About the Programme|
Computers are machines that manipulate abstract symbols according to specified rules. Therefore, computer science relies heavily on abstract reasoning and mathematics. The mathematics involved is usually quite different. However, from traditional mathematics one can then learn computer mathematics. Much of it has been developed recently in response to the development of computers. Bachelor of Science programme in Mathematics and Computer Science offers a blended degree programme of Mathematics and Computer Science. This degree programme is designed to engage with and complement the existing programmes from both, the School of Mathematics, Statistics and Actuarial Science and the School of Informatics and Computer Science.
Objectives
The main objectives of this programme are to:
• Equip the learner with a solid foundation in mathematics and computer science.
• Prepare learners for postgraduate studies and research in mathematics or computer science.
• Prepare learners for independent work as computer hardware or software specialist.
• Prepare learners for a career in scientific, banking or business areas requiring mathematical, statistical or computing background.
Programme Courses
Year 1: Semester 1 | |
MMA 100 | Basic Mathematics |
MMA 109 | Foundation of Pure Mathematics |
MMA 111 | Introduction to Calculus |
MAS 103 | Introduction to Probability Theory |
MAS 101 | Descriptive Statistics |
CCS 103 | Discrete Structures I |
CCS 101 | Fundamentals of Computing |
CCS 111 | Introduction to Programming |
CCS 107 | Electronics |
Year 1: Semester 2 | |
MMA 101 | Analytical Geometry |
MMA 103 | Linear Algebra I |
MMA 110 | Foundation of Applied Mathematics |
MAS 102 | Probability and Distribution Theory I |
CCS 104 | Object Oriented Programming |
CCS 106 | Discrete Structures II |
CCS 108 | Digital Electronics I |
CCS 110 | Introduction to Internet Technologies |
MIT 102 | Handling Data |
MIT 104 | Descriptive Statistical; Analysis and Presentation |
PHT 112 | HIV/AIDS |
Year 2: Semester 1 | |
MMA 202 | Vector Analysis |
MMS 215 | Calculus |
MMA 217 | Numerical Convergence |
MMA 221 | Introduction to Number Theory |
CCS 201 | Object Oriented Programming II |
CCS 203 | Data Structures and Algorithms |
CCS 207 | Digital Electronics II |
CCS 209 | Principles of Operating Systems |
CCS 213 | Systems Analysis and Design |
MIT 201 | Statistical Computing I |
MIT 203 | Collecting and Organising Data |
Year 2: Semester 2 | |
MMA 201 | Linear Algebra II |
MMA 206 | Algebraic Structures |
MMA 208 | Introduction to Analysis |
MMA 216 | Multivariate Calculus |
MMA 219 | Graph Theory |
MAS 202 | Principles of Statistical Inference |
CCS 202 | Computer Organisation and Architecture I |
CCS 206 | Application Development for the Internet |
CCS 210 | Automata Theory |
CCS 212 | Web Design and Publishing |
CCS 214 | Group Project I |
MIT 202 | Data Management |
MIT 204 | Scientific Report Reading, Writing and Presentation |
Year 3: Semester 1 | |
MMA 300 | Real Analysis I |
MMA 301 | Ordinary Differential Equations I |
MMA 307 | Methods I |
MMA 308 | Fluid Mechanics I |
MMA 319 | Numerical Mathematics I |
CCS 301 | Principles of programming languages |
CCS 307 | Computer Networks |
CCS 303 | Design and Analysis of algorithms |
CCS 305 | Compiler Construction and Design |
CCS 309 | Information Systems Security and Design |
CCS 317 | Computer Networks LabI(CISCO) |
CCS 319 | Database Administration |
CCS 308 | Electronic Commerce |
MIT 301 | Computer based Survey Techniques |
MIT 303 | Computers applied to Mathematics |
MAS 303 | Estimation Theory |
MAS 305 | Stochastic Processes I |
MAS 307 | Theory of sampling Techniques |
MAS 309 | Time Series Analysis and Forecasting |
MAS 311 | Statistical Demography I |
MAS 313 | Principles of Econometrics |
MAS 315 | Statistical Genetics |
Year 3: Semester 2 | |
MMA 302 | Linear Algebra III |
MMA 303 | Complex Analysis I |
MMA 304 | Group Theory I |
MMA 309 | Real Analysis II |
MMA 310 | Dynamics II |
MMA 312 | Operations Research I |
MIT 302 | Statistical Computing II |
MIT 304 | Introduction to object oriented programming |
CCS 304 | Human Computer Interaction |
CCS 306 | Software Engineering |
CCS 310 | Computer Graphics |
CCS 308 | Research Methods and Technical Writing |
CCS 314 | Computer Networks LabII(CISCO II) |
