Course Content
KM-01: Introduction to RPA and Digital Transformation
This module introduces learners to the fundamentals of Robotic Process Automation (RPA), digital transformation, and automation technologies used in modern business environments. Learners will explore how businesses use automation to improve efficiency, reduce repetitive tasks, and support digital innovation.
0/7
KM-04: Computing Theory
This module introduces learners to the foundational principles of programming and computing theory used in software development and automation environments. Learners will explore programming languages, programming logic, algorithms, variables, operators, loops, functions, and software applications commonly used in modern computing systems. The module also introduces concepts related to web technologies, databases, artificial intelligence, and software development methodologies.
0/7
KM-05: Data, Databases and Data Scraping
This module introduces learners to the principles of data management, databases, and data scraping used in modern digital and automation environments. Learners will explore how organisations collect, store, analyse, secure, and visualise data to support business processes and decision-making. The module also introduces structured query language (SQL), relational databases, web scraping techniques, and software tools used for analysing and visualising data in automation and RPA environments.
0/13
KM-06: Introduction to RPA for Automation of Processes
This module introduces learners to the foundational concepts, technologies, and processes involved in Robotic Process Automation (RPA). Learners will explore automation principles, business process analysis, workflow automation, process mapping, bots, attended and unattended automation, and the role of RPA in improving operational efficiency. The module also examines how organisations identify processes suitable for automation and how RPA supports digital transformation initiatives.
0/7
KM-07: Robotic Process Automation (RPA)
This module focuses on building an understanding of how to use a toolkit or platform, using a vendor-specific approach, for the creation and deployment of automated processes. Learners will explore variables, arguments, automation selectors, control flow, data manipulation, automation concepts, automation management, and methods used to secure the RPA ecosystem from security risks. The module develops practical knowledge required to build, manage, and support automation solutions within modern RPA environments.
0/15
KM-08: Introduction to RPA Governance, Legislation and Ethics
This module introduces learners to governance, legislation, compliance, ethics, and responsible practices within Robotic Process Automation (RPA) environments. Learners will explore legal requirements, organisational governance, ethical considerations, compliance frameworks, privacy protection, intellectual property, accountability, and professional conduct related to automation technologies. The module also examines how organisations manage risk, maintain compliance, and ensure ethical use of RPA systems within modern digital business environments.
0/19
KM-09: Fundamentals of Design Thinking and Innovation
This module introduces learners to the fundamentals of design thinking and innovation within modern business and technology environments. Learners will explore design thinking principles, human-centered design, creativity, innovation, design concepts, design thinking methodologies, and the practical application of design thinking in software development, cybersecurity, and business problem-solving. The module focuses on developing innovative thinking, problem-solving skills, and creative approaches used in modern workplaces and digital transformation environments.
0/15
KM-10: 4IR and Future Skills
This module focuses on building an understanding of the impact of the Fourth Industrial Revolution (4IR) on communities, individuals, and businesses, as well as the future skills required in modern digital environments. Learners will explore emerging 4IR technologies, computing knowledge, future skills and competencies, business trends, interpersonal and intrapersonal skills, communication methods, workplace teamwork, customer service, and professional workplace practices required within modern organisations and Robotic Process Automation (RPA) environments.
0/29
PM-01: Basic Calculations for Programming
This practical module introduces learners to the mathematical and computational concepts required in programming and automation environments. Learners will develop practical skills in number systems, measurement conversions, mathematical operations, scientific notation, logical calculations, and computational problem solving. The module focuses on applying calculations and numerical reasoning in software development and Robotic Process Automation (RPA) environments. Learners will complete practical activities that strengthen analytical thinking, accuracy, and computational problem-solving skills required in modern digital workplaces.
0/16
PM-02: Basic Programming
This practical module introduces learners to fundamental programming concepts, software toolkits, coding environments, programming paradigms, data types, APIs, functions, logical operations, loops, SQL queries, error handling, and software development processes used in Robotic Process Automation (RPA) environments. Learners will develop practical programming skills by creating coding environments, writing and testing code, working with variables and functions, integrating APIs, handling errors, and developing simple automation solutions using industry-relevant software toolkits and platforms.
0/15
PM-03: Access, Analyse and Visualise Structured Data Using Spreadsheets and Scraping Tools
This practical module focuses on developing the skills required to access, analyse, organise, transform, visualise, and report structured data using spreadsheets, dashboards, pivot tables, databases, and web scraping tools within a Robotic Process Automation (RPA) environment. Learners will work with spreadsheet reporting, dashboards, pivot tables, SQL imports, data models, charts, and web scraping techniques to process and visualise data for business decision-making.
0/12
PM-05: Execute Test Procedures for Evaluating the RPA Solution Performance
This practical module focuses on developing the practical skills required to prepare, execute, evaluate, and improve test procedures for Robotic Process Automation (RPA) solutions. Learners will work with test cases, testing methodologies, simulation tools, workflow evaluations, exception handling, and remedial actions to determine whether an RPA solution passes or fails according to business and technical requirements. Learners will also develop the ability to analyse automation outcomes, identify application and workflow issues, document test evidence, and apply corrective actions to improve automation reliability and performance.
0/4
PM-06: Deploy RPA Solutions Which Emulate Actions of a Human Interacting Within Digital Systems
This practical module focuses on developing the practical skills required to deploy, schedule, monitor, manage, and maintain Robotic Process Automation (RPA) solutions within production environments. Learners will work with unattended and attended robots, deployment procedures, process documentation, auditing dashboards, scheduling systems, and RPA environment management tools. Learners will also develop the ability to schedule automated workflows, deploy bots into production environments, update process documentation, train end-users, monitor runtime activities, and import or export automation solutions between environments.
0/7
PM-07: Modify and Improve Existing RPA Solutions
This practical module focuses on developing the practical skills required to troubleshoot, improve, maintain, and optimise existing Robotic Process Automation (RPA) solutions within operational environments. Learners will work with debugging tools, workflow optimisation techniques, infrastructure changes, software upgrades, regulatory requirements, and process improvement strategies to ensure that automation workflows continue to operate efficiently and reliably. Learners will also develop the ability to investigate alternative solutions, apply continuous improvement techniques, manage changes in technical environments, explore workflow scalability, and update robotic workflows when organisations upgrade RPA software versions.
0/6
PM-08: Function Ethically and Effectively as a Member of a Multidisciplinary Team
This practical module focuses on developing the practical skills required to function ethically, professionally, and collaboratively within multidisciplinary Robotic Process Automation (RPA) environments. Learners will work with business analysts, solution architects, DevOps teams, infrastructure engineers, project managers, business users, and stakeholders throughout the automation life cycle. Learners will also develop the ability to communicate effectively, collaborate across departments, support business process automation initiatives, engage with stakeholders ethically, adapt to organisational policies and infrastructure changes, and contribute to teamwork and business optimisation activities.
0/7
PM-09: Apply Design Thinking Methodologies
This practical module focuses on developing the practical skills required to apply Design Thinking methodologies within problem-solving and innovation environments. Learners will collaborate with multidisciplinary teams to investigate problems, generate innovative ideas, develop prototypes, and test solutions using the Design Thinking process. Learners will also develop the ability to engage in collaborative discussions, participate in innovation workshops, analyse user needs, challenge assumptions, generate creative solutions, and apply the five Design Thinking phases: Empathize, Define, Ideate, Prototype, and Test.
0/3
Occupational Certificate: Robotic Process Automation (RPA) Developer

