Postgraduate Diploma in Business Administration (PGD BA)

The following are the objectives of the Diploma in Data Science and Artificial Intelligence:

• Equip students with foundational skills in data analysis, visualization, and interpretation.
• Provide practical experience with key tools and techniques used in data science and analytics.
• Introduce students to fundamental concepts in machine learning and artificial intelligence.
• Foster ethical considerations in data-driven decision-making.
• Facilitate hands-on learning through real-world projects, enhancing problem-solving skills.
• Prepare students for entry-level positions in data analytics and related fields.
• Cultivate adaptability to evolving industry trends in data science and analytics.

Upon successful completion of a Diploma in Data Science and Artificial Intelligence at Cavendish University Uganda, a student should be able to:

1. Develop basic skills in analysing datasets and presenting fundamental insights.
2. Acquire a foundational understanding of basic machine learning and AI concepts for solving simple problems.
3. Gain familiarity with essential tools like Python for basic data analysis.
4. Create basic visualisations to represent simple data patterns.
5. Introduce ethical considerations in data science and AI applications at a foundational level.
6. Understand the basics of collaborating on simple real-world projects and applying basic skills.
7. Explore entry-level roles in the data science and AI industry with a foundational understanding of industry trends.

• Technical Proficiency

Students will develop strong technical skills in at least two programming languages and relevant data science frameworks, enabling them to effectively implement and evaluate machine learning models for various data types.

• Hands-on Application

Students will complete industry-relevant projects to simulate challenges faced in professional settings, and gain practical experience through internships or collaborative education opportunities with organisations, preparing them for hands-on real-world applications.

• Ethical Considerations

Students will complete coursework on ethical considerations in AI, addressing bias, fairness, transparency, and privacy, to be able to navigate and address ethical dilemmas in AI applications. Case studies or projects, will be applied to foster a responsible and ethical approach to AI.

• Adaptability to Emerging Technologies

Students will demonstrate familiarity with and the ability to use the latest tools and technologies in data science and AI, involving emerging trends such as edge computing or federated learning and ensuring they are equipped to adapt to the rapidly evolving field.

• Technical Skills

Upon completion of the programme, students will demonstrate proficiency in programming languages commonly used in data science and artificial intelligence, such as Python and be able to apply mathematical and statistical concepts to analyze and interpret data effectively. They will also be able to demonstrate knowledge of machine learning algorithms and techniques to solve data-driven problems.

• Data Analysis and Interpretation

Students will be able to collect, clean, and preprocess data from various sources for analysis, interpret, and communicate insights effectively using data visualization techniques as means of informing decision making processes.

• Machine Learning and AI

Students will demonstrate knowledge in fundamental machine learning concepts, including supervised or unsupervised learning, regression, classification, clustering, and developing machine learning models using appropriate algorithms and techniques. They will also be able to apply artificial intelligence principles to develop intelligent systems capable of learning from data.

• Problem-solving Skills

Students will be able to identify and define data-driven problems in diverse domains, design and implement effective solutions using data science and AI techniques, in addition to evaluating and improving the performance of applied solutions.

• Ethical Awareness and Responsible AI

Upon graduation, students will be able to recognise ethical considerations and biases inherent in data and AI applications. They will be able to apply ethical frameworks to guide decision-making, mitigate potential risks, and design AI systems that prioritize fairness, transparency, and accountability.

This is a post-basic in-service course for health workers. It is meant to equip them with management skills. It is a one-year course (two semesters)

• To introduce the learners to the concept of an organized health system, its goals, functions, and building blocks.
• To introduce to the students the different health systems in the world, their organization and policies.
• To introduce the participants to health sector reforms around the world
• To equip the learners with the skills to design, conduct, analyse and report health services research essential to meeting the demands and challenges of the Great Lakes region of Africa and beyond.
• To increase the learners’ capacity for designing, implementing and evaluating health programmes and projects relevant to local, national, regional and global health demands
• To introduce learners to the fundamental concepts and practice of planning, management, leadership and organizational development
• To provide the participants with guided practical and field-oriented training focused on the duties and responsibilities of mid-level health services managers

• Students who successfully complete the course shall attain the following learning outcomes:
• Describe a health system, its goals, functions, and building blocks using Uganda’s health system as a reference
• Describe the key types of health systems operational in different parts of the world
• Differentiate clearly between health services, a health system and the health sector and describe the interconnections between the three
• Describe health sector reforms around the world using Uganda’s health sector as a reference
• Design, conduct, analyse and report on basic health services research
• Design, manage and evaluate the designs and implementation of health projects and programmes
• Demonstrate ability to plan, lead and manage teams and health services
• Demonstrate familiarity with and agility in practical managerial functions of health services

The programme is open to Ugandans and Non-Ugandans who fulfill the minimum admission requirements described below:

1. A Diploma in health sciences disciplines such as Clinical Medicine, Nursing (general and comprehensive), Midwifery, Pharmacy, Dentistry, Environmental Health, Public health, Orthopedics, and laboratory technology from a recognised health training institution OR equivalent qualifications in the education systems of the neighbouring countries upon establishment of equivalence by the Uganda NCHE.
2. Relevant fieldwork experience is an added advantage.

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Campus-based Study Mode

As one of the most innovative academic institutions in Uganda, we’re renowned for our accredited programmes, quality education and student-centred way of doing business that creates responsible, educated, employable and entrepreneurial citizens (REEE).

Weekend Learning Study Mode

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August Intake Ongoing!