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Course Details
Course Details
What You'll Learn
This course prepares you for the MLA-C01 certification exam, covering all official exam domains and their approximate weightings:
Domain 1 Domain 1: Data Preparation for Machine Learning (ML) (28%)
- Ingest and store data from AWS sources (S3, EFS, FSx) and streaming sources (Kinesis, Apache Flink/Kafka); choose data formats (Parquet, JSON, CSV, ORC, Avro, RecordIO)
- Transform data and perform feature engineering (cleaning, encoding, scaling/normalization, binning) using SageMaker Data Wrangler, AWS Glue/Glue DataBrew, Spark on EMR
- Create and manage features using SageMaker Feature Store; validate and label data using SageMaker Ground Truth / Mechanical Turk
- Ensure data integrity: identify and mitigate bias (class imbalance, DPL) using SageMaker Clarify
- Apply data classification, anonymization, masking and encryption for compliance (PII, PHI, data residency)
- Prepare data for modeling (splitting, shuffling, augmentation) and configure data loading into training resources (EFS, FSx)
Domain 2 Domain 2: ML Model Development (26%)
- Choose a modeling approach: assess feasibility, select ML algorithms/AI services (Bedrock, Rekognition, Translate, Transcribe), consider interpretability and cost
- Use SageMaker built-in algorithms, script mode (TensorFlow/PyTorch), and JumpStart/Bedrock foundation models for fine-tuning
- Train and refine models: hyperparameter tuning (SageMaker AMT), regularization (dropout, L1/L2), prevent overfitting/underfitting/catastrophic forgetting
- Combine models via ensembling, stacking, boosting; reduce model size via pruning/compression/quantized data types
- Manage model versions using SageMaker Model Registry for repeatability and audits
- Analyze model performance: select/interpret evaluation metrics (F1, precision/recall, RMSE, ROC/AUC), create baselines, detect bias and convergence issues via SageMaker Clarify/Model Debugger
Domain 3 Domain 3: Deployment and Orchestration of ML Workflows (22%)
- Select deployment infrastructure: real-time/serverless/asynchronous endpoints vs batch inference, compute provisioning (CPU/GPU), containers, edge optimization (SageMaker Neo)
- Choose deployment orchestrator and target (SageMaker Pipelines, Airflow, SageMaker endpoints, ECS/EKS, Lambda) and deployment strategy (real time vs batch, blue/green, canary, linear)
- Create and script infrastructure as code (CloudFormation, AWS CDK) including containerization (ECR, EKS, ECS, bring-your-own-container) and SageMaker endpoint auto scaling
- Configure SageMaker endpoints within a VPC and deploy/host models using the SageMaker SDK
- Set up CI/CD pipelines with AWS CodePipeline, CodeBuild, and CodeDeploy, integrated with Git-based version control
- Automate orchestration of training/inference jobs (EventBridge rules, SageMaker Pipelines) and build automated tests plus retraining mechanisms
Domain 4 Domain 4: ML Solution Monitoring, Maintenance, and Security (24%)
- Monitor model inference: detect data/model drift and anomalies using SageMaker Model Monitor and SageMaker Clarify; monitor performance via A/B testing
- Monitor and optimize infrastructure and costs using CloudWatch, X-Ray, CloudTrail, Cost Explorer, Trusted Advisor, and resource tagging strategies
- Rightsize instances and troubleshoot latency/scaling/capacity issues using SageMaker Inference Recommender and AWS Compute Optimizer
- Optimize infrastructure costs via purchasing options (Spot, On-Demand, Reserved Instances, SageMaker Savings Plans)
- Secure AWS resources: configure least-privilege IAM roles/policies for ML systems and applications, including SageMaker Role Manager
- Build VPCs, subnets, and security groups to isolate ML systems; monitor, audit, and log ML systems for continued security and compliance
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
- Machine Learning Engineer
- AI Solutions Architect
- Data Scientist
- Cloud AI Engineer
- AWS Machine Learning Specialist
- Deep Learning Engineer
- Data Analyst (Machine Learning Focus)
- AI Research Scientist
- Computer Vision Engineer
- Natural Language Processing Engineer
- AWS Data Engineer
- ML Operations Engineer
- Predictive Analytics Consultant
- Cloud Solutions Architect (ML Focus)
- Robotics Process Automation Engineer
- Model Deployment Engineer
- AI Product Manager
- Data Engineer (AI/ML Focus)
- Cloud Developer (Machine Learning)
- Technical Consultant (AI and ML)
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)
- Clear and easy to follow 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 10/15/2024)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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Excellent delivery and good balance between theory and practice. Learned a lot in a short time. (Posted on 8/8/2024)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 - Great learning experience Review by Course Participant/Trainee
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I found the course extremely useful and relevant to my job. Highly recommend it to others. (Posted on 6/28/2024)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 - Good course materials Review by Course Participant/Trainee
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I found the course extremely useful and relevant to my job. Highly recommend it to others. (Posted on 2/7/2024)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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