AWS Certified Machine Learning Specialty MLS-C01 Exam Prep

1. Introduction to Machine Learning on AWS

• Overview of Machine Learning (ML)
• Introduction to AWS Machine Learning Services
• Exam Structure and Preparation Tips

2. Data Engineering

• Data Collection and Integration
• Data Cleaning and Preparation
• Data Storage Solutions on AWS (S3, RDS, Redshift)
• Data Pipeline Design using AWS Glue and AWS Data Pipeline

3. Exploratory Data Analysis (EDA)

• Data Visualization Techniques
• Statistical Analysis and Summarization
• Feature Engineering and Selection
• Tools for EDA (AWS QuickSight, Jupyter Notebooks)

4. Modeling

• Supervised Learning Algorithms (Regression, Classification)
• Unsupervised Learning Algorithms (Clustering, Dimensionality Reduction)
• Deep Learning (Neural Networks, CNNs, RNNs)
• Model Evaluation and Validation Techniques

5. Machine Learning Implementation and Operations

• Model Deployment using AWS SageMaker
• Automating Model Training and Deployment with SageMaker Pipelines
• Real-Time Inference and Batch Inference
• Monitoring and Troubleshooting Models in Production

6. Security and Monitoring

• Security Best Practices for Machine Learning
• Data Privacy and Protection
• Monitoring and Logging Machine Learning Workflows
• Auditing and Compliance

7. Specialized Topics

• Natural Language Processing (NLP) with AWS Comprehend
• Computer Vision with AWS Rekognition
• Anomaly Detection using AWS SageMaker
• Recommendation Systems

8. Case Studies and Practical Applications

• Case Studies on AWS Machine Learning Implementations
• Hands-on Labs and Projects
• Best Practices for Industrial Applications

9. Exam Preparation

• Practice Questions and Mock Exams
• Time Management Strategies
• Review of Key Concepts and Common Pitfalls
• Q&A and Discussion Sessions

Practice Exam

Promotion Code

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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:

• Git Lab

Hardware: Window or Mac Laptops

• Machine Learning Engineer
• Data Scientist
• AI/ML Specialist
• Cloud Solutions Architect
• Data Engineer
• AWS Solutions Architect
• Research Scientist
• AI Developer
• Big Data Engineer
• Analytics Engineer
• Cloud Engineer
• DevOps Engineer
• Data Analyst
• Software Engineer
• Business Intelligence Developer
• IT Consultant
• System Architect
• Application Developer
• Technical Consultant
• Product Manager in AI/ML

Quah Chee Yong: Quah Chee Yong is a ACTA certified trainer. Quah Chee Yong Chee Yong is an experienced professional who has held various Technical, Operations and Commercial positions across several industriesA firm believer that AI can create a better world, he has equipped himself with the Knowledge and Skills in the fields of Data Science, Machine Learning, Deep Learning and Cloud Deployment

He has a deep passion for training & facilitating and is currently a Singapore WSQ certified Adult Educator. He particularly enjoys the interactive engagements with his fellow trainers and learners

Agus Salim: Agus Salim is a professional with more than 10 years of experience in Project Management, IT Solutions Management, and Systems Integration both in waterfall and agile methodology. He started out his career as a Web Developer before moving on to Business Analyst/Project Manager. He has strong leadership and the capability of leading a team with a proven ability to deliver projects with tight timelines. Besides his experiences in managing projects, he has good knowledge in Cybersecurity and hands-on experience in Next Generation Firewall such as Check Point. During his free time, he likes to explore Cloud Technology, especially on Microsoft Azure. Agus has obtained AZ-104, AZ-500 and other Microsoft certifications. I am also a ALCP certified trainer.

Anil Bidari: Anil  is a ACLP certified trainer. He is an Enterprise Cloud and DevOps Consultant , responsible for  helping clients to move Virtual data centre to Private Cloud based on OpenStack and Public Cloud ( AWS, Azure and Google cloud) . Consulting and training experience on Devops tool chain like github , Jenkins, Sonarqube, Docker & kubernetes, Cloud foundry, Openshift, Ansible and SaltStack. Lot of my Role is involved design and implementation of a solution and training

Peter Cheong :  Peter is a ACLP certied trainer. Specialise In IT related knowlege and conduct IT Training which Include Microsoft Window Server Technology (Wintel) and Linux - Centos/Red Hat. Comptia ,ITIL , Motorola Solution Trunking System and Cisco Networking. I was worked in Motorola Solutions Conduct Motorola Astro 25 Trunking System For Police Force Malaysia (RMPnet),Taiwan Navy, Indonesia METRO POLDA (Police Force). After that Peter Join As IT Group Manager For W-Group which include 17 subsidiaries Companies in Real Estate Developer,Plantation, Building Management Services ,Contruction and also Fiber Opti Service Provider in Sabah,Malaysia.

Ben Law Beng Tjin: Ben is an experienced IT Infrastructure professional with more than 20 years of working experience in IT sector. Due to Corporate Digital Transformation and COVID-19 during early 2020 he shifted his focus to Cloud Computing specialized in Cloud Infrastructure Solutioning. He is  an AWS Certified Solution Architect Associate, Google Certified Cloud Engineer, Microsoft Certified Azure Fundamentals and Alibaba Cloud Associate.