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 Overview

This lesson introduces learners to Structured Query Language (SQL) and its role in managing relational databases. Learners will explore how SQL is used to store, retrieve, manipulate, and manage data within database management systems. The lesson also examines common SQL operations and how SQL supports business systems, reporting, and automation processes in modern digital environments.

Lesson Outcomes

After completing this lesson, learners will be able to:

  • Explain the purpose and function of SQL
  • Describe how SQL is used in relational database systems
  • Identify common SQL code constructs
  • Explain how SQL is used to store, retrieve, and manipulate data
  • Describe the role of SQL in automation and business systems

KT0301: SQL Programming Language

Structured Query Language (SQL) is a programming language used to communicate with relational databases.

SQL allows users and systems to:

  • Store information
  • Retrieve records
  • Update data
  • Delete records
  • Create database structures
  • Manage database access

SQL is widely used because relational databases store large amounts of structured information used by organisations.

Examples of systems that use SQL include:

  • Banking systems
  • Inventory systems
  • Payroll systems
  • Customer management systems
  • Reporting platforms

SQL provides a standard method for interacting with databases across many different platforms.

Common relational database systems include:

  • MySQL
  • Microsoft SQL Server
  • Oracle Database
  • PostgreSQL

SQL is important in RPA environments because automation bots often interact with databases to process and retrieve information automatically.


KT0302: SQL Code Constructs to Perform Database Transactions

SQL uses different commands and code structures called constructs to perform database operations.

Common SQL Constructs

SQL Command Purpose
SELECT Retrieve data
INSERT Add new data
UPDATE Modify existing data
DELETE Remove data
CREATE Create tables or databases
DROP Delete database structures

SELECT Statement

The SELECT statement retrieves information from a database.

Example:

</>     SQL
SELECT * FROM Customers;
 

This retrieves all records from the Customers table.

INSERT Statement

The INSERT statement adds new records.

Example:

</>     SQL
INSERT INTO Customers (Name, City)
VALUES ('John', 'Pretoria');
 

UPDATE Statement

The UPDATE statement changes existing data.

Example:

</>     SQL
UPDATE Customers
SET City = 'Cape Town'
WHERE Name = 'John';
 

DELETE Statement

The DELETE statement removes records.

Example:

</>     SQL
DELETE FROM Customers
WHERE Name = 'John';
 

These SQL constructs help organisations manage information efficiently.


KT0303: Storing, Retrieving, Managing and Manipulating Data Inside an RDBMS

An RDBMS (Relational Database Management System) is software used to manage relational databases.

Examples of RDBMS platforms include:

  • MySQL
  • Oracle
  • Microsoft SQL Server
  • PostgreSQL

SQL is used within an RDBMS to perform database operations.

Storing Data

Organisations store information in tables containing rows and columns.

Example table:

CustomerID Name City
1 Sarah Johannesburg
2 Ahmed Durban

Retrieving Data

SQL queries retrieve specific information from databases.

Example:

</>     SQL
SELECT Name FROM Customers;
 

This retrieves customer names only.

Managing Data

Database administrators manage:

  • User access
  • Database security
  • Data backups
  • Database performance
  • System updates

Manipulating Data

Data manipulation refers to changing stored information.

Examples include:

  • Updating records
  • Deleting records
  • Sorting data
  • Filtering information

SQL allows businesses to manage information efficiently and accurately.


SQL in Business and Automation Environments

SQL is important because organisations rely on data for daily operations and decision-making.

SQL supports:

  • Reporting systems
  • Business intelligence
  • Automation workflows
  • Customer management systems
  • Financial systems
  • Inventory management

In RPA environments, bots may use SQL to:

  • Extract information from databases
  • Update records automatically
  • Generate reports
  • Process transactions
  • Validate information

SQL improves operational efficiency by allowing systems to process large amounts of information quickly and accurately.


Advantages of SQL

Advantages of SQL include:

  • Efficient data retrieval
  • Standardised database communication
  • Improved data management
  • Support for automation
  • Secure data access
  • Scalability for large systems

SQL is widely used because it supports reliable and structured data management in modern digital systems.


Key Notes

  • SQL stands for Structured Query Language.
  • SQL is used to communicate with relational databases.
  • Common SQL commands include SELECT, INSERT, UPDATE, and DELETE.
  • An RDBMS manages relational databases and stored information.
  • SQL allows organisations to store, retrieve, manage, and manipulate data.
  • SQL supports reporting systems, automation workflows, and business intelligence.
  • RPA bots often use SQL to process database information automatically.
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