Course Brief

This comprehensive module empowers the learners to transform their daily operations by seamlessly integrating Claude into their workflows. Learners will gain the practical skills needed to move beyond basic AI interactions, mastering structured prompt engineering, automated document collaboration, and data-driven decision-making. By the end of the course, participants will be fully equipped to design and deploy custom AI tools and analytics frameworks that directly solve real-world business challenges, all while establishing safe, responsible AI governance practices within their organizations.

The learning journey begins with Instructional Unit 1, which establishes foundational Claude core skills, teaching learners how to craft structured prompts, eliminate hallucinations, and utilize Claude Co-work for multi-step document collaboration. Building upon this, Instructional Unit 2 dives into the mechanics of business automation. Here, participants learn the complete lifecycle of designing, testing, and deploying both single-task and multi-step AI agents. Learners will create highly functional tools, such as SOP generators and email assistants, establishing reusable, standardized templates that drastically reduce time spent on repetitive tasks.

The focus then shifts to generating strategic insights in Instructional Unit 3, where learners harness Claude to interpret data. Participants will master KPI and variance analysis, transform raw data into CFO-ready narrative reports, and conduct scenario planning and forecasting. Finally, the module project challenges learners to synthesise these capabilities into an integrated workplace solution. Participants will identify a genuine operational bottleneck, build an automating agent, apply data analytics, and present a management-ready framework that delivers immediate, measurable business value.

Course Knowledge, Skills & Ability Summary

At the end of the course, you will be able to acquire the following:

Knowledge

  • Define the core structural components of prompt engineering, including role, task, context, constraints, and output.
  • Identify the architectural differences between standard conversational chatbots and goal-oriented AI agents.
  • Explain output quality control protocols to reduce AI hallucinations and effectively refine prompt responses.
  • Describe data interpretation methods for tracking key performance indicators and analyzing business variances using AI.
  • Outline responsible AI governance practices for ensuring data privacy and safe automation boundaries.

Skills

  • Construct structured, multi-shot prompts to generate reliable, context-aware business documents using Claude.
  • Design specialized AI agents to automate routine workplace workflows, such as drafting standard operating procedures.
  • Utilize Claude Co-work to process complex documents and establish shared team prompt libraries for collaboration.
  • Analyze Excel-based datasets with AI to identify business trends, benchmark performance, and calculate financial variances.
  • Formulate executive narratives by converting quantitative data and dashboards into structured management reports.

Ability

Upon completion of this course, learners will be able to independently design and implement integrated AI-enabled workplace solutions that combine automation, data analytics, and responsible AI practices to enhance productivity and decision-making in MSME environments.

Blended Learning Journey

(60.5 Hours)

Placeholder Image

E-Learning

12 Hours

Placeholder Image

Flipped Class

16 Hours

Placeholder Image

Mentoring Support (Sync) (Assignment)

11 Hours

Placeholder Image

Mentoring Support (Sync) (Project)

9 Hours

Placeholder Image

Mentoring Support (Async)

12 Hours

Placeholder Image

Summative Assessment

0.5 Hours

Module Summary

WSQ Generative AI (SF)

Module Brief

This comprehensive module empowers the learners to transform their daily operations by seamlessly integrating Claude into their workflows. Learners will gain the practical skills needed to move beyond basic AI interactions, mastering structured prompt engineering, automated document collaboration, and data-driven decision-making. By the end of the course, participants will be fully equipped to design and deploy custom AI tools and analytics frameworks that directly solve real-world business challenges, all while establishing safe, responsible AI governance practices within their organizations.

The learning journey begins with Instructional Unit 1, which establishes foundational Claude core skills, teaching learners how to craft structured prompts, eliminate hallucinations, and utilize Claude Co-work for multi-step document collaboration. Building upon this, Instructional Unit 2 dives into the mechanics of business automation. Here, participants learn the complete lifecycle of designing, testing, and deploying both single-task and multi-step AI agents. Learners will create highly functional tools, such as SOP generators and email assistants, establishing reusable, standardized templates that drastically reduce time spent on repetitive tasks.

The focus then shifts to generating strategic insights in Instructional Unit 3, where learners harness Claude to interpret data. Participants will master KPI and variance analysis, transform raw data into CFO-ready narrative reports, and conduct scenario planning and forecasting. Finally, the module project challenges learners to synthesise these capabilities into an integrated workplace solution. Participants will identify a genuine operational bottleneck, build an automating agent, apply data analytics, and present a management-ready framework that delivers immediate, measurable business value.

Other Information
  • SSG Module Reference No: TGS-2024046660
  • Module Validity Date: 2027-01-31

Target Audience & Prerequisite

Target Audience

Prerequisite

  • Minimum Age: Minimum 21 years.
  • English Proficiency: Minimum IELTS 5.5 or its equivalent.
  • Academic Qualification: Minimum one credit in O Level or its equivalent
  • Experience: Minimum 1 year of experience in any business process

Graduation Requirements

Certificates

Academic Qualification

  • No Academic Qualification for this course

Statement of Attainment

  • WSQ Generative AI (SF)

    ICT-DIT-4029-1.1: Text Analytics and Processing

Industry Skills Certificate

  • No Industry Skills Certificate for this course

Other Information

Course Reference

  • SSG Course Reference No: TGS-2024046660

  • Course Validity Date: 2027-01-31

  • Course Developer : Lithan Academy

Pricing & Funding