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Course Details
Course Details
What You'll Learn
This course prepares you for the INF-307 certification exam, covering all official exam domains:
Domain 1 AI Problem Definition
- Identify the problem to solve using AI (need, inputs/outputs, whether AI is warranted, measurable success)
- Classify the problem type (e.g., classification, regression, unsupervised, reinforcement) based on available data
- Identify areas of expertise needed (business, domain, AI, implementation)
- Build a security plan (access levels, infrastructure security, attack-surface/risk assessment)
- Ensure AI is used appropriately (guard against misprediction/harm, set data and algorithm-selection guidelines)
- Choose transparency and validation activities (communicate data-collection purpose, review legal/industry requirements)
Domain 2 Data Collection, Processing, and Engineering
- Choose data collection methods and determine whether an existing dataset can be used or a new one must be generated
- Assess data quality and ensure data are representative (check for missing/corrupt data and bias)
- Identify resource requirements (compute, time complexity, budget)
- Convert data into suitable formats and select/engineer features for the AI model
- Identify training and test datasets
- Document data decisions for transparency to regulators and end users
Domain 3 AI Algorithms and Models
- Evaluate applicability of specific algorithm families (e.g., neural network, decision tree, k-means) to the problem
- Train and tune a model, gathering performance metrics and iterating
- Select a specific model after experimentation while avoiding overengineering, considering cost/speed/explainability
- Evaluate model performance (accuracy, precision, overfitting/underfitting, cross-validation) and sensitivity/specificity
- Look for potential sources of bias in the algorithm and training data
- Confirm regulatory adherence and obtain stakeholder approval
Domain 4 Application Integration and Deployment
- Train customers on product use, limitations, and expectations; share documentation
- Plan to address potential challenges of models in production
- Design a production pipeline (training/prediction) and integrate the AI with the application
- Test accuracy, robustness, and speed of the AI through the application
- Support the AI solution (maintenance documentation, support team, feedback mechanism, drift detector)
Domain 5 Maintaining and Monitoring AI in Production
- Engage in oversight: log performance, monitor systems, act on alerts, watch for drift/degraded operation
- Assess business impact via key performance indicators, comparing pre/post-change metrics
- Measure impacts on individuals and communities; identify and mitigate subgroup issues
- Handle user feedback (satisfaction, confusion) and incorporate it into future versions
- Decide on a regular basis whether to retrain, continue using as-is, or decommission the AI
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 Specialist
- Machine Learning Engineer
- Data Scientist
- AI Solutions Architect
- AI Consultant
- AI Researcher
- Data Engineer
- Business Intelligence Analyst
- AI Project Manager
- AI Product Manager
- Automation Engineer
- IT Specialist (AI)
- Software Engineer (AI/ML)
- Cloud AI Engineer
- AI Ethics & Compliance Specialist
- AI Trainer & Educator
- Digital Transformation Manager
- AI Application Developer
- Big Data Analyst
- AI Policy Advisor
Trainers
Trainers
Saeid is co-founder of Skymics Sdn Bhd. He has 8 years of experience in the field of IoT (Internet of Things) and Information Technology. He is a certified IBM IoT Practitioner and instructor, and a Certified Citizen Data Scientist Train-The-Trainer. He has been co-inventor of 3 inventions during the last 4 years.
Review
Customer Reviews (6)
- Superb 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 21/06/2026)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 - Hands-on and practical 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 25/06/2025)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 satisfied Review by Course Participant/Trainee
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Very informative and interactive. The small class size meant we got a lot of personal attention. (Posted on 14/02/2025)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 - Fantastic experience Review by Course Participant/Trainee
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The training was very practical and hands-on. I could apply what I learned to my work immediately. (Posted on 12/05/2024)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 - Exceeded my expectations 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 07/03/2024)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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