Courses Under Industrial Mathematics Degree
On this article, I am going to list out all Industrial Mathematics course outline in Nigeria Universities which you will study before you can to become a graduate of Industrial Mathematics. Normally, a course outline should contain; course name, course description, course hours etc… but I am going to skip that information and go straight to Industrial Mathematics subjects for university students.
I will only list out the course names excluding GST Courses and those courses with part II and III to avoid too much information. There is no guarantee that the listed Industrial Mathematics subjects (courses) will be fully covered in your school because universities in Nigeria does not use a uniform curriculum.
Nevertheless, you will study 97% of Industrial Mathematics courses listed here.
The following Industrial Mathematics courses in Nigeria listed here do not follow the traditional course structure and they have been arranged in alphabetical order. Notwithstanding, the list here covers 100 level courses, 200 level courses 300 courses and 400 level courses.
The following are the list of Industrial Mathematics Courses in Nigeria
- Classical Mechanics
- Computer Programming
- Control Theory and Optimization
- Control Theory and Project Management
- Discrete Mathematics
- Distribution Theory
- Elasticity
- Elementary Differential equations
- Elementary Mathematics
- Financial Mathematics
- Fluid Dynamics
- General Biology
- General Chemistry
- General Physics
- Introduction to Computer Science
- Introduction to Industrial Mathematics
- Introduction to numerical analysis
- Introduction to Operations Research
- Library Studies
- Linear Algebra
- Mathematical Computing
- Mathematical Methods
- Mathematical Modelling
- Nigerian People and Culture
- Numerical Analysis
- Optimization Theory
- Ordinary Differential Equations
- Probability
- Real Analysis
- Sets Logic and Algebra
- Special Topics in Industrial Mathematics
- Statistical Inference
- Systems Theory
- Theory and Applications of Neural Networks
- Theory and Applications of Ordinary Differential Equations
- Theory and Applications of Partial Differential Equations
- Vector Analysis
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