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MASTER OF SCIENCE IN DATA SCIENCE AND ARTIFICIAL INTELLIGENCE (MSc. DSAI)

Programme Overview

The Master of Science in Data Science and Artificial Intelligence (MSc. DSAI) programme aims to equip graduate students with advanced theoretical knowledge, practical skills, and managerial competencies in Data Science and AI. It focuses on producing professionals who can drive change and innovation through applied training, industry collaboration, and a focus on entrepreneurship. The programme is designed to develop specialists capable of supporting the achievement of national and international development goals, such as the UN Sustainable Development Goals and the Tanzania Development Vision 2050, through data-driven solutions.

Entry Requirements
To be admitted into the MSc. DSAI programme, applicants must meet the following requirements:

  1. Possess a Bachelor’s degree from an accredited university with a GPA of at least 3.0/5.0 or equivalent (or an average of B for unclassified degrees) in Information and Communication Technology related fields.
  2. Relevant fields include, but are not limited to: Information Systems, Information Technology, IT Security, Informatics, Software Engineering, Computer Science, Computer Engineering, and Mathematics.
  3. Candidates with a Post Graduate Diploma (at least 4.0 GPA) on top of an Advanced Diploma in a field closely related to ICT are also eligible for consideration.
  4. Applicants must provide evidence (e.g., certificates, transcripts) of their qualifications.
  5. All university qualifications from foreign institutions must be authenticated by the Tanzania Commission for Universities (TCU).
  6. Applicants must demonstrate English proficiency. This can be met by:
  • Successful completion of a bachelor’s or postgraduate degree from a recognized institution where English is the language of instruction.
  • Submission of official TOEFL results with a score of 550 (paper-based), 213 (computer-based), or 80 (internet-based) or higher.

Areas of Specialization

  1. The programme offers four areas of specialty:
  2. Machine Learning and Deep Learning (ML and DL)
  3. Natural Language Processing (NLP)
  4. Autonomous Systems and Visual Intelligence (AS&VI)
  5. Data Science (DS)

Programme Duration

  1. Status: Full Time
  2. Years: 2 Years
  3. Semesters: 4

Mode of Delivery

  • Blended mode. This includes a mix of face-to-face instruction and online learning supported by learning management systems (LMS) such as Moodle, Google Classroom, Zoom, and Microsoft Teams.

Course Categories
Course Structure for the Master of Science in Data Science and Artificial Intelligence (MSc. DSAI).

Common Core Courses

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

Program Core

  1. CCSE 6001: Research Methods and Soft Skills
  2. CCSE 6011: Outreach and Internship
  3. DSAI 6104: Graduate Seminar
  4. DSAI 6102: DSAI Group Project
  5. DSAI 6100: Python for Data Analysis
  6. DSAI 6101: Mathematics for Machine Learning
  7. DSAI 6103: Ethics and Responsible AI

Specialty Core Courses

Machine Learning and Deep Learning (ML and DL)

  1. DSAI 6219: Neural Networks
  2. DSAI 6220: Advanced Machine Learning

Natural Language Processing (NLP)

  1. DSAI 6221: Machine Translation
  2. DSAI 6222: Large language Models

Autonomous Systems and Visual Intelligence (AS&VI)

  1. DSAI 6223: Robotics and Control Systems
  2. DSAI 6224: Computer Vision

Data Science (DS)

  1. DSAI 6225: Data Visualization
  2. DSAI 6226: Data Engineering and Analytics

Electives

  1. DSAI 6301: Programming in Python
  2. DSAI 6302: Statistical Methods for Data Science
  3. DSAI 6303: Reinforcement Learning and Adaptation
  4. DSAI 6304: Geospatial Data Management
  5. DSAI 6305: Cloud Computing
  6. DSAI 6306: Mathematical Modeling and Methods
  7. DSAI 6307: AI/ML User Experience (UX) Design
  8. DSAI 6308: Natural Language Processing
  9. DSAI 6309: Advanced Database Management
  10. DSAI 6310: Big Data Analytics
  11. DSAI 6311: Advanced Data Warehousing and Data Mining
  12. DSAI 6312: Artificial Intelligence of Things (AIoT)

Dissertation

  1. DSAI 6199: Dissertation

By the end of the programme, graduates of the MSc. in DSAI will be able to:

Knowledge (K)

  1. K1: Demonstrate a systematic and critical understanding of the theoretical foundations of Data Science and Artificial Intelligence, including advanced mathematical, statistical, and algorithmic principles.
  2. K2: Appraise the legal, ethical, and societal implications of AI and data-driven systems, including issues of privacy, bias, fairness, and accountability.
  3. K3: Understand the principles of technological innovation and entrepreneurship required to translate research outputs into viable products or services.

Cognitive Skills (SC)

  1. SC1: Critically evaluate complex, real-world problems and synthesize novel solutions by selecting, adapting, and integrating advanced DS and AI methodologies.
  2. SC2: Formulate original research questions, design rigorous research methodologies, and conduct independent research that makes a contribution to the field.
  3. SC3: Analyze and critique cutting-edge research and developments in DS and AI from academic literature and industry practice.

Practical Skills (SP)

  1. SP1: Master the use of a comprehensive suite of modern programming languages, libraries, and platforms for large-scale data processing, model development, and system deployment.
  2. SP2: Design, implement, and validate robust, scalable, and efficient AI/ML pipelines, from data ingestion and preprocessing to model training and deployment.
  3. SP3: Create effective and insightful data visualizations and dashboards to communicate complex findings to diverse audiences.

Interpersonal Skills (SI)

  1. SI1: Communicate complex technical concepts, research findings, and strategic recommendations clearly and persuasively to both specialist and non-specialist audiences, orally and in writing.
  2. SI2: Function effectively and lead within multidisciplinary teams, demonstrating skills in collaboration, negotiation, and project management to achieve common goals.

Attitude (A)

  1. A1: Demonstrate a commitment to lifelong learning and professional development by independently seeking out and mastering new technologies and methodologies in the rapidly evolving fields of DS and AI.
  2. A2: Uphold the highest standards of professional ethics, academic integrity, and social responsibility in all professional activities.
  3. A3: Exhibit intellectual curiosity, creativity, and an innovative mindset in approaching and solving novel and challenging problems.

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