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Course Details
Course Details
What You'll Learn
This course prepares you for the AIF-C01 certification exam, covering all official exam domains and their approximate weightings:
Domain 1 Domain 1: Fundamentals of AI and ML (20%)
- Explain basic AI/ML terminology (AI, ML, deep learning, neural networks, NLP, LLM, GenAI, agentic AI) and differentiate AI, ML, GenAI, deep learning, and agentic AI
- Describe types of AI/ML learning (supervised, unsupervised, reinforcement) and types of data/inferencing (batch, real-time, labeled/unlabeled, etc.)
- Identify practical AI/ML use cases, select appropriate techniques (regression, classification, clustering), and recognize when AI/ML is NOT appropriate
- Explain capabilities of AWS managed AI/ML services (Amazon SageMaker AI, Transcribe, Translate, Comprehend, Lex, Polly)
- Describe the AI/ML development lifecycle/pipeline and MLOps fundamentals (experimentation, monitoring, retraining, production readiness)
- Describe model performance metrics (accuracy, precision, recall, F1 score) and business metrics (cost per user, ROI) to evaluate ML models
Domain 2 Domain 2: Fundamentals of GenAI (24%)
- Define foundational GenAI concepts (tokens, chunking, embeddings, vectors, prompt engineering, transformer-based LLMs, foundation models, diffusion models)
- Identify GenAI use cases (image/video/audio generation, summarization, AI assistants, code generation, customer service agents)
- Describe the foundation model (FM) lifecycle: data selection, model selection, pre-training, fine-tuning, evaluation, deployment, feedback
- Understand capabilities and limitations of GenAI for business problems (hallucinations, interpretability, nondeterminism) and model selection factors
- Describe AWS infrastructure/services for building GenAI applications (Amazon Bedrock, SageMaker AI/JumpStart, Strands Agents, Bedrock AgentCore)
- Describe the token-based pricing model and cost tradeoffs of AWS GenAI services
Domain 3 Domain 3: Applications of Foundation Models (28%)
- Identify FM selection criteria (cost, modality, latency, model size, customization) and the effect of inference parameters (e.g. temperature)
- Define Retrieval Augmented Generation (RAG) and identify AWS vector database services (Amazon OpenSearch Service, Aurora, Neptune, RDS for PostgreSQL)
- Choose effective prompt engineering techniques (chain-of-thought, zero-shot, few-shot, prompt templates) and recognize risks (prompt injection, jailbreaking, hijacking)
- Describe FM training and fine-tuning methods (instruction tuning, transfer learning, continuous pre-training, RLHF) and data preparation practices
- Describe methods/metrics to evaluate FM performance (ROUGE, BLEU, BERTScore, LLM-as-a-judge, benchmark datasets, human-in-the-loop)
- Identify approaches to evaluate FM-based applications (RAG, agents, workflows) against business objective alignment metrics
Domain 4 Domain 4: Guidelines for Responsible AI (14%)
- Identify features of responsible AI: bias, fairness, inclusivity, robustness, safety, veracity
- Explain tools to identify/monitor bias, trustworthiness, and truthfulness (Amazon SageMaker Clarify, SageMaker Model Monitor, Amazon A2I, Bedrock Guardrails)
- Identify legal and ethical risks of working with GenAI (IP infringement claims, biased model outputs, hallucinations, loss of customer trust)
- Recognize the importance of transparent and explainable models and related tools (SageMaker Model Cards, Bedrock Model Evaluations)
- Describe tradeoffs between model safety and transparency, and principles of human-centered design for explainable AI
Domain 5 Domain 5: Security, Compliance, and Governance for AI Solutions (14%)
- Identify AWS services/features to secure AI systems (IAM roles/policies, encryption, Amazon Macie, AWS PrivateLink, Bedrock Guardrails, Bedrock AgentCore Identity)
- Describe security and privacy considerations for AI systems (prompt injection, data leakage prevention, output filtering/validation, audit trail and logging)
- Describe hallucination detection methods and grounding techniques (RAG grounding, output validation, confidence scoring)
- Identify AWS services for governance and regulation compliance (AWS Config, Amazon Inspector, AWS Audit Manager, AWS Artifact, AWS CloudTrail, Trusted Advisor)
- Describe data governance strategies (data lifecycles, residency, retention, monitoring) and governance frameworks (e.g. Generative AI Security Scoping Matrix)
Course Info
Promotion Code
Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.
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: 18-65 years old
Minimum Software/Hardware Requirement
Software:
TBD
Hardware: Window or Mac Laptops
Job Roles
Job Roles
- AI Engineer
- Machine Learning Engineer
- Data Scientist
- Cloud Solutions Architect
- AI Solutions Architect
- Data Analyst
- AWS Cloud Practitioner
- AI Consultant
- Machine Learning Specialist
- AI Research Scientist
- Cloud Developer
- Data Engineer
- AI Product Manager
- Software Developer
- IT Consultant
- Technical Support Engineer
- Business Intelligence Developer
- AI System Developer
- Cloud Infrastructure Engineer
- Technology Analyst
Trainers
Trainers
is an accomplished IT and data specialist with over 20 years of experience in academia, ICT leadership, and professional training, with a strong focus on data analytics and Excel-based solutions. He has developed and delivered specialized training programs on Statistical Data Analysis with Excel and Visual Basic for Applications (VBA) for Excel, equipping learners with advanced data manipulation, automation, and reporting skills. His expertise extends to automating institutional reporting systems, where he successfully streamlined academic records management through Excel-based tools, integrating macros and automation to improve efficiency and accuracy. As a trainer and consultant, Dr. Siraj has taught Excel to diverse audiences, including university staff, administrative teams, and professionals in banking, security, and education, ensuring they can apply Excel for decision-making, statistical modeling, and process automation. His practical mastery of Excel is complemented by his deep knowledge of office automation and ICT project management, making him a highly sought-after trainer in data analysis and productivity tools. With his blend of hands-on technical expertise and instructional experience, Dr. Siraj stands out as a credible authority in leveraging Excel to drive organizational efficiency and data-driven strategies
Review
Customer Reviews (8)
- Great practical training Review by Course Participant/Trainee
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Really enjoyed the training. The examples were relevant and the pace was just right. (Posted on 5/11/2026)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 - Fantastic experience Review by Course Participant/Trainee
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The trainer is an expert in the subject and shared many practical insights from real projects. (Posted on 5/10/2026)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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The course materials were detailed and easy to reference afterwards. Great value for money. (Posted on 3/20/2026)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 - Learned a lot 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 2/18/2026)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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Very engaging session. The trainer patiently answered all our questions and gave useful tips. (Posted on 8/27/2024)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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