Computing Mathematics (SF)
Training Provider: TRAINING VISION INSTITUTE PTE. LTD.
Course Reference: TGS-2019503652
S$750
Original: S$1,500
Save S$750
About This Course
The learners will acquire the knowledge and understanding of mathematics needed to underpin the computing modules and to provide the mathematical toolbox of techniques for other units. The learners will also be equipped to carry out conversion numbers to various bases and perform simple binary arithmetic operations, use algebraic terminology to solve algebraic equations, perform simple statistical calculations and use Boolean algebra, Venn diagrams and logic networks.
What You'll Learn
1. Define range of statistical and advanced computational modelling techniques, advanced mathematical models and theories and develop mathematical models to isolate trends and optimise data-driven decision making. (K1, K2, A4)
2. Define elements of various algorithms and develop new algorithms to enable the learning, improvement, adaptation or reproduction of outcomes. (K3, A2)
3. Define features and applicability of various data models and develop regression models, including linear, multiple and logistic regression models (K4, A3)
4. Define features, pros and cons of various statistical approaches, algorithms and tools and facilitate changes to statistical models, to optimise performance and yield intended outcomes (K5, A8)
5. Develop testing procedures and use them to evaluate statistical models and data models. (K6, A6)
6. Define impact of changes to algorithms and models on performance outcomes and describe the underlying relationships among different variables. (K7, A10)
2. Define elements of various algorithms and develop new algorithms to enable the learning, improvement, adaptation or reproduction of outcomes. (K3, A2)
3. Define features and applicability of various data models and develop regression models, including linear, multiple and logistic regression models (K4, A3)
4. Define features, pros and cons of various statistical approaches, algorithms and tools and facilitate changes to statistical models, to optimise performance and yield intended outcomes (K5, A8)
5. Develop testing procedures and use them to evaluate statistical models and data models. (K6, A6)
6. Define impact of changes to algorithms and models on performance outcomes and describe the underlying relationships among different variables. (K7, A10)
Course Details
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