📘 Lesson Summary:

This lesson covers Workplace Experience Tasks WE04 and WE05, where learners analyse solution design documents, prepare technical designs for AI solutions, scrape datasets, and complete initial data analysis required for AI development.

Lesson 1: Analysing Technical Designs & Preparing Data for AI Systems (WE04–WE05)

This lesson focuses on preparing learners to understand and contribute to AI solution development. It combines reading and interpreting technical design documentation with scraping and analysing data that will be used in AI models.

These tasks reflect real industry workflows for junior AI developers and data technicians.

⭐ WE04: Analyse Solution Design Document (SDD) & Prepare Technical Design

Learners will:

• Access and read the organisation’s Solution Design Document (SDD)
• Understand system requirements, workflows, and components
• Identify data requirements for the AI solution
• Interpret diagrams, flows, or UML-like structures (if provided)
• Participate in preparing the technical design for implementation
• Document their understanding and findings
• Discuss the design with team members or supervisors

This ensures that learners can follow development standards and understand how AI components fit into the bigger system.

⭐ WE05: Scrape and Analyse Data for AI Solution Design

Learners complete supervised data scraping and analysis tasks:

• Scrape, export, or collect raw datasets from approved sources
• Clean, organise, and validate the dataset
• Identify relevant fields for AI processing
• Detect missing, incorrect, or inconsistent data
• Perform simple analysis such as counts, averages, or categories
• Prepare the dataset for model development (to be done in later WE tasks)

These tasks help learners understand data structures and prepare high-quality input for AI models.