AWS Certified Machine Learning - Specialty
ML training, evaluation, feature engineering, data analysis, visualization, deployment, hyperparameter optimization, and AWS security for building ML solutions.
Course Fee
S$2000
Up to 70% funding available
Course Information
What you'll learn
- Data Repositories & Management
- ML Model Training & Evaluation
- Feature Engineering & Data Analysis
- ML Solution Deployment & Operationalization
- Data Preparation & Hyperparameter Optimization
- ML Problem Framing & AWS Integration
Requirements
- Basic ML Proficiency: Intuition & Hyperparameter Optimization
- ML Pipeline Understanding: Components & Frameworks
- Model Training & Deployment Experience
Description
Title
AWS Certified Machine Learning-Specialty
Foundational Concepts in Machine Learning and Data Management
This comprehensive program covers various essential aspects of Machine Learning (ML) and equips participants with the skills and knowledge necessary to build and deploy ML solutions effectively. Participants will begin by understanding the significance of data repositories in ML and learn how to access and manage data from various sources. They will then delve into the process of data preparation, including sanitization and transformation, to ensure data quality and suitability for modeling.
ML Pipeline: Training, Evaluation, and Model Selection
The program will extensively cover the ML pipeline, guiding participants through the steps of model training and evaluation. Attendees will learn how to select the most appropriate model(s) for specific ML problems and gain experience in performing hyperparameter optimization to fine-tune their models for optimal performance. Additionally, participants will explore featuring engineering techniques to extract relevant information from data and frame business problems as ML challenges, identifying solutions for data-ingestion and data-transformation.
Deploying and Operationalizing ML Solutions with AWS
A key aspect of the program is understanding the deployment and operationalization of ML solutions. Participants will be equipped with the knowledge to deploy ML models effectively and ensure performance, availability, scalability, resiliency, and fault tolerance. They will learn to apply basic AWS security practices to ML solutions, safeguarding data and ensuring compliance with security standards. The program also emphasizes the importance of data analysis and visualization for ML, providing participants with the ability to gain insights from data and make informed decisions in their ML projects.
Data Analysis, Visualization, and Practical Proficiency in ML Frameworks
Throughout the program, participants will have hands-on experience with ML and deep learning frameworks, allowing them to gain practical proficiency in building ML solutions. Moreover, they will learn to recommend and implement the appropriate ML services and features to address specific problems effectively. By the end of the program, attendees will be well-prepared to tackle real-world ML challenges and contribute to the development of successful ML projects in a variety of domains.
Who this course is for
- Developers
- Data Scientists
- Certification Seekers
- Machine Learning Aspirants
- AWS Professionals
- Development Roles
- Data Science Roles
What You'll Learn
Facilities & Equipment
Virtual Training
- Electronic materials
- IT support for software & hardware
- Administrative support
Face-to-Face Training
- Air-conditioned classroom
- Meals & refreshments provided
- Projector & smart board
- Stationery provided