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:

  • Explain mixing data types in programming
  • Identify different data types used in calculations
  • Perform calculations involving mixed data types
  • Differentiate between integer and floating-point values
  • Apply mixed-type calculations in programming scenarios
  • Verify and correct mixed-type calculation errors

Overview

Programming environments use different data types to store and process information. Calculations may involve mixing integers, decimal values, text, and other data types. Programmers must understand how different data types interact to avoid calculation and processing errors.

This practical lesson introduces learners to mixed data types and their use in programming and Robotic Process Automation (RPA) environments. Learners will complete practical activities involving integers, floating-point numbers, mixed calculations, and type-related problem solving.


Scenario: Automated Pricing System

A software developer is creating an automated pricing system that calculates product totals, taxes, and discounts using different types of numerical values.

The system processes integers and decimal values together during calculations.

Learners are required to complete mixed-type calculations and verify the outputs generated by the system.


PA0701 — Identify Different Data Types

Programming systems use different data types to represent information.

Tools/Resources

  • IDE or coding environment
  • Notebook
  • Programming reference material

Activity Instructions

  1. Identify integer values.
  2. Identify floating-point or decimal values.
  3. Classify provided values according to their data types.
  4. Record all answers clearly.

Example

Value Data Type
25 Integer
15.75 Floating-point
100 Integer
3.14 Floating-point

Expected Outcome

Data types are identified and classified correctly.

Evidence Required

  • Screenshot of classified data types
  • Written explanation of identified types

PA0702 — Perform Mixed-Type Calculations

Programming calculations may combine integers and decimal values.

Tools/Resources

  • Calculator
  • IDE
  • Spreadsheet software

Activity Instructions

  1. Perform calculations using integers and decimal values.
  2. Record the outputs correctly.
  3. Verify all calculations manually.

Example

Problem:

25 + 4.5

Solution:

29.5


Expected Outcome

Mixed-type calculations are completed correctly.

Evidence Required

  • Screenshot of completed calculations
  • Screenshot of verified outputs

PA0703 — Differentiate Between Integer and Floating-Point Values

Programming systems process integers and floating-point values differently.

Tools/Resources

  • IDE
  • Notebook
  • Calculator

Activity Instructions

  1. Compare integer and floating-point values.
  2. Observe differences in outputs.
  3. Record all observations clearly.

Example

Integer:

7

Floating-Point:

7.0

Observation:

Floating-point values contain decimal precision.


Expected Outcome

Differences between integer and floating-point values are identified correctly.

Evidence Required

  • Screenshot of comparisons
  • Written explanation of observations

PA0704 — Apply Mixed Types in Programming Scenarios

Programming systems frequently use mixed-type calculations in real-world applications.

Tools/Resources

  • IDE or coding environment
  • Calculator
  • Notebook

Activity Instructions

  1. Solve practical problems involving mixed data types.
  2. Record all calculations clearly.
  3. Verify the final outputs.

Example

Problem:

A product costs R199.99 and VAT is R30.00. Calculate the total price.

Solution:

199.99 + 30.00 = 229.99


Expected Outcome

Mixed-type calculations are applied correctly in programming scenarios.

Evidence Required

  • Screenshot of practical calculations
  • Screenshot of completed outputs

PA0705 — Verify and Correct Mixed-Type Errors

Incorrect handling of data types may cause programming and calculation errors.

Tools/Resources

  • IDE
  • Debugging tools
  • Calculator

Activity Instructions

  1. Review provided mixed-type calculations.
  2. Identify incorrect outputs.
  3. Correct all identified errors.
  4. Verify corrected calculations.

Example

Incorrect Output:

5 + 2.5 = 7

Correct Output:

5 + 2.5 = 7.5


Expected Outcome

Mixed-type calculation errors are identified and corrected successfully.

Evidence Required

  • Screenshot of corrected calculations
  • Written explanation of corrections

Key Notes

  • Programming environments use different data types.
  • Integers represent whole numbers.
  • Floating-point values represent decimal numbers.
  • Mixed-type calculations combine different data types.
  • Incorrect type handling may cause programming errors.
  • Verifying outputs improves programming accuracy.
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