
Worth every cent Review by Course Participant/Trainee
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
The training was very practical and hands-on. I could apply what I learned to my work immediately. (Posted on 05/01/2024)

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