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.
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.
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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.
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.
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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.
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.
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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.
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 Overview

This lesson introduces learners to the principles and importance of data security in modern digital and automation environments. Learners will explore methods used to protect information from unauthorised access, corruption, and loss. The lesson also examines security risks, data protection processes, and common security solutions used in organisations to maintain data confidentiality, integrity, and availability.

Lesson Outcomes

After completing this lesson, learners will be able to:

  • Define data security and explain its purpose

  • Describe the importance of protecting data

  • Explain processes used to secure information

  • Identify risks related to unauthorised access and data corruption

  • Describe common data security solutions

  • Explain the importance of data security in automation and RPA environments


KT0601: Definition

Data security refers to the processes, technologies, and practices used to protect information from unauthorised access, misuse, loss, or damage.

Organisations rely on data security to ensure that sensitive information remains:

  • Confidential

  • Accurate

  • Available when needed

Data security applies to:

  • Databases

  • Business systems

  • Cloud platforms

  • Automation systems

  • Networks

  • Digital files

Data security is important because organisations process large amounts of sensitive information daily.

Examples of sensitive information include:

  • Customer details

  • Financial records

  • Employee information

  • Medical records

  • Business reports

Protecting this information is essential for business continuity and compliance with regulations.


KT0602: Purpose of Protecting Data

The main purpose of data protection is to ensure that information remains secure, reliable, and accessible only to authorised users.

Data protection helps organisations to:

  • Prevent unauthorised access

  • Protect customer privacy

  • Maintain business operations

  • Reduce financial losses

  • Ensure legal compliance

  • Maintain trust and reputation

Without proper security measures, organisations may experience:

  • Data breaches

  • Financial losses

  • Legal penalties

  • Operational disruptions

  • Reputation damage

In RPA environments, automation systems often process sensitive business information, making strong security controls essential.


KT0603: Process for Protecting Data

Organisations follow structured processes to secure information and reduce risks.

Common data protection processes include:

Access Control

Access control limits who can view or modify information.

Examples include:

  • Password protection

  • User permissions

  • Multi-factor authentication

Encryption

Encryption converts information into coded formats that cannot easily be read by unauthorised users.

Backups

Backups create copies of important data to prevent loss during system failures or cyberattacks.

Monitoring and Auditing

Monitoring systems track user activity and identify suspicious behaviour.

Security Policies

Organisations implement rules and procedures to guide employees on secure data handling practices.

Effective data protection processes improve system reliability and reduce security risks.


KT0604: Unauthorised Access

Unauthorised access occurs when individuals or systems gain access to information without permission.

Examples include:

  • Hacking

  • Stolen passwords

  • Insider misuse

  • Weak security controls

Unauthorised access may result in:

  • Data theft

  • Privacy violations

  • Financial losses

  • System disruption

Organisations reduce unauthorised access risks by implementing:

  • Strong passwords

  • User authentication

  • Access restrictions

  • Security monitoring

Automation systems and RPA bots must also follow strict access controls to ensure secure operations.


KT0605: Data Corruption

Data corruption occurs when information becomes damaged, altered, or unusable.

Causes of data corruption may include:

  • Hardware failures

  • Software errors

  • Malware

  • Power failures

  • Human error

Data corruption may lead to:

  • Inaccurate reports

  • System failures

  • Lost information

  • Operational disruptions

Organisations reduce corruption risks through:

  • Regular backups

  • Error checking

  • Secure systems

  • Reliable infrastructure

Maintaining accurate and reliable data is important because automation systems rely on correct information to function properly.


KT0606: Data Security Solutions

Organisations use different technologies and security solutions to protect information.

Common data security solutions include:

Security Solution Purpose
Firewalls Block unauthorised network access
Antivirus Software Detect and remove malware
Encryption Protect sensitive information
Backups Prevent data loss
Access Control Systems Restrict user access
Security Monitoring Tools Detect suspicious activity

Firewalls

Firewalls monitor and control incoming and outgoing network traffic.

Antivirus Software

Antivirus systems detect malicious software that may damage or steal information.

Encryption

Encryption protects sensitive information during storage and transmission.

Backup Systems

Backups help organisations recover information after system failures or cyberattacks.

Security Monitoring

Monitoring systems detect threats and support incident response activities.

Strong security solutions are essential in modern digital environments because cyber threats continue to increase.


Data Security in Automation and RPA Environments

Automation systems and RPA bots often process sensitive business information.

For this reason, organisations must ensure that:

  • Bots use secure credentials

  • Access permissions are controlled

  • Sensitive data is encrypted

  • System activities are monitored

  • Security policies are followed

Secure automation environments improve trust, compliance, and operational reliability.


Key Notes

  • Data security protects information from unauthorised access, misuse, and damage.

  • Organisations protect data to maintain privacy, compliance, and business continuity.

  • Security processes include access control, encryption, backups, and monitoring.

  • Unauthorised access may lead to data theft and operational disruption.

  • Data corruption affects the accuracy and reliability of information.

  • Common security solutions include firewalls, antivirus software, encryption, and backups.

  • Automation and RPA systems require strong security controls to protect sensitive information.

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