This course provides engineering students with a strong foundation in differential equations as a prerequisite for advanced engineering and mathematics courses. It covers first-order differential equations, higher-order linear differential equations, systems of first-order linear differential equations, and the application of Laplace transforms in solving differential equations. Emphasis is placed on the application of differentiation and integration techniques, the identification and classification of differential equations, the determination of the existence and uniqueness of solutions, and the selection of appropriate analytical methods for obtaining and interpreting solutions. Students will develop the ability to model and analyze practical engineering and scientific problems using differential equations and utilize computational tools to solve, verify, and interpret mathematical solutions in real-world engineering applications. CMO 101, CMO 88 Series 2017
The course is designed for undergraduate engineering students with emphasis on problem-solving related to societal that engineers and scientists area called upon to solve. It introduces different methods of data collection and the suitability of using a particular methods for a given situation. It includes coverage and discussion of the relationship of probability to statistics, providing students with tools they need to understand how “chance” plays a role in statistical analysis. Probability distributions of random variables and their uses, are also considered, along with a discussion of linear functions of random variables within the context of their application to data analysis and inference. The course also include estimation techniques for unknown parameters, and hypothesis testing used in making inferences from sample to population, inference for regressions parameters and build models for estimating means and predicting future values of key variables under study Finally, statistically based experimental design techniques and analysis of data are discussed with the aid of relevant statistical software.
understanding of electronic components and their applications while emphasizing their crucial role in contributing to sustainable development. Through hands-on learning and theoretical concepts, students will gain insights into various electronic devices, diode and transistor characteristics and models (BJT and FET), diode circuit analysis, transistor biasing, small and large signal analysis, transistor amplifiers, Boolean logic, and transistor switches.