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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Occupational Certificate: Robotic Process Automation (RPA) Developer

Lesson Overview

This lesson introduces learners to workflow automation and the principles used to automate business processes within RPA environments. Learners will explore workflows, automation logic, automation sequences, triggers, exceptions, process integration, and workflow execution. The lesson also examines how workflows are designed, tested, monitored, and maintained to support reliable automation solutions in organisations.

Lesson Outcomes

After completing this lesson, learners will be able to:

  • Define workflows and workflow automation
  • Explain workflow sequences and automation logic
  • Describe triggers and automation execution methods
  • Explain exception handling in workflows
  • Identify workflow integration methods
  • Describe workflow testing and monitoring processes
  • Explain workflow maintenance and optimisation principles

KT0301: Workflows and Workflow Automation

A workflow is a sequence of tasks or activities performed to complete a business process.

Workflow automation uses technology to execute workflow activities automatically with minimal human involvement.

In RPA environments, workflows define:

  • What tasks must happen
  • In what order tasks occur
  • What systems are involved
  • What decisions must be made
  • What outputs are produced

Examples of workflow automation include:

  • Automated invoice approval
  • Customer onboarding
  • Payroll processing
  • Report generation
  • Email notifications

Workflow automation improves:

  • Efficiency
  • Accuracy
  • Consistency
  • Productivity
  • Service delivery

Automation workflows are important because organisations often perform repetitive processes that consume time and resources.


KT0302: Workflow Sequences

Workflow sequences define the order in which automation activities are executed.

Each workflow step must follow a logical structure to ensure that the automation performs correctly.

Example workflow sequence:

  1. Open application
  2. Log into system
  3. Retrieve customer data
  4. Validate information
  5. Update records
  6. Generate report
  7. Send confirmation email

Workflow sequences may include:

  • Inputs
  • Conditions
  • Decisions
  • Loops
  • Outputs
  • Exceptions

Proper workflow sequencing is important because incorrect workflow order may cause:

  • Process failures
  • Incorrect outputs
  • System errors
  • Duplicate processing

Workflow sequences are often represented visually using workflow diagrams.


KT0303: Automation Logic

Automation logic refers to the rules and decision-making structures used within workflows.

Automation logic determines:

  • What actions should happen
  • When actions should occur
  • How systems respond to conditions
  • What happens when exceptions occur

Common logic structures include:

Logic Structure Purpose
If Statements Decision-making
Loops Repeating tasks
Conditions Evaluating data
Variables Storing information
Functions Reusable activities

Example:

</>     Python
if invoice_amount > 5000:
send_for_approval()
 

In this example, the automation checks whether the invoice exceeds a specific amount before continuing.

Good automation logic improves workflow reliability and process accuracy.


KT0304: Triggers and Automation Execution

A trigger is an event or condition that starts an automation workflow.

Triggers help automation systems respond automatically to business events.

Common triggers include:

  • Scheduled times
  • New emails
  • File uploads
  • Database changes
  • User actions
  • System notifications

Scheduled Execution

Workflows may run according to schedules.

Example:

  • Daily at 18:00
  • Every Monday morning
  • End-of-month processing

Event-Based Execution

Automation may begin when a specific event occurs.

Example:

  • A customer submits a form
  • A file is added to a folder
  • A new invoice is received

Triggers improve automation efficiency because workflows can run automatically without manual intervention.


KT0305: Exception Handling

Exceptions are unexpected situations or errors that prevent workflows from completing normally.

Examples of workflow exceptions include:

  • Missing data
  • Incorrect login credentials
  • System downtime
  • Network failures
  • Invalid input information

Exception handling refers to the methods used to manage and respond to these problems.

Common Exception Handling Techniques

Error Messages

The system displays or records information about the problem.

Retry Logic

The workflow attempts the task again automatically.

Logging

Workflow activity and errors are recorded for troubleshooting.

Escalation

The issue is reported to a human user or support team.

Exception handling is important because automation systems must continue operating reliably even when problems occur.


KT0306: Workflow Integration

Workflow integration refers to connecting workflows with different systems, applications, or services.

RPA workflows often integrate with:

  • Databases
  • Emails
  • ERP systems
  • CRM systems
  • Websites
  • APIs
  • Cloud services

Integration allows workflows to:

  • Exchange information
  • Process data automatically
  • Coordinate activities between systems

Example:

An automation workflow may:

  1. Read customer information from a database
  2. Update a CRM system
  3. Generate an invoice
  4. Email the customer automatically

Workflow integration improves operational efficiency by reducing manual system interactions.


KT0307: Workflow Testing

Workflow testing verifies that automation processes operate correctly according to requirements.

Testing helps identify:

  • Errors
  • Incorrect logic
  • Missing steps
  • Integration issues
  • Performance problems

Types of Workflow Testing

Testing Type Purpose
Unit Testing Tests individual workflow components
Integration Testing Tests connected systems
System Testing Tests the complete workflow
User Acceptance Testing Verifies business requirements

Testing is important because poorly tested workflows may cause business disruptions and incorrect outputs.

Automation testing should occur before deployment into production environments.


KT0308: Workflow Monitoring

Workflow monitoring involves tracking automation performance and workflow execution.

Monitoring helps organisations:

  • Identify workflow failures
  • Measure performance
  • Detect bottlenecks
  • Review automation logs
  • Improve operational efficiency

Monitoring tools may display:

  • Workflow status
  • Execution times
  • Error reports
  • Bot activity
  • Queue performance

Continuous monitoring improves automation reliability and supports proactive problem-solving.


KT0309: Workflow Maintenance and Optimisation

Workflow maintenance involves updating and supporting automation processes after deployment.

Maintenance activities may include:

  • Fixing errors
  • Updating workflows
  • Improving performance
  • Responding to system changes
  • Adjusting business rules

Optimisation focuses on improving workflow efficiency and effectiveness.

Optimisation may involve:

  • Reducing unnecessary steps
  • Improving execution speed
  • Enhancing error handling
  • Improving integrations
  • Updating automation logic

Workflows require regular maintenance because business systems and requirements change over time.

Well-maintained workflows improve reliability, scalability, and business performance.


Workflow Automation in Business Environments

Workflow automation is widely used across industries to improve operational performance.

Examples include:

Industry Workflow Example
Banking Loan processing
Healthcare Patient registration
Retail Inventory updates
Insurance Claims processing
Government Document approvals

Workflow automation supports digital transformation by reducing manual work and improving service delivery.


Key Notes

  • Workflows are structured sequences of activities used to complete business processes.
  • Workflow automation executes tasks automatically using technology and bots.
  • Workflow sequences define the order of automation activities.
  • Automation logic controls decisions and workflow behaviour.
  • Triggers start workflows automatically based on schedules or events.
  • Exception handling manages workflow errors and unexpected situations.
  • Workflow integration connects automation with systems and applications.
  • Workflow testing verifies that automation performs correctly.
  • Workflow monitoring tracks performance and detects issues.
  • Workflow maintenance and optimisation improve reliability and efficiency over time.
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