• Welcome to your new Gnomio site

    Now, you are in control!

    Moodle is an open-source Learning Management System (LMS) that provides educators with the tools and features to create and manage online courses. It allows educators to organize course materials, create quizzes and assignments, host discussion forums, and track student progress. Moodle is highly flexible and can be customized to meet the specific needs of different institutions and learning environments.

    Moodle supports both synchronous and asynchronous learning environments, enabling educators to host live webinars, video conferences, and chat sessions, as well as providing a variety of tools that support self-paced learning, including videos, interactive quizzes, and discussion forums. The platform also integrates with other tools and systems, such as Google Apps and plagiarism detection software, to provide a seamless learning experience.

    Moodle is widely used in educational institutions, including universities, K-12 schools, and corporate training programs. It is well-suited to online and blended learning environments and distance education programs. Additionally, Moodle's accessibility features make it a popular choice for learners with disabilities, ensuring that courses are inclusive and accessible to all learners.

    The Moodle community is an active group of users, developers, and educators who contribute to the platform's development and improvement. The community provides support, resources, and documentation for users, as well as a forum for sharing ideas and best practices. Moodle releases regular updates and improvements, ensuring that the platform remains up-to-date with the latest technologies and best practices.

    Links of interest:

    (You can edit or remove this text)

Available courses

Course Summary: Engineering Mathematics

Course Description:

Engineering Mathematics is a foundational course designed to equip students with the mathematical tools and analytical techniques necessary for solving engineering problems. It includes a study of advanced calculus, linear algebra, differential equations, complex analysis, and numerical methods, with applications in various engineering fields.


Course Objectives:

  • To develop the ability to model physical systems using mathematical concepts.

  • To provide a strong foundation in calculus, algebra, and differential equations.

  • To introduce numerical and analytical methods for problem-solving.

  • To enhance logical reasoning and mathematical thinking skills.


Major Topics Covered:

  1. Linear Algebra:

    • Matrices and determinants

    • Systems of linear equations

    • Eigenvalues and eigenvectors

    • Vector spaces

  2. Calculus:

    • Limits, continuity, and differentiability

    • Partial differentiation and applications

    • Multiple integrals and their applications

    • Vector calculus (gradient, divergence, curl, line and surface integrals)

  3. Differential Equations:

    • First and second-order ordinary differential equations (ODEs)

    • Solutions of linear differential equations

    • Applications in physical and engineering systems

    • Laplace transforms and their applications

  4. Complex Numbers and Complex Analysis:

    • Complex functions

    • Analytic functions

    • Cauchy’s theorem and integral formula

    • Taylor and Laurent series

    • Residue theorem

  5. Numerical Methods:

    • Solutions of nonlinear equations

    • Numerical integration and differentiation

    • Numerical solutions to ODEs

    • Interpolation and curve fitting

  6. Probability and Statistics (optional/extended):

    • Probability distributions

    • Descriptive statistics

    • Hypothesis testing

    • Regression and correlation


Learning Outcomes:

By the end of the course, students should be able to:

  • Apply mathematical methods to analyze engineering systems.

  • Solve differential equations relevant to mechanical, electrical, and civil engineering.

  • Use linear algebra in systems modeling and control.

  • Implement numerical methods for engineering simulations.

  • Interpret and analyze data using probability and statistics (if included)