Master’s in Applied Mathematics and Computational Science (AMCS)

The NM-AIST will admit competitively qualified students mainly from the Eastern African Region and Sub-Saharan Africa. Entry requirement for successful participation in the Master of Applied Mathematics and Computational Science Program should be as follows:

(a)  Master’s by Coursework and Dissertation

  1. Possession of at least a second class Bachelor’s degree with at least a GPA of 3.0/5.0 or its equivalent or a postgraduate diploma with at least a GPA of 4.0/5.0 or its equivalent in an appropriate area of study from an accredited university or similar institution of higher learning. For an applicant holding unclassified degrees (e.g. M.D, BVM & DDS) should have at least an overall of “C” grade and an average of “B” grade in the relevant subject or field of his/her specialization.
  2. The applicant must satisfy the Programme and specialty specific requirements as specified by the respective School/Department hosting the programme
  3. The applicant may be expected to pass an entry assessment, which may take one of the following methods: (1) personal interview, (2) written assessment, (3) interview plus written assessment, or (4) assessment exemption (on justifiable grounds).

(b)  Master’s by Research and Thesis

  1. Possession of a Bachelor’s degree from an accredited university or similar institution of higher learning with a GPA of at least 3.5/5.0 or its equivalent in an appropriate area of study from an accredited university or similar institution of higher learning. For an applicant holding unclassified degrees (e.g. M.D, BVM & DDS) should have at least an overall of “C” grade and an average of “B” grade in the relevant subject or field of his/her specialization and, either (a) Possession of a prototype that requires incubation/scaling up in line with NM-AIST’s research and innovation policy and guidelines, or (b) Evidence of at least ONE year working experience in related field and at least ONE publication in an accredited peer-reviewed journal as the FIRST author.
  2. Submission along with application documents, a concise ONE-page concept note or details of a prototype of what he/she wishes to work on as part of his/her study provided it is within the NM-AIST research agenda.
  3. The applicant should be ready to pursue prescribed skills and capacity enhancing courses which are offered to all Master’s students at NM-AIST as common core courses and as may be recommended by the supervisors, to enhance research performance. The courses may be taken flexibly during the duration of the programme but MUST be successfully completed before graduation.

Areas of Specialization

  1. Operations Research (OR)
  2. Computational Mathematics Techniques (CMT)
  3. Probability, Stochastic, and Discrete Mathematics (PSDM)

Programme Duration

  1. Status: Full Time
  2. Years: Two (2) Years
  3. Semesters: Four (4)

Mode of Delivery

Face to face, Mixed (Mixed-mode (also known as blended or hybrid mode) are delivery modes where a portion of the traditional face-to-face instruction is replaced by web-based online learning)

Programme Outline for Master’s in Applied Mathematics and Computational Science by Coursework and Dissertation

Common Core Courses

  1. BuSH 6007: Foundation of Law Philosophy and Ethics
  2. BuSH 6008: Technological Innovation and Entrepreneurship Management

Programme Core

  1. CCSE 6001: Research Methods and Communication
  2. CCSE 6011: Outreach and Internship
  3. AMCS 6011: Computer Programming with MATLAB and Python
  4. AMCS 6012: Ordinary and Partial Differential Equations and their Numerical Methods
  5. AMCS 6402: Graduate Seminar
  6. AMCS 6199: Dissertation

Specialty Courses

  1. *AMCS 6201 Numerical Optimization
  2. AMCS 6202 Fluid Mechanics
  3. ***AMCS 6203 Machine Learning Theories and Applications

* Speciality for: Operations Research (OR)

**Speciality for Computational Mathematics Techniques (CMT)

***Speciality for Probability, Stochastic, and Discrete Mathematics (PSDM)

Elective Courses for Operations Research (OR)

  1. AMCS 6301 Combinatorial and Discrete Optimization
  2. AMCS 6303 Probability and Stochastic Methods
  3. AMCS 6302 Optimal Control and Calculus of Variations
  4. AMCS 6305 Data Analytics

Elective Courses for Computational Mathematics Techniques (CMT)

  1. AMCS 6303 Probability and Stochastic Methods
  2. AMCS 6306 Data Mining
  3. AMCS 6304 Numerical Linear Algebra
  4. AMCS 6305 Data Analytics

Elective Courses for Probability, Stochastic, and Discrete Mathematics (PSDM)

  1. AMCS 6303 Probability and Stochastic Methods
  2. AMCS 6307 Financial Mathematics
  3. AMCS 6308 Discrete Mathematics
  4. AMCS 6309 Dynamical Systems for Biological and Chemical Processes

Programme expected learning outcomes 

Knowledge

­­­­­­­­­­­By the end of the Programme, graduates of Masters in AMCS will be able to:

  1. Identify and classify adequate mathematical and computational methods and techniques and use them to solve real life problems.
  2. Understand the key criteria of a conducting a research and communication strategy to disseminate the research output

Skills

By the end of the Programme, graduates of Masters of AMCS will able to:

  1. Evaluate and select mathematical methods to solve given models,
  2. Design algorithms, write computer programmes/ codes using either MATLAB, or Python, or R programming languages, use codes to solve the models, do simulations, produce results and graphics, and write reports
  3. Conduct a research and properly communicate research output

Competence

By the end of the Programme, graduates of the Masters in  AMCS will be able to:

  1. Investigate and analyse existing mathematical models of real life problems; and
  2.  Derive and develop new computational techniques and evaluate their applicability.