Skip to content

Software Automation

NESA

Algorithms in Machine Learning

Key Description Reference Comment
SA-AM-01 Investigate how machine learning (ML) supports automation through the use of DevOps, robotic process automation (RPA) and business process automation (BPA) These are 4 separate topics and should not be conflated
SA-AM-02 Distinguish between artificial intelligence (AI) and ML AI
SA-AM-03 Explore models of training ML
SA-AM-03.01 supervised learning
SA-AM-03.02 unsupervised learning
SA-AM-03.03 semi-supervised learning
SA-AM-03.04 reinforcement learning
SA-AM-04 Investigate common applications of key ML algorithms
SA-AM-04.01 data analysis and forecasting
SA-AM-04.02 virtual personal assistants
SA-AM-04.03 image recognition
SA-AM-05 Research models used by software engineers to design and analyse ML
SA-AM-05.01 decision trees
SA-AM-05.02 neural networks
SA-AM-06 Describe types of algorithms associated with ML
SA-AM-06.01 linear regression
SA-AM-06.02 logistic regression
SA-AM-06.03 K-nearest neighbour

Programming for Automation

Key Description Reference Comment
SA-PA-01 Design, develop and apply ML regression models using an OOP to predict numeric values
SA-PA-01.01 linear regression
SA-PA-01.02 polynomial regression Why is this not consistent with the previous section and do K-nearest?
SA-PA-01.03 logistic regression
SA-PA-02 Apply neural network models using an OOP to make predictions

Significance and impact of ML and AI

Key Description Reference Comment
SA-SI-01 Assess the impact of automation on the individual, society and the environment
SA-SI-01.01 safety of workers
SA-SI-01.02 people with disability
SA-SI-01.03 the nature and skills required for employment
SA-SI-01.04 production efficiency, waste and the environment
SA-SI-01.05 the economy and distribution of wealth
SA-SI-02 Explore by implementation how patterns in human behaviour influence ML and AI software development
SA-SI-02.01 psychological responses
SA-SI-02.02 patterns related to acute stress response
SA-SI-02.03 cultural protocols
SA-SI-02.04 belief systems
SA-SI-03 Investigate the effect of human and dataset source bias in the development of ML and AI solutions