Program Profile

The Master of Science Degree in Information Science (Data Science and Analytics) program has the following profiles:

General course contents

It includes foundation courses, elective-courses, bridging courses, research and professional skill courses.

Course breakdown by semester

The master program will have a total of 36 credit hours

Admission Requirements

The admission requirement for the program shall be:

  • Open to all Science and engineering graduates of University of Gondar and other Universities approved by Senate of University of Gondar.
  • Preference could be given to candidates with Information Science, Information Studies, library and Information Science, Computer Science, Information Technology, Information Systems, Health Informatics, Software Engineering, Computer Engineering, Mathematics, Statistics. and having passed an entrance examination by the Department of Information Science;
  • Any applicant, who did not take the course listed in bridge courses, will be required to take.
  • Candidate must be supported by letters of recommendation from appropriate body or faculties. Such letters of recommendations should preferably come from instructors or employers and other conditions as obtained by University of Gondar for graduate programs.

Duration of the study

The program is for four semesters/two academic years. It comprises two semester/one academic year course work and the other two semester/second academic year shall be for Internship and thesis work.

Graduation Requirements

The major graduation requirements of the program are fulfilling the graduation requirements set by the University of Gondar senate legislation.

Degree Nomenclature

The English title of the degree shall be:

Master of Science Degree in Information Science (Data Science and Analytics)

The Amharic title of the degree shall be:

የሳይንስ ማስተርስ ዲግሪ በኢንፎርሜሽን ሳይንስ (ዳታ ሳይንስና አናሊቲክስ)

Resource Profile (Staff and facilities)

Staff resource profile

The home of the program is Department of Information Science, Departments in the Faculty are interrelated and the Faculty has sufficient human resource with relevant specialization to run the program.  And since the program is multidisciplinary staffs from other departments such as Statistics are parts of potential human resource for the program.  

  • Collaboration staffs from Addis Ababa University, Haramya University Jimma University, Mekele University, Bahir Dar University and Wollo University.
  • Partnerships from: Ethio telecom, INSA, Dabat Research Center, Ethiopian National Metrology Agency, Entoto Observatory Research Center, Ethiopian Central statistical Agency

Professional Profile

Data Science and analytics is a multidisciplinary field emerging technology that is currently becoming a hot issue in different big organizations, companies and industries for the purpose of analyzing and extracting valuable data from big data and visualizing it for making the right decisions and predicting its future. It is the development of analytical models and methods to extract actionable knowledge from huge volume of data. Therefore, graduates will have major skills and competencies that would include; values, attitudes, professionalism, problem solving skills, Leadership and team skills, data science and lifelong learning skills and entrepreneurial skills: as stated on the rationalities of the program the graduates will be working on the following organizations:

  • Information Network and Security Agency (INSA):-the graduates will easily understand different forms of data, sources of big data, for extracting, analyzing, modeling, visualizing and interpret huge volumes of data by apply analytical tools and techniques to resolve big data problems and administering big data sources for decision making.
  • Ethio-Telecom: – the graduates will easily understand different forms of user behavior related data, sources of big data, for extracting, analyzing, modeling, visualizing and interpret huge volumes of data by apply analytical tools and techniques to resolve big data problems and administering big data sources for decision making.
  • Ministry of Health data centers: the graduates will easily understand different forms of health related data, sources of big data, for extracting, analyzing, modeling, visualizing and interpret huge volumes of data by apply analytical tools and techniques to resolve big data problems and administering big data sources for decision making.
  • Banks: the graduates will easily understand different forms of financial transaction data from government and private banks and financial institutions, sources of big data, for extracting, analyzing, modeling, visualizing and interpret huge volumes of data by apply analytical tools and techniques to resolve big data problems and administering big data sources for decision making.
  • National Metrology Agency: – the graduates will easily understand different forms of weather related data, sources of big data, for extracting, analyzing, modeling, visualizing and interpret huge volumes of data by apply analytical tools and techniques to resolve big data problems and administering big data sources for decision making.
  • Ministry of Education data centers: – the graduates will easily understand different forms of educational data, sources of big data, for extracting, analyzing, modeling, visualizing and interpret huge volumes of data by apply analytical tools and techniques to resolve big data problems and administering big data sources for decision making.

Objective of the program

 The aim of this program is to produce graduates with the Big Data analytics and technical skills to effectively extract meaningful data and information from massive amount of data to support the management and operations of an organization.

Specific objectives

  • To train students in Data Science program for teaching and research activity in the country,
  • To prepare students for a career as data scientist, data engineer, big data analyst, business analytics specialist, data analyst data architect, big data expert, data miner, researcher and database administrator.
  • To prepare students who can organize, integrate, process, analyze, model, extract and visualize big data in the country;
  • To equip students with analytical tools and techniques to resolve big data scientific problems in various sectors and domains, and skills to communicate insights gained using visualization tools.
  • To facilitate and mentor advanced study in data science.

Course List

Course Code Course Title Cr. Hrs. Course category
ISDS1101 Foundation of Information & Data Science 3 GENERAL COURSES
ISDS1102 Research Methods 3 GENERAL COURSES
   
ISDS1113 Introduction to Data Analytics 3 CORE COURSES
ISDS1114 Exploratory Data Analysis and Visualization 3 CORE COURSES
ISDS1211 Advanced Database Systems and Semantic Web Analysis 3 CORE COURSES
ISDS1213 Advanced Machine Learning Data Mining 3 CORE COURSES
ISDS1214 Big Data Analytics 4 CORE COURSES
ISDS2111 Graduate Seminar in Information & Data Science 2 CORE COURSES
ISDS2211 Master’s Thesis 6 CORE COURSES
ISDS1212  Data Science and Analytics workshop 4 CORE COURSES
ISDS2121 Data and Information Security 2 CORE COURSES
ISDS2122 Statistical Techniques for  Data Science 2 CORE COURSES
ISDS2123 Artificial Intelligence 2 CORE COURSES
INSC Fundamental of Database systems  – Bridge course
INSC Systems Analysis and Design (Software Engineering) Bridge course
INSC Fundamental of Programing Bridge course
STAT Introduction to Statistics  Bridge course