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.
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.
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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.
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.
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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.
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 Fourth Industrial Revolution (4IR) trends affecting businesses and organisations. Learners will explore Afro-centric approaches to solving African challenges, the use of digital tools to reduce development time, business intelligence and Big Data, collecting customer data, market insights, automated factories, and global digital exposure. The lesson focuses on how modern organisations use technology and innovation to improve business operations, decision-making, and competitiveness in digital economies.

Lesson Outcomes

After completing this lesson, learners will be able to:

  • Explain Afro-centric approaches to solving African challenges
  • Describe how digital tools reduce development time
  • Explain business intelligence and Big Data concepts
  • Describe data collection on clients
  • Explain market insights and analysis
  • Describe automated factories
  • Explain the impact of global digital exposure on businesses

KT0401: Afro-Centric Approach to African Problems

An Afro-centric approach focuses on solving African challenges using solutions that consider African environments, communities, opportunities, and realities.

According to the learner material:

“Taking the best from existing products and coming up with own solutions.”

This approach encourages innovation suited to African conditions and needs.


African Challenges and Opportunities

Africa faces challenges such as:

  • Infrastructure limitations
  • Unemployment
  • Digital inequality
  • Skills shortages

However, Africa also has opportunities including:

  • Young populations
  • Growing digital markets
  • Mobile technology adoption
  • Innovation ecosystems

Developing Local Solutions

Organisations and innovators are encouraged to:

  • Adapt global technologies
  • Develop local innovations
  • Solve community problems
  • Support digital transformation

Afro-centric innovation supports economic growth and sustainability.


KT0402: Using Google, Amazon and MS Forms and Tools to Reduce Development Time

Modern organisations use cloud-based tools and services to reduce software development and operational time.

Examples include:

  • Google tools
  • Amazon Web Services (AWS)
  • Microsoft tools and platforms

These tools improve productivity and simplify development processes.


Cloud-Based Development Tools

Cloud platforms provide:

  • Storage
  • Computing services
  • APIs
  • Automation tools
  • Development environments

Businesses use these tools to build systems more efficiently.


Artificial Intelligence APIs

The learner material refers to embedding AI APIs.

AI APIs allow developers to integrate intelligent features into applications without building AI systems from scratch.

Examples include:

  • Chatbots
  • Language translation
  • Image recognition
  • Voice recognition

Using APIs reduces development time and complexity.


Benefits of Cloud and Digital Tools

These tools help organisations:

  • Reduce costs
  • Improve efficiency
  • Increase scalability
  • Accelerate development

Cloud technologies are widely used in modern digital environments.


KT0403: Business Intelligence Applications and Availability of Big Data

Business Intelligence (BI) refers to technologies and processes used to analyse data and support decision-making.

Big Data refers to large volumes of data generated from digital systems and activities.


Data to Wisdom Process

According to the learner material, organisations move through the following process:

  1. Collecting data
  2. Converting data into information
  3. Turning information into knowledge
  4. Converting knowledge into intelligence
  5. Transforming intelligence into wisdom

This process improves organisational decision-making.


Business Intelligence Applications

Business intelligence applications help organisations:

  • Analyse performance
  • Identify trends
  • Improve decision-making
  • Understand customers
  • Improve operations

Big Data

Big Data includes large and complex data sets generated through:

  • Websites
  • Mobile devices
  • Social media
  • Sensors
  • Business systems

Organisations use Big Data to improve services and business strategies.


KT0404: Collecting Data on Clients

Modern businesses collect client data to better understand customer behaviour and improve services.

Examples of client data include:

  • Contact information
  • Purchasing behaviour
  • Preferences
  • Service history

Purpose of Collecting Client Data

Businesses collect data to:

  • Improve customer experiences
  • Personalise services
  • Analyse trends
  • Improve marketing
  • Support decision-making

Responsible Data Collection

Organisations must collect and manage data responsibly by:

  • Protecting privacy
  • Following legal requirements
  • Securing information
  • Maintaining confidentiality

Responsible data management improves customer trust.


KT0405: Insight into Different Markets

Market insight refers to understanding customer needs, trends, competitors, and business environments.

Organisations use market insights to:

  • Develop products
  • Improve services
  • Identify opportunities
  • Improve competitiveness

Sources of Market Insights

Examples include:

  • Customer feedback
  • Market research
  • Sales data
  • Social media analysis
  • Industry reports

Market insights support informed business decisions.


Importance of Market Analysis

Market analysis helps organisations:

  • Understand customer behaviour
  • Identify market opportunities
  • Reduce business risks
  • Improve strategic planning

Businesses that understand markets are often more competitive.


KT0406: Automated Factories

Automated factories use machines, robotics, software systems, and digital technologies to automate manufacturing and production processes.

Automation improves:

  • Productivity
  • Efficiency
  • Accuracy
  • Consistency

Technologies Used in Automated Factories

Examples include:

Technology Purpose
Robotics Automated production
Sensors Monitoring systems
Artificial Intelligence Smart decision-making
IoT Device communication

Automation reduces repetitive manual tasks and improves operational performance.


Benefits of Automated Factories

Automated factories help organisations:

  • Increase production speed
  • Improve quality
  • Reduce errors
  • Improve workplace safety

Modern industries increasingly rely on automation technologies.


KT0407: Exposure to the Global World

Digital technologies have increased global connectivity and business exposure.

Businesses can now:

  • Operate internationally
  • Access global markets
  • Collaborate remotely
  • Compete globally

Global Digital Environments

The internet and digital systems allow organisations to:

  • Communicate worldwide
  • Sell products globally
  • Access international information
  • Participate in global innovation

Benefits of Global Exposure

Global exposure helps organisations:

  • Expand business opportunities
  • Access international customers
  • Learn from global trends
  • Improve competitiveness

Digital transformation has made global business participation more accessible.


4IR Trends in Modern Businesses

Modern businesses are increasingly influenced by:

  • Automation
  • Artificial intelligence
  • Cloud computing
  • Big Data
  • Global connectivity

These technologies improve organisational efficiency, innovation, and competitiveness.

Businesses that adapt to 4IR trends are often better prepared for future digital economies.


Key Notes

  • Afro-centric innovation focuses on solving African challenges using localised solutions.
  • Cloud-based tools reduce development time and improve efficiency.
  • Business intelligence helps organisations analyse data and make decisions.
  • Big Data supports trend analysis and business insights.
  • Client data helps organisations improve services and customer experiences.
  • Market insights improve competitiveness and strategic planning.
  • Automated factories improve efficiency and productivity.
  • Digital technologies increase global business exposure and opportunities.
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