The Artificial Intelligence Software Developer Course is designed for learners who want to build intelligent software systems using Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Python programming, TensorFlow, data analytics, and modern AI development frameworks.
This qualification prepares learners to develop AI-powered applications, train machine learning models, build neural networks, test AI performance, deploy intelligent solutions, and maintain AI systems in real-world business environments. Learners gain both theoretical knowledge and practical workplace experience required by the rapidly growing AI industry.
Artificial Intelligence is transforming industries worldwide. Organisations are increasingly seeking professionals who can build intelligent applications, automate decision-making processes, analyse large datasets, and create machine learning solutions.
At Wheelset Academy, learners gain practical exposure to AI software development using Python, Machine Learning, Deep Learning, TensorFlow, SQL databases, data visualisation, and modern AI development methodologies.
After completing this Artificial Intelligence Software Developer Course, learners will be able to:
Develop Artificial Intelligence software applications
Build Machine Learning models
Create Deep Learning neural network architectures
Develop AI solutions using Python
Use TensorFlow and AI frameworks
Analyse and visualise data
Design and implement intelligent systems
Test and optimise AI model performance
Deploy AI applications into production environments
Maintain and improve AI solutions
Apply ethical and legal AI practices
Solve business problems using AI technologies
This qualification is a registered Occupational Certificate aligned with the South African National Qualifications Framework.
To enrol for this Artificial Intelligence Software Developer Course, learners should have:
Recognition of Prior Learning (RPL) may apply where appropriate.
Full course fee or range Payment plan options Special discounts
On completion, learners receive a Letter of Competence from Wheelset Academy and, once verified, a Certificate of Competence with a Statement of Results from the QCTO.
Full course fee or range Payment plan options Special discounts
The course is taught in English through interactive methods such as lectures, discussions, case studies, videos, and assessments. Study options include classroom, blended online, or on-site training.
Upon successful completion, learners may pursue careers as:
Learners gain an understanding of Artificial Intelligence concepts, AI evolution, business applications, AI taxonomy, benefits, limitations, and future opportunities across industries.
This module develops mathematical and statistical foundations required for Artificial Intelligence, Machine Learning, Deep Learning, data analytics, probability, Bayes’ Theorem, linear algebra, and predictive modelling.
Learners develop analytical reasoning, critical thinking, root cause analysis, decision-tree analysis, and AI-based problem-solving approaches.
This module introduces data management, database concepts, SQL, data analytics, web scraping, data mining, dashboards, spreadsheets, visualisation tools, and data security.
Learners gain a strong foundation in programming concepts, algorithms, computational thinking, software development principles, coding logic, and Python programming.
This module explains the relationship between AI, Machine Learning, and Deep Learning while introducing intelligent systems and learning models.
Learners explore leading AI frameworks including TensorFlow, Keras, PyTorch, AWS AI tools, IBM Watson, and AI-driven data scraping techniques.
This module covers supervised learning, unsupervised learning, reinforcement learning, machine learning workflows, algorithms, model training, evaluation, and business applications.
Learners study neural networks, advanced deep learning concepts, deep learning architectures, TensorFlow, Keras, and advanced AI model development.
This module provides knowledge of legal compliance, ethical AI development, governance principles, and responsible AI implementation.
Learners develop innovation skills, creative problem-solving techniques, user-centred thinking, and AI solution design methodologies.
This module explores Fourth Industrial Revolution technologies, emerging trends, digital transformation, and future workplace competencies.
Learners apply mathematics and statistical techniques used in programming, machine learning, and AI development.
This module develops structured problem-solving and decision-making skills used in AI project environments.
Learners analyse datasets, build reports, create dashboards, and visualise information using spreadsheet tools.
This module develops database querying skills using SQL for AI and software development applications.
Learners create and test AI applications using Python programming and AI development libraries.
This module develops web scraping and data extraction skills for AI and analytics projects.
Learners develop machine learning applications using Python-based frameworks and algorithms.
This module focuses on building neural network architectures using Python deep learning tools.
Learners develop advanced deep learning solutions using TensorFlow and neural network frameworks.
This module develops teamwork, communication, professionalism, collaboration, and ethical workplace conduct.
Learners apply innovation methodologies to design, evaluate, and improve AI-based solutions.
Learners participate in interpreting solution designs and developing practical AI applications.
This workplace module develops skills in testing AI models, evaluating performance, measuring accuracy, and improving model effectiveness.
Learners gain experience in deploying AI solutions, monitoring performance, maintaining models, and implementing continuous improvements.
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An Artificial Intelligence Software Developer builds intelligent applications that use AI, Machine Learning, and Deep Learning technologies to solve real-world problems.
Yes. It is an Occupational Certificate developed through MICT SETA and aligned to QCTO occupational qualification standards.
The qualification is registered at NQF Level 5.or Artificial Intelligence and Machine Learning development.
The programme primarily uses Python, which is the leading language
Yes. Machine Learning is one of the core components of the qualification.
Yes. The qualification includes advanced Deep Learning concepts, neural networks, TensorFlow, and AI model development.
Yes. Learners complete extensive practical skills modules and workplace experience modules.
Yes. Applicants with an NQF Level 4 qualification may enrol.
Graduates may work as AI Developers, Machine Learning Developers, AI Engineers, AI Application Developers, and Artificial Intelligence Software Developers.
Yes. Learners complete work experience modules covering AI development, testing, deployment, and solution improvement.
Artificial Intelligence is one of the fastest-growing technology sectors globally and offers excellent career opportunities across industries including finance, healthcare, manufacturing, telecommunications, education, and technology.
