Bachelor of Information Sciences

Download 58.6 Kb.
Size58.6 Kb.

2017 – 2018 Calendar Proof

Bachelor of Information Sciences

  • General Information

  • Curriculum

  • Certificate in Data Analytics

General Information

The Bachelor of Information Sciences (BISc) program is by design an interdisciplinary program involving core courses taken primarily from Business Administration, Computer Science, Economics, Mathematics and Statistics. The core subjects are particularly relevant to the collection, treatment, understanding and management of data (information) encountered in other academic disciplines as well as in business, industry, government and other areas. Emphasis is placed on the statistical methods and modern computing techniques of handling these data, the design and application of mathematical models, and the management of information within organizations.

This four-year degree program is offered in cooperation and in conjunction with departments in the Faculty of Science, Applied Science and Engineering, the Faculty of Business and the Faculty of Arts.

For general regulations on admission, please consult the appropriate section of the University calendar. Transfer into the BISc from another UNB degree program is not permitted if the GPA for the most recent assessment period is below 2.0. For transfer from another university, a CGPA equivalent to 2.0 at UNB is required.

UNB Saint John also offers a Bachelor of Arts with a Major in Information and Communication Studies. This interdisciplinary program explores the influences of communication technology, the media industries and information policy on society. Additional detail and program requirements can be found in this section of the Calendar under Bachelor of Arts, Information and Communication Studies.

General Regulations

It is recommended that students read the General University Regulations, Section B of the calendar, and in particular the subsection headed “Grading System and Classification.”


The basic curriculum of the degree consists of a specified set of core courses and a set of regulations governing the choice of others. A student's program is chosen in consultation with a faculty advisor. Two specializations are offered. Years 1 and 2 are the same in all specializations. In Years 3 and 4, students must choose to follow the Decision and Systems Science Specialization, or the Decision and Business Management Specialization.

I. Required Courses

Years 1 and 2

BA 1501 , BA 1216 , BA 2504 , CS 1073 , CS 1083 , CS 1303 , CS 2043 , INFO 1103 , ECON 1013 , ECON 1023 , ECON 2013 , ECON 2023 , MATH 1003 , MATH 1013 , MATH 2213 , STAT 1793 , STAT 2793 .

Years 3 and 4

Decision and Systems Science Specialization
BA 2303 , CS 2113 , or CS 3113 , CS 2253 , CS 2383 , CS 3403 , CS 2998 , CS 3983 , CS 4525 , DA 4993 , ECON 3665 , MATH 2903 , MATH 2913 , MATH 3343 , STAT 3083 , STAT 3093 , STAT 4703.

Decision and Business Management Specialization

BA 2123 , BA 2217 , BA 2303 , BA 2858 , BA 3425 , BA 3623 , BA 3672 , ECON 3013 , ECON 3023 , ECON 3665 , ECON 4645 , MATH 2903 , MATH 2913 .

II. Regulations Governing Course Selection

  1. At least 6 ch of courses selected from HUM 2003, HUM 1021 , HUM 2021 , ICS 1001, ICS 2001 , ICS 3001 , ICS 3005 , any ENGL course, WLIT 2503 , PHIL 1053 and PHIL 2111.   

    Decision and Systems Science Specialization   

  2. At least 3 ch of courses must be chosen from upper-level Computer Science, Mathematics or Statistics courses. These courses are in addition to those listed in I.

  3. Three credit hours (3 ch) from either MATH 3753 or MATH 3903 .

  4. Three credit hours (3 ch) in upper-level Statistics. These courses are in addition to those listed in I or chosen to fulfill II.2.

  5. At least 3 ch selected from disciplines in Arts or Business to be approved by faculty advisor.  

    Decision and Business Management Specialization

  6.     At least 12 ch of courses selected from disciplines in Arts, Business or Science, Applied Science and Engineering to be approved by faculty advisor.

  7.     Twelve credit hours (12 ch) of courses selected from CS 2253 , CS 2998 , CS 3033 , CS 3403 , CS 3423 , CS 4033 , CS 4525 and DA 4403.

A grade of C or better is required in all required courses and all courses selected under II.1-II.7

An example of what would typically be taken by a student in the first year of the degree program follows:

BA 1501 Introduction to Business (1st term)
BA 1216 Accounting for Managers I (2nd term)
MATH 1003 Intro to Calculus I (1st term)
MATH 1013 Intro to Calculus II (2nd term)
CS 1073 Intro to Computer Programming I (in Java) (1st term)
CS 1083 Intro to Computer Programming II (in Java) (2nd term)
ECON 1013 Introduction to Microeconomics (1st term)
ECON 1023 Introduction to Macroeconomics (2nd term)
Plus specified Arts electives (Regulation II.1) equivalent to 2 term courses.

Certificate in Data Analytics

Nowadays, massive amounts of data are available via the Internet, or they are stored in the companies’ databases. The main problem faced is how to leverage such data into information useful for decision making. The main purpose of this certificate is to help build the skills necessary to tackle this problem.

