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Curriculum Studies in Physics

This course is designed to offer students the opportunity to discuss the Senior High School curriculum in Physics, including the basic principles of curriculum development.  Students will be exposed to the factors that influence the development, design, implementation and evaluation of curriculum. 

This course introduces students to the various theories of curriculum development. It covers the various factors that influence curriculum development. Students will learn how to select and organize learning experiences. Curriculum implementation and evaluation will be covered in this course. Students will be exposed to how to interpret the Physics syllabus.

Course Code: 
ESC220
No. of Credits: 
3
Level: 
Level 200
Course Semester: 
Second Semester
Select Programme(s): 
Science

Electronics I (Practicals)

This is the practical component of PHY 204 and is designed to help students gain hands-on experience with laboratory equipment with regards to electronic components and devices. Such experiments would include the construction and testing of half-wave and full-wave rectifiers, step-up and step-down transformers.

Course Code: 
PHY 208
No. of Credits: 
1
Level: 
Level 200
Course Semester: 
Second Semester
Select Programme(s): 
Meteorology and Atmospheric Physics
Science

Measure and Integration

This course covers advanced topics in abstract measure theory and Lebesgue integration. Topics covered include: measurable sets and functions, measure spaces, Lebesgue integral, monotone convergence theorem, Fatou’s lemma, Lebesgue dominated convergence theorem, Vitali’s theorem, decomposition of measures, Caratheordory and Hahn extension theorem,  spaces, Riesz representation theorem, and product measures.

Course Code: 
MAT802
No. of Credits: 
3
Level: 
Level 800
Course Semester: 
Second Semester
Pre-requisite: 
MAT 408 and MAT 801
Select Programme(s): 
Mathematics
Mathematics
Mathematics

Electricity and Magnetism Practicals

Electricity and Magnetism Experiments

Course Code: 
PHY206
No. of Credits: 
1
Level: 
Level 200
Course Semester: 
Second Semester
Select Programme(s): 
Science

General Topology

 This course is about the study of properties of topological spaces. Topological spaces turn up naturally in mathematical analysis, abstract algebra and geometry. A topological space is a structure that allows one to generalize concepts such as convergence, connectedness and continuity. Topics covered include: open and closed sets, neighbourhood, basis, convergence, limit point, completeness, compactness, connectedness, continuity of functions, separation axioms, subspaces, product spaces, and quotient spaces.

Course Code: 
MAT 801
No. of Credits: 
3
Level: 
Level 800
Course Semester: 
First Semester
Pre-requisite: 
MAT 430
Select Programme(s): 
Mathematics
Mathematics
Mathematics

Electronics I

This is a foundation course in analogue Electronics and is meant to provide a comprehensive overview of the scope and dynamics of electricity and the fact that electronic refers to a extremely wide range of electrical technology.  Students will be introduces to the building blocks of electronics such as the semiconductor, power supplies, operational amplifiers, attenuators and transducers.  Students will learn the theory and mathematics that govern the workings of the components that make up an electronic system.

Course Code: 
PHY204
No. of Credits: 
2
Level: 
Level 200
Course Semester: 
Second Semester
Select Programme(s): 
Science

Electricity and Magnetism

This course is an extension of the electricity and magnetism basics introduced in PHY102.  It is designed to improve students understanding of electric and magnetic phenomena.  The course covers basic computation of electric and magnetic fields, calculation of electric potentials and their applications.  A.C. theory and electromagnetic waves and their related calculations are covered. Application of RCL circuit is discussed.  

Course Code: 
PHY202
No. of Credits: 
2
Level: 
Level 200
Course Semester: 
Second Semester
Select Programme(s): 
Science

Methods of Teaching Biology

This course requires student-teachers to scaffold learning; practice how to promote active engagement of the learner; expose and discuss common misconceptions; organize the syllabus into schemes of work and further into lesson notes; use assessment as a means of advancing learning; develop effective and interactive teaching techniques and styles; and use collaborative rich tasks to engage science students in co-operative small group work.

Course Code: 
ESC208
No. of Credits: 
3
Level: 
Level 200
Course Semester: 
Second Semester
Select Programme(s): 
Science

Curriculum Studies in Biology

This course is designed to offer students the opportunity to discuss the Senior High School curriculum in biology, including the basic principles of curriculum development.  Students will be exposed to the factors that influence the development, design, implementation and evaluation of curriculum. 

