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Course Details
Course Details
What You'll Learn
This course prepares you for the N/A certification exam, covering all official exam domains and their approximate weightings:
Domain 1 Architecting low-code AI solutions (13%)
- Build models in BigQuery ML or Gemini Enterprise Agent Platform AutoML (classification, regression, forecasting, clustering) based on the business problem
- Perform feature engineering/selection using BigQuery ML; generate predictions using BigQuery ML
- Train models using Agent Platform AutoML; fine-tune Gemini models using BigQuery
- Evaluate and select the appropriate model from Agent Platform Model Garden for a given task
- Build applications using industry-specific APIs (Document AI, Vision, Translate) and tune models for specific use cases (Gemini, Imagen, Veo)
- Optimize Gemini-based applications for cost, latency, and availability
Domain 2 Collaborating within and across teams to manage data and models (16%)
- Organize and explore tabular, text, and image data for efficient experimenting, training, and serving
- Choose the right preprocessing tool by scale/complexity (BigQuery SQL, Dataflow, Apache Spark, in-memory Python frameworks)
- Create/consolidate features in Agent Platform Feature Store; ensure data privacy and handle PII
- Prototype models in Agent Platform Workbench or Colab Enterprise notebooks using PyTorch, sklearn, JAX and Model Garden models
- Choose the right environment for experimentation (Experiments on Agent Platform, Agent Platform Pipelines, Kubeflow Pipelines)
- Evaluate predictive and gen AI solutions (metrics, LLM-as-a-judge) and track model artifacts/versions/lineage
Domain 3 Scaling prototypes into ML models (21%)
- Choose model type (ARIMA, DNN, LLM), product (AutoML, BigQuery ML, Pipelines), deployment strategy, and modeling technique given interpretability needs
- Organize and ingest structured/unstructured training data (Cloud Storage, BigQuery) into training pipelines
- Train models via different SDKs (Agent Platform custom training, Kubeflow on GKE, AutoML, Tabular Workflows)
- Troubleshoot ML model training failures and perform hyperparameter tuning
- Fine-tune foundational models from Agent Platform/Model Garden and judge when tuning is warranted
- Evaluate compute/accelerator options (CPU, GPU, TPU) and distributed training strategies (data/model parallelism)
Domain 4 Serving and scaling models (20%)
- Deploy models for batch and online inference (Agent Platform, Model Garden, Cloud Run, GKE)
- Package/serve models from different frameworks (PyTorch, XGBoost) using prebuilt/custom containers
- Organize and version models in Gemini Enterprise Agent Platform Model Registry
- Implement rollout strategies (A/B testing, canary deployments) and inference pre/postprocessing
- Manage and serve features via Agent Platform Feature Store; deploy to public/private endpoints
- Choose appropriate serving hardware (CPU/GPU/TPU/edge) and scale serving backend based on throughput
Domain 5 Automating and orchestrating ML pipelines (18%)
- Validate data and models within end-to-end ML pipelines
- Build and orchestrate pipelines using managed/unmanaged services or templates (Agent Platform Pipelines, Managed Service for Apache Airflow, Ray on Agent Platform)
- Ensure consistent data preprocessing between training and serving
- Determine an appropriate model retraining policy
- Deploy models in CI/CD/CT pipelines (e.g., Cloud Build)
Domain 6 Monitoring AI solutions (13%)
- Build secure AI systems against data/model exfiltration, malicious prompting, and sensitive-data leakage to LLMs (Regex, safety filters, Model Armor)
- Align with responsible AI practices, including monitoring for bias
- Provide model explainability on Agent Platform (e.g., Agent Platform Inference)
- Configure Model Monitoring on Gemini Enterprise Agent Platform for continuous evaluation metrics
- Monitor for training-serving skew, data drift, concept drift, and feature attribution drift
- Monitor, test, and evaluate gen AI solutions
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
- Data Scientist
- Machine Learning Engineer
- AI Engineer
- Data Analyst
- Software Engineer
- Cloud Solutions Architect
- Research Scientist
- Application Developer
- Big Data Engineer
- Business Intelligence Developer
- Robotics Engineer
- Quantitative Analyst
- Systems Analyst
- Product Manager
- Technical Program Manager
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 (9)
- Fantastic experience 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 5/17/2024)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 - Worth every cent 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 4/10/2024)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 - Very informative 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 2/27/2024)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 - Clear and easy to follow 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 1/2/2024)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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