Pearson Vue Certified IT Specialist - Artificial Intelligence
About This Course
The WSQ Pearson VUE Certified IT Specialist Artificial Intelligence course provides comprehensive training in AI implementation, model deployment, and data management. Participants will learn to identify AI problem areas, classify problems, and ensure ethical and secure AI application. The course covers data collection, processing, and engineering techniques, including feature selection, quality assessment, and dataset preparation for AI training.
Through hands-on practice, you will explore AI algorithms, model training, performance evaluation, and bias detection to enhance AI application accuracy. The course also focuses on AI system deployment, integration, and monitoring to ensure optimal performance in production environments. With a strong emphasis on transparency, security, and regulatory compliance, this certification prepares professionals for real-world AI challenges.
What You'll Learn
LO1: Implement AI applications by integrating data management principles and fundamental AI concepts to address real-world challenges.
LO2: Deploy AI workflows using machine learning techniques and software development methodologies to optimize performance and accuracy.
LO3: Identify and report issues in AI applications by analyzing implementation procedures and evaluating collected data.
Topics Covered:
Topic 1: AI Problem Definition
• Identify the problem you are trying to solve using AI
• Classify the problem
• Identify the areas of expertise needed to solve the problem
• Build a security plan
• Ensure that AI is used appropriately
• Choose transparency and validation activities
Topic 2: Data Collection, Processing, and Engineering
• Choose the way to collect data
• Assess data quality
• Ensure that data are representative
• Identify resource requirements
• Convert data into suitable formats
• Select features for the AI model
• Engage in feature engineering
• Identify training and test datasets
• Document data decisions
Topic 3: AI Algorithms and Models
• Consider applicability of specific algorithms
• Train a model using the selected algorithm
• Select specific model after experimentation
• Tell data stories
• Evaluate model performance
• Look for potential sources of bias in the algorithm
• Evaluate model sensitivity
• Confirm adherence to regulatory requirements
• Obtain stakeholder approval
Topic 4: Application Integration and Deployment
• Train customers on how to use the product and what to expect
• Plan to address potential challenges of models in production
• Design a production pipeline, including application integration
• Support the AI solution
Topic 5: Maintaining and Monitoring AI in Production
• Engage in oversight
• Assess business impact
• Measure impacts on individuals and communities
• Handle feedback from users
• Consider improvement or decommission on a regula
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