This certificate is meant for students having a previous background in computer science, engineering, business, or science, or students currently in their final year of such a degree, and who are interested in upgrading their skills to be able to analyze data in their field. High School students with industry experience are also welcome to this program. Students with no prior background may take it as well, but they should expect to take more time to complete it, as they will have to take a significant number of prerequisite courses in addition to the core program.

The certificate is composed of 3 required courses that form the basis of data analytics. The subjects covered in those required courses include: data storage into databases, SQL queries, statistical analysis through linear regression, and finally data visualization and data mining techniques so that raw data can be converted to information useful for decision making. In the 2 elective courses, the student can build further their knowledge in the area(s) of their choice, which make up the data analytics field: data acquisition and integration, data storage, data visualization, data mining, and statistics; including the current technologies used in industry.

General Regulations

  1. Each person entering the program must have the approval of the Department of Computer Science and Applied Statistics.

  2. Only two of the five courses listed below for the certificate may be transferred from another degree or similar program.  The DA 4993 project cannot be transferred.  

  3. Normally a student must have grade 12 mathematics to enter the program. Math 1863 may be taken as one of the optional courses in the certificate program by those students who do not have grade 12 mathematics from high school or feel that they are weak in the subject. 

  4. To earn a certificate a student must successfully complete all required courses, elective courses, and the project, with a grade of C or better.  


• 3 required courses: INFO1103, STAT4703, and DA4403

• 2 elective courses from: CS2383, CS3423, CS3773, CS4525, CS4783, STAT3083, STAT3703, STAT4043, STAT4203, STAT4243, DA 4803 / DA 4813 / CS 4998 / CS 4999, BA3126
• 1 project (DA4993), which should be an industry-related project or a research-related project, involving a large amount of data.
• Note: students should also ensure that the pre-requisite courses are passed. In particular, the following courses are pre-requisites to the required courses above:

1. CS 1073

2. STAT 1793 and STAT 2793 (or one equivalent sequence: BA1605/BA2606, PSYC2901/PSYC3913, or STAT3083/STAT3093)
3. MATH1503 or MATH2213

Students with a prior degree in BScCS or BISc would have such prerequisites covered. Students with a prior degree in business, economics, biology, psychology (except BA major in psyc, with only PSYC2901), mathematics, or statistics, would most probably have already the proper background in statistics (#2 above). Students with a prior degree in engineering (assuming STAT2593 and CS1003 already taken) would have to take STAT2793 and CS1073. Engineering students who have taken CS1023 could take CS2616 rather than CS1073 (covering CS1083 as well, which might be needed for some elective courses).

This certificate requires a minimum of three terms of courses, followed by a project to complete the program on a full-time basis. An example of a course schedule for students without the prerequisites is as follows:

Fall Courses

Winter Courses

Fall Courses

CS 1073
STAT 1793
MATH 1503

STAT 2793
INFO 1103

STAT 4703
DA 4403
TWO Electives

Information about elective courses (to help in the course selection):




CS 2383 - data structures and algorithms

CS 1073

CS 1303

For students who are planning on writing programs to perform specific analyses, this course presents data structures that will help manipulate data internally in an efficient way.

CS 4525 – database management systems II


For an advanced coverage of database technologies (including data warehouses).

CS3423 – data management


Covers technologies used in the storage and manipulation of data, outside of a database framework (e.g., XML, regular expressions, etc).

CS3773 – Topics in Web Science

Provides an overview of Web-based architectures and applications facilitating online data analytics using open data.

CS4783 – Web: Semantics, Services and Solutions


Focuses on the methodologies and infrastructures driving the migration toward the semantic web. Covers interoperability, distributed data sources, information retrieval, information extraction, web services and workflow technology.

STAT4203 – intro to multivariate data analysis

STAT 1793 and STAT2793, or equivalent (see #2 above)
MATH1503 or MATH2213

More advanced statistical techniques for dealing with a large number of variables (including how to reduce that number of variables using principal components analysis).

STAT4243 – statistical computing

CS1073 or CS1003
STAT 1793 and STAT2793, or equivalent (see #2 above)

For programming in R, the language of choice when it comes to using libraries of statistical techniques.

STAT4043 – sample survey theory

STAT 1793 and STAT2793, or equivalent (see #2 above)

For those who are planning on gathering and analyzing data through surveys.

STAT3083 – probability and mathematical statistics I

STAT1793 or equivalent

In depth study of common probability distributions on which most statistical analyses and decision making rely.

STAT3703 – experimental design

 STAT 1793 and STAT2793, or equivalent (see #2 above)

Basic + complex designs for organizing experimental data collection and corresponding data analysis procedures.

DA 4803 / DA 4813 (independent studies in DA)

CS 4998 / CS 4999 (directed studies in CS or applied CS)

• Department approval

For covering topics of interest that are not currently included in available courses (e.g.,  BIG Data technologies). Students can also choose topics supportive of their project course (DA 4993). The student should find a supervisor for this.

BA3126 – Frontiers of E-Commerce I


This course incorporates a lot of data visualization techniques.

Further information may be obtained by contacting the Department of Computer Science.  In particular, the Department's website will be updated with information about the current tools and technologies taught in the courses making up this certificate, and project details.

Download 58.6 Kb.

Share with your friends:

The database is protected by copyright © 2023
send message

    Main page