This course introduces students to the various theories of curriculum development. It covers the various factors that influence curriculum development. Students will learn how to select and organize learning experiences. Curriculum implementation and evaluation will be covered in this course. Students will be exposed to how to interpret the biology syllabus.

Course Code: 
ESC214
No. of Credits: 
3
Level: 
Level 200
Course Semester: 
Second Semester
Select Programme(s): 
Science
Degree Type: 
Master of ScienceDepartment of Mathematics
Programme Duration: 
2 years (Standard Entry)
About Programme: 

In the case of MSc. Programme, without dissertation, students must select courses to attain a minimum of 30 credits of coursework.

The M.Sc programmes are over a twelve-month period involving two semesters of course work.

Objectives 

  • To produce pure mathematics graduates who can undertake research work and create new concepts.

  • To produce applied graduates who can use mathematics as a tool to do research work in other disciplines such as physics, biology and economics.

  • To provide a solid foundation for students to pursue advanced and specialised courses in the mathematical sciences.

 

9 READING LIST 

                             

  1. Adams,  A. R. (2003). Calculus, A Complete Course, 6th Ed. Addison Wesley Longman.

  2. Ahlfors,  L. (1979).  Complex Analysis, McGraw-Hill.

  3. Allan, J. (2002). Advanced Engineering Mathematics, Harcourt/Academic Press, USA.

  4. Allen L, J.S. (2007). An Introduction to Mathematical Biology,  Pearson Education, New Jersey, USA

  5. Anderson, A. & May, R.  (1991). Infectious Diseases of Humans: Dynamics and Control,  Oxford University Press, London. United Kingdom.

  6. Anderson, D. R., Sweeney, D. J. & Williams, T. A. (1988). An Introduction to Management Science: Quantitative Approaches to Decision Making; 5 Ed., West Pub. Co., USA.

  7. Anton, H. & Rorres, C. (1988 ). Elementary Linear Algebra, Applications Version, John Wiley, New York, USA.

  8. Axler, S. (1997).  Linear Algebra Done Right, Springer. 

  9. Bak, J. & Newman, D. J. (2010). Complex Analysis, Springer-Verlag, New York.                             

  10. Betts, J. T. (2001). Practical Methods for Optimal Control Using Nonlinear   

      Programming, SIAM, Philadelphia, USA.

  1.  Berenstein, C. A. (1985). Complex Analysis; Springer-Verlag, New York.

  2. Bick, T. A. (1971 ). Introduction to Abstract Mathematics; Academic Press.

  3. Birkhoff, G. and Rota, G. (1989).  Ordinary Differential Equations; John Wiley and Sons.

  4. Boyce, W. E. & DiPrima, R. C. (2006).  Elementary Differential Equations And Boundary Value Problems, Prentice Hall, New Jersey, USA.

  5.   Brauer, F. (2006).  Some Simple Epidemic Models, Mathematical biosciences and  

  6. Brauer, F., Castillo-Chavez, C. (2012). Mathematical Models for Communicable 

  7. Brian D, Hahn, (2007). Essential MATLAB for Scientists and Engineers, Pearson Education, South Africa.

  8. Broman, A. (1970). Introduction to Partial Differential Equations; Dover, USA.

  9. Brown, J. & Churchill, R. (1996). Complex variables and applications, 7th Ed. 

  10. Brown, J. W. & Sherbert, D. R. (1984). Introductory Linear Algebra with Applications, PWS, Boston.

  11. Bryson, A. E. & Ho, Y. (1975).  Applied optimal control: Optimization, Estimation  

  12. Budak, B. M., & Fomin S. (1973). Multiple Integrals, Field Theory and Series; Mir Publishers, Moscow.

  13. Burden, R. & Faires, J. D.  (2006), Numerical Analysis, PWS Publishers

Diseases, SIAM, Philadelphia, USA.  

