To provide a sound basis in mathematical topics of relevance to data sciences.
1. Formulae (1.1 Recognise, manipulate, evaluate, and solve a given formulae. These formulae may involve a combination of polynomial, algebraic, trigonometric, exponential, and logarithmic components.)
2. Logarithms, Exponentials and Hyperbolic Functions (2.1 Definitions and laws of logarithms log and exponentials exp. Graphs of log and exp. Manipulation of expressions involving log and exp. Definition and drawing the graph of hyperbolic functions. Use of identities associated with hyperbolic functions.)
3. Application of linear, log and exponential functions (3.1 Applications of the straight line equation. Linear-linear graphs and linear interpolation. Reduction of algebraic equations. Linear graphs of logarithmic functions. Log-linear scales. Log-log scales)
4. Introduction to differentiation (4.1 Derivatives as rate of change. Definition of a derivative. Derivatives of polynomials, differentiation of other common function. Higher derivatives. The chain, product and quotient rules. Implicit and Parametric differentiation. Curve sketching, stationary points. Simple rate problems)
5. Computer Algebra System (5.1 Accurately and precisely input mathematical syntax into a computer algebra system)
By the end of the course, students should be able to do the following:
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SCQF Level: 7
Credits: 7.5