AWS Certified Machine Learning Specialty Training

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

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:

• 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.