  1. Capinski, M. &  Kopp, E. (2005), Measure, Integral and Probability,   Springer-Verlage London Limited.                

  2. Christian, P., Nagy, J. G.  Dianne & O’Leary, D., (2006), Deblurring Images, Matrices, Spectra, and Filtering. SIAM , Philadelphia, USA.

  3. Churchill, R. V. & Brown, J. W (1990 ). Complex Variables and Applications; McGraw Hill Inc., USA.

  4. Coddington, E.A. & Levinson, N. (1983), Theory of Ordinary Differential Equations; Robert Krieger Publishing Company, Malabar, Florida.

  5. Courant, R., & John, F. (1974). Introduction to Calculus and Analysis; Vol. 2, John Wiley and Sons, USA.                         

  6. Daellenbach, H. G., George, J. A. & McNicke, D.C. (1983). Introduction to Operations Research Techniques; 2 Ed., Allyn and Bacon, Inc., USA.

  7. Datta, B. N.  (2009), Numerical Linear Algebra and Applications, SIAM, Philadelphia, USA.

  8. David, C. L. (2002). Linear Algebra and its Applications, Addison-Wesley, New York, USA.

  9. De-Lillo, N. J. (1982). Advanced Calculus with Applications; Macmillan Pub., USA.

  10. Diekmann, O. & Heesterbeek, J.A. P.  (2000). Mathematical Epidemiology of Infectious Diseases, John Wiley & Sons, West Sussex.

  11. Edwards, C. H. & Penny, D. E. (2005).  Elementary Differential Equations With Boundary Value Problems, Prentice Hall, New Jersey, USA

  12. Edwards,  C. H. & Penney, D. E. (1999). Calculus With Analytic Geometry: Early Trancendentals; 5 Prentice Hall Inc., USA.

  13. Eisberg, R.M. (2000). Fundamentals of Modern Physics, John Wiley & Sons Inc. New York.      

  14. Evans, C. L. (2010). Partial Differential Equations, American Mathematical Society.                 

  15. Fiacco, A. V. &  McCormock, G. P. (1990). Nonlinear Programming, SIAM, Philadelphia, USA.

  16. Fraleigh, J. B. (1989). A First Course in Abstract Algebra.

  17. Froberg E. (1968). Introduction to Numerical Analysis, Addison and Wesley, USA.

 Philadelphia, USA.                        

  1. Gallian, J. A.  (1990), Contemporary Abstract Algebra; D. C. Heath and Company.

  2.  Gerald, C. F. & Wheatley (2001)  Applied Numerical Analysis; Addison &Wesley, USA.

  3.  Gibarg, D. & Trudinger, N. S. (1983). Elliptic Partial Differential Equations of Second  Order; Springer-Verlag, New York.

  4. Goldstein, H. (1986).  Classical Mechanics, Addison-Wesley Publishing Company.                  

  5. Haaser, N. B. & Sullivan, J. A. (1991). Real Analysis; Dover.

  6. Halmos, P.R. (1960), Measure Theory; Springer-Verlag, New York.

  7. Hertcote , H. W. (2000). The Mathematics of Infectious Disease, SIAM Review,  Amsterdam, The Netherlands.

  8. Higham , D. J.  (2005). MATLAB Guide, SIAM, Philadelphia, USA.

  9. Hilberland, F. B. (1962). Advanced Calculus for Application; Prentice Hall, USA.

  10. Hillier, F. S. (2012). Introduction to Operations Research, McGraw Hill, Inc., USA.

  11. Hirsch, M. W, Smale, S. & Devaney, R. L. (2004).  Differential Equations,         Dynamical Systems & An Introduction to CHAOS, Elsevier Academic Press,  

  12. Hocking, L. M. (1991), Optimal Control: An Introduction to the Theory with Applications, Clarendon Press, London.

  13. Hungerford, T. W. (1974). Algebra; Springer-Verlag, New York.

 Vol 42, No. 4, December 2000, pp. 599—653.         

  1. Igor G., Nash, S. G. & Sofer A., (2009). Linear and Nonlinear  Optimization, SIAM, Philadelphia, USA.

  2. Kaufmann, J. E. (1987). College Algebra and Trigonometry; PWS Publishers, USA.

  3. Kirk , D. E., (2004), Optimal control theory: An Introduction, Dover Publications.

  4. Klages, R. & Howard, P. (2008),  Introduction to Dynamical Systems, (Lecture         Notes Version 1.2), Queen Mary University of London.