CCS 316 | Network Administration |
CCS 320 | Financial and Management Accounting |
CCS 304 | Computer Science Project II |
MAS 302 | Mathematical Methods |
MAS 304 | Test of Hypotheses |
MAS 306 | Statistical Modelling |
MAS 308 | Analysis of Experimental Designs I |
MAS 310 | Stochastic Decision Models I |
MAS 314 | Research Methodology |
Year 3: Semester 3 | |
MAS 317 | Industrial Attachment |
Year 4: Semester 1 | |
MMA 401 | Ring Theory |
MMA 403 | Topology I |
MMA 404 | Complex Analysis II |
MMA 405 | Partial Differential Equations I |
MMA 409 | Differential Geometry |
MMA 412 | Fluids Mechanics II |
MMA 413 | Methods II |
MMA 417 | Group Theory II |
MMA 420 | Operation Research II |
MMA 431 | Numerical Mathematics II |
MIT 401 | Bayesian Modelling |
MIT 403 | Writing Macros |
CCS 405 | Management information systems |
CCS 401 | Software Project management |
CCS 407 | Distributed systems |
CCS 403 | Computer Science project I |
CCS 409 | Computer Networks LabIII(CISCO II) |
CCS 411 | Business Management |
CCS 413 | IT in Human Resources Management |
CCS 415 | Data Mining |
CCS 417 | Principles of Functional Programming |
CCS 419 | Advanced Computer Architecture |
CCS 421 | Intelligent Agents |
CCS 423 | Program Verification |
MAS 401 | Further Distribution Theory |
MAS 403 | Non Parametric methods |
MAS 405 | Analysis of Experimental Designs II |
MAS 407 | Further Time series Analysis |
MAS 409 | Further Sample Survey Theory and Methods |
MAS 411 | Stochastic Decision Models II |
MAS 413 | Stochastic Models for Biological Processes |
MAS 415 | Biometric Models |
MAS 417 | Statistical Demography II |
MAS 419 | Econometric Models I |
MAS 421 | Stochastic Processes II |
MAS 423 | Practical Statistics |
MAS 425 | Labour Dynamics |
MAS 427 | Agricultural Indices |
MAS 429 | Energy Analysis |
MAS 431 | Teaching of Statistics |
Year 4: Semester 2 | |
MMA 402 | Measure Theory |
MMA 407 | Field Theory |
MMA 408 | Topology II |
MMA 410 | Functional Analysis |
MMA 411 | Partial Differential Equations II |
MMA 414 | Fourier Analysis |
MMA 416 | Galois Theory |
MMA 418 | Algebraic Geometry |
MMA 429 | Operations Research III |
CCS 404 | Social Legal and ethical issues in Computing |
CCS 406 | Computer Science Project II |
CCS 408 | Computer Networks LabIV (CISCO IV) |
CCS 410 | Computational Science |
CCS 414 | Pattern Recognition |
CCS 420 | Neural Networks |
CCS 418 | Advanced Database Systems |
CCS 412 | Natural Language Processing |
MAS 402 | Bayesian Inference and Decision Theory |
MAS 406 | Robust Methods and Non-Parametrics |
MAS 408 | Multivariate Methods |
MAS 410 | Statistic Model Building |
MAS 412 | Stochastic Models for social Processes |
MAS 414 | Survey Research Methods |
MAS 416 | Quality Control Methods |
MAS 418 | Applied Population Analysis |
MAS 420 | Applied demography |
MAS 422 | Econometric Models II |
MAS 424 | Applied Econometrics |
MAS 426 | Statistical Computing III |
MAS 428 | Response Surface Methodologies |
MAS 430 | Educational Statistics |
MAS 432 | Health Indicators |
MAS 434 | Government Financial Structure |
MAS 436 | Environmental / Ecological Indicators |
MAS 438 | Statistical Organization |
MIT 402 | Problem based Statistical Analysis |
Programme Requirements
Admission Requirements
Applicants eligible for admission into the program must:
• Satisfy the minimum entry requirements for admission to the University and the School of Mathematics, Statistics and Actuarial Science.
• Attain a B-(minus) in Mathematics at KCSE or equivalent.
Duration of the Programme
The duration of the program shall normally be four (4) academic years.
Teaching methods in all units shall include lectures, seminars, tutorials, discussions.
Degree Structure
The program offers courses within the degree structure spelled out by the Faculty.
Course Structure
• The Department offers courses in terms of units as defined by the faculty.
• There shall be CORE, ELECTIVE and REQUIRED courses. Core courses are mandatory, while Elective and Required courses may be chosen by students as preferred in fulfilling the full-time load requirement.
• A student will take a minimum of 14 and a maximum of 16 units in each year of study. Students wishing to take more than 16 units will require Senate approval.
• There shall be an industrial attachment at the end of third year.