Read, understand, and write code in Python, including language constructs such as functions and classes.
Read code using vectorized operations with the NumPy library.
probability theory
single variable calculus
vectors and matrices
machine learning
Build a machine learning model for a supervised learning problem and understand basic methods to represent categorical and numerical features as inputs for this model
Perform simple machine learning tasks, such as classification and regression, from a set of features
Apply basic knowledge of Python data and machine learning frameworks (Pandas, NumPy, TensorFlow, PyTorch) to manipulate and clean data for consumption by different estimators/algorithms (e.g. CNNs, RNNs, tree-based models).
syllabus may include:
clinical data
clinical knowledge systems such as physiologic time series, differential diagnosis, disease progression and modelling
Aust Inst. of ICT AI course - 6 months online, four exams across four certifications that need to be undertaken in-person at a testing centre near you, or in an online proctored environment; $4,544 fee.