  5. Kofinti, N. K. (1997). Mathematics Beyond the Basic; Vol. 1, City Printers, Accra.

  6. Kolman, B. (1984). Introductory Linear Algebra with Applications; Macmillan Publishing Company.

  7. Kreyszig, E. (1978 ). Introductory Functional Analysis with Applications; John Wiley and Sons,  New York, U.S.A.

  8. Kudryavtsev, V. A. (1981). A Brief Course of Higher Mathematics; Mir Publishers, Moscow.  

  9. La Salle, J. P.  (1976), The Stability of Dynamical Systems, SIAM, Philadelphia, USA.

  10. Lang, S. (2012). Calculus of Several Variables, Springer-Verlag, New York.

  11.  Lenhart S., & Workman J. T., (2007), Optimal Control Applied to Biological         Systems, Chapman & Hall, New York, USA.

  12.  Lenhart, S., & Workman, J. T. (2007). Optimal Control Applied to Biological, John Wiley & Sons, New York, USA.   

  13.  Levine, I.N.  (1991). Quantum Chemistry, 4th Ed., Prentice Hill.

  14.  Levy, A. B.  (2009). The Basics of Practical Optimization, SIAM, Philadelphia,            USA.

  15. Levy, A. B. (2009). The Basics of Practical Optimization and Control, SIAM, Philadelphia, USA.

  16.  Linz, P. &  Wang, R. (2002). Exploring Numerical Methods: An Introduction to Scientific Computing Using MATLAB, Jones & Bartlett Publishers, London.

  17. Lipschuts, S.  (1975), General Topology; McGraw-Hill Book Company.

  18. Liu, J. H. (2003). A First Course in the Qualitative Theory of Differential Equations, Pearson Education, Inc., New Jersey.

  19.  Luenberger, D. G., (1996). Optimization by Vector Space Methods, John Wiley & Sons, New York, USA.    

  20. Marion, J.B. & Thornton, S.T. (1995).  Classical Dynamics of Particles and Systems, Saunder College Publishers.

  21. Marsden, J.E. (1970). Basic Complex Analysis; W.H. Freeman and Co.

  22. McCann, R. C. Introduction to Ordinary Differential Equations; Harcourt Brace Janovich, USA.

  23. McCoy, N. H. (1968). Introduction to Modern Algebra; Allyn and Bacon Inc.,

  24. Merzbacher, E.  (1986). Quantum Mechanics, 2nd Ed. John Wiley & Son Inc.

  25. Morash, R. P. (1987). A Bridge to Abstract Mathematics; Random House Inc., New York.

  26. Munem, M. A. (1989). After Calculus: Analysis; Collier Macmillan Pub. , London.

  27. Nicholson, K. W. (1986). Elementary Linear Algebra with Applications; PWS-KENT.

  28.  Ortega, J. M. (1990), Numerical Analysis, SIAM, Philadelphia, USA.

 Philadelphia, USA.

  1.  Offei, D.N.  (1970), The use of boundary condition functions for non-self-adjoint boundary value problems; I

  2.  Offei, D. N. (1969). Some asymptotic expansions of a third-order differential equations; Journal of London Mathematical Society, 44 71-87.

