AWS Certified AI Practitioner Training
About This Course
This WSQ AWS Certified AI Practitioner Training provides learners with a comprehensive foundation in AI and machine learning using AWS technologies. Participants will explore fundamental AI concepts, machine learning workflows, and generative AI capabilities to develop AI-driven applications. The course covers AWS AI services, including Amazon Q and AWS AI Bedrock, enabling learners to deploy and optimize foundation models effectively. Emphasis is placed on data management, interoperability, and implementing best practices for AI development within an AWS ecosystem.
Through hands-on learning, participants will apply AI security, compliance, and governance frameworks to ensure ethical and responsible AI deployment. The course also covers prompt engineering, model fine-tuning, and performance evaluation to enhance AI system efficiency. By the end of this training, learners will be equipped with the skills to design, implement, and maintain AI applications using AWS, preparing them for AWS AI certification and real-world AI solution deployment.
What You'll Learn
LO1: Implement AI applications with Amazon Q business and AWS AI models.
LO2: Deploy AWS AI Bedrock workflows according to plan and machine learning techniques.
LO3: Identify and report issues with AI applications and data and implementation procedures.
LO4: Maintain data interoperability during AI development in accordance to principles of data management
LO5: Perform data cleaning techniques to optimize AWS Foundation models
Course Outline:
Topic 1 : Fundamentals of AI and ML
Basic AI concepts and terminologies
Practical use cases for AI
Machine Learning development lifecycle
Topic 2: Fundamentals of Generative AI
Basic concepts of generative AI.
Capabilities and limitations of generative AI for solving business problems
AWS infrastructure and technologies for building generative AI applications
Topic 3: Applications of Foundation Models
Design considerations for applications that use foundation models
Effective prompt engineering techniques
Training and fine-tuning process for foundation models
Methods to evaluate foundation model performance
Amazon Q
Topic 4: Guidelines for Responsible AI
Development of AI systems that are responsible.
Importance of transparent and explainable models.
Topic 5: Security, Compliance, and Governance for AI Solutions
Methods to secure AI systems.
Governance and compliance regulations for AI systems.
Entry Requirements
Knowledge and Skills
• Able to operate computer functions with minimum Computer Literacy Level 2 based on ICAS Computer Skills Assessment Framework
• 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 Year Group : 21-65 years old