INTRODUCTION

PURPOSE OF THE PROGRAMME

Data science and informatics is a skills-based programme which emphasizes data analytics, machine learning, algorithm design, computer vision and data protection. The programme aims to:

Develop knowledge, skills, and competencies in the field of Data Science and Informatics, data analytics, machine learning, and computer vision relevant to various employment capabilities and careers in the world of work and society.

To prepare students for further studies and lifelong learning in the Data Science Profession.

OBJECTIVES

3 ENTRY REQUIREMENTS

Normal Entry

To qualify for entry into the Bachelor of Commerce Honours Degree in Data Science and Informatics programme, a candidate, in addition to satisfying the minimum conditions as prescribed under the General Regulations for English and Mathematics at ‘O’ Level, must have obtained a pass in ‘A’ Level Mathematics or Statistics and a pass at ‘A’ level in at least two of the following subjects or their equivalents: Accounts, Economics, Management of Business and Computing [Computer Studies/Software engineering]

Visiting / Harare Weekend School Programme

To qualify for entry into the Bachelor of Commerce Honours Degree in Data Science and Informatics programme (Visiting / Harare Weekend School), a candidate, in addition to satisfying the minimum conditions prescribed under the General Regulations must have:

either:

A National Diploma in an Information Technology related field or any equivalent Tertiary qualification

or:

At least two (2) passes in relevant “A” Level subjects.

and:

Confirmation of employment in Data analytics or relevant Information Technology departments.

Special Entry

Candidates who have successfully completed a Professional Diploma in Data Science or have obtained equivalent qualifications within three years may apply for direct entry into Level 2 of the degree programme, subject to availability of places. Candidates admitted under the above regulation will normally be exempted from level 1 on a module-by-module basis. No candidate may complete the degree in less than three academic levels. Successful completion of the Work-Related Learning component at level three is compulsory for all candidates.

Mature Entry

Should be at least 23 years old for females and 25 years old for males AND should have at least 2 years relevant industrial experience.

 

4 Career Opportunities and Further Education

Graduates with a Bachelor of Commerce Honours Degree in Data Science and Informatics can pursue careers in Data Science and Informatics including Data Science Engineer, Data Analysts, Big Data Consultant, Data Warehouse Specialist, Database Administrator, and Business Intelligence Analysts.

The programme also opens opportunities for graduates to pursue further education within the data science and informatics fields. Students can enroll for Master’s and Doctoral studies in Data Science and Informatics or in interdisciplinary programmes related to Artificial intelligence, Cloud Computing, the Internet of Things and other related higher qualifications.

5 GENERAL PROVISIONS

Refer to faculty and general regulations

6 ASSESSMENT

PROGRAMME STRUCTURE 

Level 1 Semester 1

Code	Module Description	Credits
CS131	Basic Communication Skills	12
GSB211	Gender Studies for Business	12
DSI 132	Foundations of Data Science	12
DSI 136	Data Structures and Algorithms	12
DSI 131	Introduction to Informatics	12
DSI 133	Human-computer interaction principles and practices	12
DSI 134	Principles of Programming Languages	12
DSI 135	Computer Architecture and Organisation	12

Level 1 Semester 2

Code	Module Description	Prerequisites	Credits
DSI 137	Computer-information ethics, social informatics, and data governance		12
DSI 139	Introduction to Python	DSI 134 & DSI 136	12
DSI 142	Operating systems	DSI 135	12
DSI 140	Information Infrastructure 1	DSI 139	12
DSI 141	Natural Language Processing	DSI 139	12
DSI 143	Fundamentals of Data Warehouse and Data Mining		12

Level 2 Semester 1

Code	Module Description	Prerequisites	Credits
ENT 131	Entrepreneurship 1		12
DSI 232	Information Systems Analysis, Design and Development Methodologies		12
DSI 234	Information Representation		12
DSI 231	Introduction to Research in Data Science and Informatics		12
DSI 233	Enterprise Architecture		12
DSI 235	Machine Learning I: Using Python	DSI 139	12

Level 2 Semester 2

Code	Module Description	Prerequisites	Credits
DSI 237	Statistical analysis		12
DSI 240	R Programming and Computer Vision		12
DSI 236	Introduction to Media Application Development	DSI 133	12
DSI 238	Organisational Informatics		12
DSI 239	Data Science and Informatics Project 1		12

Level 3 Semester 1 Work-Related Learning

Code	Module Description	Prerequisites	Credits
DSI 340	Work-Related Learning Preliminary Report		40

Level 3 Semester 2 Work-Related Learning

Code	Module Description	Prerequisites	Credits
DSI 341	Work-Related Learning Continuous Assessment		40
DSI 342	Work-Related Learning Report		40

Level 4 Semester 1

Code	Module Description	Prerequisites	Credits
DSI 434	Optimisation Techniques with NumPy & SciPy	DSI 235	12
DSI 435	Applied cloud computing for data-intensive sciences		12
DSI 431	Data Science and Informatics Project Management		12
DSI 432	Information Infrastructure 2: OOP	DSI 140	12
DSI 433	Advanced Data Warehouse and Data Mining	DSI 143	12

Level 4 Semester 2

Code	Module Description	Prerequisites	Credits
DSI 436	Data analytics and visualisation using matplotlib & seaborn	DSI 240	12
DSI 437	Machine Learning II: Using JAVA	DSI 235	12
DSI 438	Data Science and Informatics Project 2		24