  3. Penny, J. & Lindfield, G.  (1995), Numerical Methods Using MATLAB, Ellis Horwood, New York.

  4. Petrovsky, I. G.(1954 ).  Lectures on Partial Differential Equations; Dover, USA.

  5. Pinchover, Y. & Rubinstein, J. (2005). An Introduction to Partial Differential Equation, Cambridge University Press.

  6. Piskunov, N. (1981). Differential and Integral Calculus; 4 Ed., Mir Publishers, Moscow.

  7.  Pliska, S. R.  (2002). Introduction to mathematical finance: Discrete time models, Blackwell Publishers Inc. 

  8.  Poole, D. (2014). Linear Algebra: A Modern Introduction, Dover, USA.

  9. Priestley, H. A. (2003). Introduction to Complex Analysis, 2nd  Ed., OUP.

  10. Redheffer, R. (1992). Introduction to Differential Equations; Jones & Bartlett Pub., Inc.

  11.  Roberts, A. J.  (2009), Elementary Calculus of Financial Mathematics, SIAM, Philadelphia, USA.

  12.  Rofman, J. J. (2015). Advanced Modern Algebra, American Mathematical Society.

  13. Roman, S. (2005), Advanced Linear Algebra, 2nd edn; Springer-Verlag, New York.

  14. Ross, S. L. (1984). Differential Equations; 3 Ed., John Wiley & Sons, USA.

  15. Rudin, W. (1974), Principles of Mathematical Analysis; McGraw-Hill Book Company.

  16. Savin, A. & Sternin, B. (2017). Introduction to Complex Theory of Differential Equations, Birkhauser.

  17.  Scheid, F.  (1988). Numerical Analysis (Schaum Series); McGraw Hill, USA.

  18. Schiff, L.I. (1988). Quantum Mechanics, 3rd Ed., McGraw Hill, New York.

  19. Simmon, G.F. (1973), Introduction to Topology and Modern analysis; McGraw-Hill. 

  20. Smith, K. L. (1988). College Mathematics and Calculus With Applications to Management, Life and Social Sciences; Brooks/Cole Publishing Co., California, USA.

  21. Speyer,  J. L. & Jacobson, D. H. (2010). Primer on Optimal Control Theory, SIAM.

  22. Spiegel, M. R. (1991 ). Complex Variables (Schaum Outline Series); McGraw Hill Inc.

  23. Spiegel, M.R. (1992), Real Variables:  Lebesque Measure and Integration with Applications to Fourier Series; MacGraw-Hill  

  24. Spiegle, M. R. (1991). Advanced Calculus; McGraw Hill, USA.

  25. Stewart J. (1983). Single Variable Calculus; PWS, USA.

  26. Stewart, J. (1987). Calculus; Wadsworth Inc.

  27. Stewart, J. (2003). Calculus (Early Transcendental), 6th Ed. Thomson Brooks/Cole.

  28. Strang, G. (2006). Linear algebra and Its Applications, Thomson Brookes/Cole,  

California, USA.

  1. Strauss, W. A. (1992). Partial Differential Equations, an Introduction; John Wiley &  

Sons Inc. New York. 

  1. Sun, W. & Yuan, Y. (2006), Optimization Theorey and Methods: Nonlinear  

Programming, Springer, New York, USA. 

  1. Swokowski, E. W. (1984). Calculus With Analytic Geometry; 3 Ed. Prindle, Weber 

  and Schmidt, Boston, USA.

  1. Symon, K.R.  (1973). Mechanics, Addison-Wesley Publishing Company

      Systems, Chapman & Hall, New York, USA.

  1. Taylor, A.E. & Lay, D.C.  (1988), Introduction to Functional  analysis; John Wiley 

 and Sons.

  1. Teschle, G., (2010). Ordinary Differential Equations and Dynamical Systems:  

 Graduate Studies in Mathematics, AMS Vol 140, Providence, Rhode Island, USA

  1. Thomas, G. B. and Finney, R. L. (1996). Calculus and Analytic Geometry; 9 Ed. 

 Addison-Wesley Pub., Reading, USA.

  1. Titchmarsh, E.C. (1972), Eigenfunction expansions associated with second-order 

 differential equations; Oxford University Press.

  1. Trefethen, L. N., &  Bau, D. ( 1997). Numerical Linear algebra ,SIAM, Philadelphia, 

USA.

  1. Winston, W. L. (1994). Operations Research: Applications and Algorithms; 3rd Ed., 

Duxbury Press, Belmont, USA.

  1. Winter, R.G. (1986).  Quantum Physics, 2nd Ed., Faculty Publishing Inc.

Zill, G. D. (2012). A First Course in Differential Equations with Modelling Applications, John Wiley and Sons.

Career Opportunities: 

Not Published

Entry Requirements: 

POST-GRADUATE ADMISSION REQUIREMENT

  • For the M.Phil/M.Sc in Mathematics, a good first degree in Mathematics, preferably in First Class or Second Class Upper Division, is required. 

  • For the Ph.D in Mathematics, an M.Phil  in Mathematics is required. 

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