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

Practice Exam

Prerequisite

This is an intermediate course. the following basic knowledge is assumed

• R Programming
• Bioinformatics

Software Requirement

Pls download and install the following software prior to the class

• R https://cran.r-project.org/
• R Studio https://www.rstudio.com/products/rstudio/download/

HRDF Funding

Please refer to this video https://youtu.be/Kzpd-V1F9Xs

1-     HRD Corp Grant Helper

How to submit grant applications for HRD Corp Claimable Courses

2-     Employers are required to apply for the grant at least one week before training commences.

Employers must submit their applications with supporting documents, including invoices/quotations, trainer profiles, training schedule and course content.

3-     First, Login to Employer’s e-TRIS account -https://etris.hrdcorp.gov.my

Second, Click Application

4-     Click Grant on the left side under Applications

5-     Click Apply Grant on the left side under Applications

6-     Click Apply

7-     Choose a Scheme Code and select HRD Corp Claimable Courses: Skim Bantuan Latihan Khas. Then, click Apply

8-     Scheme Code represents all types of training that suit the requirements provided by HRD Corp. Below are the list of schemes offered by HRD Corp:

9-     Select your Immediate Officer and click Next

10-  Select a Training Provider, then click Next

11-  Please select a training programme from the list, then key in all the required details and click Next

Select your desired training programme.

Give an explanation on why the participant is required to attend the training. E.g., related to their tasks/ career development, etc.

Explain the background and objective of this training.

Select a relevant focus area. For Employer-Specific Courses, select ‘Not Applicable’.

12-  If the training programme is a micro-credential programme, you are required to complete these 3 fields. Save and click Next

Insert MiCAS Application number

13-  Based on the nine (9) pillars listed below, HRD Corp Focus Area Courses are closely tied to support government initiatives towards nation building. As such, courses offered through the HRD Corp Focus Areas are designed to provide the workforce with skills required for current and future demands. Details of the focus areas are as follows:

14-  Please select a Course Title and Type of Training

15-  Select the correct type of training according to the actual type of training, or as mentioned in the training brochure:

16-  Please key in the Training Location and click Next

17-  Please select the Level of Certification and click Next

18-  Please follow the instructions and key in trainee details

19-  Click Add Batch, then click Save

20-  Click Add Trainee Details

21-  Please key in all the required details, then click Add

22-  Click Add if there are more participants. Once done, click Save

23-  Click Next

24-  Please key in the course fees and allowance details, then click Save

25-  Estimated cost includes the course fees/external trainer fees, allowances, and consumable training materials. Please comply with the HRD Corp Allowable Cost Matrix.

26-  Select Upfront Payment to Training Provider and key in the percentage from 0% to 30%. Then, click Save and Next

27-  Complete the declaration form and select a desired officer

28-  Add all the required documents, then click Add Attachment. Then, click Save and Submit Application

29-  Once the New Grant Application is successfully submitted, the Grant Officer will evaluate the application accordingly. The application may be queried if additional information is required.

The application status will be updated via the employer’s dashboard, email, and the e-TRiS inbox.

• 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

Ghazaleh Babanejad: Ghazaleh Babanejad has received her Ph.D from University Putra Malaysia in Faculty of Computer ‎Science and Information Technology. She is working on recommender systems in the ‎ the field of skyline queries over Dynamic and Incomplete databases for her Ph.D. thesis. She is also working ‎ on the Data Science field as a trainer and Data Scientist. She worked on Machine Learning and Process ‎ Mining projects. She also has several international certificates in Practical Machine Learning (John ‎ Hopkins University) Mining Massive Datasets (Stanford University), Process Mining (Eindhoven ‎ University), Hadoop (University of San Diego), MongoDB for DBAs (MongoDB Inc) and some other ‎ certificates. She has more than 5 years of experience as a lecturer and database administrator.

Mostafa: Mostafa has more than 5 years’ experience in teaching mathematics and statistics. His main teaching interests are statistical topics such as descriptive analysis and basic data modeling, regression analysis, design of experiment, non-parametric methods, and statistical software such as SAS, R, SPSS, and Minitab. He has started computer programming using visual basics and C++ around 15 years ago, and he has more than 10 years’ experience in programming using R.

Juv Chan: Juv Chan is a Senior Developer of Azure Marketplace and Product Engineering at Sitecore, Malaysia. He is an expert in cloud computing. He was recognized as Microsoft Most Valuable Professional (MVP) in the Microsoft Azure category in 2016 and 2017. He achieved the Grand Prize Winner in Developer Category of Microsoft Influencer Hero Competition 2015 Regional (Asia Pacific). In Angelhack Kuala Lumpur 2016, the largest angel hack hackathon in 2016 globally, he achieved 2nd Prize Winner in the Big Data Analytics Challenge as the team leads. He was a Top 3% Contributor (Azure tags) on StackOverflow in 2016.