Lesson Outcomes

After completing this practical lesson, learners will be able to:

  • Identify report-based data sources
  • Import data from existing reports
  • Extract and organise report information
  • Clean and validate imported report data
  • Analyse imported report information
  • Refresh and maintain imported report datasets

Overview

Businesses and Robotic Process Automation (RPA) environments frequently use operational and management reports as sources of structured data for analysis and decision-making. Importing data from reports improves reporting efficiency and supports automated business intelligence processes.

This practical lesson introduces learners to importing report-based data, extracting structured information, cleaning datasets, validating records, and analysing imported report information using spreadsheet and reporting tools. Learners will complete practical activities involving business performance and operational reports.


Scenario: Business Operations Reporting

A company generates monthly operational reports containing sales information, customer activity, and inventory performance.

Management requires selected report data to be imported into a spreadsheet environment for further analysis and dashboard reporting.

Learners are required to import and process information from existing reports for business reporting purposes.


PA0901 — Identify Report Data Sources

Tools/Resources

  • PC or laptop
  • Spreadsheet or BI software
  • Operational reports

Activity Instructions

  1. Review the provided reports.
  2. Identify structured data sections.
  3. Determine suitable data fields for import.
  4. Organise report files for processing.

Expected Outcome

Report-based data sources are identified successfully.

Evidence Required

  • Screenshot of selected reports
  • Screenshot of identified data sections
  • Screenshot of organised report files

PA0902 — Import Data from Reports

Tools/Resources

  • Spreadsheet software
  • Import tools
  • Report files

Activity Instructions

  1. Open the spreadsheet or reporting environment.
  2. Import report data into worksheets or tables.
  3. Configure import settings correctly.
  4. Verify imported records.

Expected Outcome

Data is imported successfully from reports into the reporting environment.

Evidence Required

  • Screenshot of import settings
  • Screenshot of imported report data
  • Screenshot of loaded tables

PA0903 — Clean and Validate Imported Report Data

Tools/Resources

  • Spreadsheet software
  • Validation tools
  • Imported datasets

Activity Instructions

  1. Identify incomplete or inconsistent records.
  2. Correct formatting issues.
  3. Remove duplicate or invalid entries.
  4. Validate imported information.
  5. Verify cleaned outputs.

Expected Outcome

Imported report data is cleaned and validated successfully.

Evidence Required

  • Screenshot of cleaned datasets
  • Screenshot of validated records
  • Screenshot of corrected formatting

PA0904 — Analyse Imported Report Information

Tools/Resources

  • Spreadsheet software
  • Pivot tables or dashboards
  • Imported report datasets

Activity Instructions

  1. Create summaries from imported report data.
  2. Analyse trends or operational performance.
  3. Generate charts or reports.
  4. Verify analysed outputs.

Expected Outcome

Imported report information is analysed successfully.

Evidence Required

  • Screenshot of summary reports
  • Screenshot of charts or dashboards
  • Screenshot of analysed outputs

PA0905 — Refresh and Maintain Imported Report Data

Tools/Resources

  • Spreadsheet software
  • Updated reports
  • Validation tools

Activity Instructions

  1. Refresh imported report data after updates.
  2. Verify data consistency and accuracy.
  3. Correct any identified issues.
  4. Save the completed workbook.

Expected Outcome

Imported report datasets are refreshed and maintained successfully.

Evidence Required

  • Screenshot of refreshed datasets
  • Screenshot of verified outputs
  • Screenshot of corrected data issues

Key Notes

  • Reports are important sources of structured business data.
  • Imported report data supports business analysis and reporting.
  • Cleaning and validation improve data quality.
  • Refreshing updates imported records automatically.
  • Visual analysis improves interpretation of business information.
  • Correct organisation improves reporting efficiency.
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