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Diploma of Data Science and Analytics



The Diploma of Data Science and Analytics (DDSA) is an all-inclusive two-year programme designed to equip students with essential skills for a career in the rapidly growing field of data science. This diploma focuses on providing hands-on experience with key tools and techniques used in data analysis, visualisation, and interpretation. Students will gain proficiency in fundamental aspects of machine learning and artificial intelligence, preparing them for entry-level positions in data analytics, data visualisation, and related fields.

The curriculum is structured to ensure graduates are well-versed in the entire data science pipeline, from data acquisition and preprocessing to model building and deployment. One of the key features of the DDSA programme is its emphasis on practical, project-based learning. Students will work on real-world projects throughout the program, enhancing their practical skills and problem-solving abilities. These projects will involve working with diverse datasets, applying various data analysis techniques, and communicating insights effectively to stakeholders. Students will explore topics such as data privacy, algorithmic bias, and the societal impact of data-driven technologies, ensuring that they are prepared to navigate the ethical challenges that arise in the data science field.

The DDSA programme is designed to be flexible and adaptable, catering to the needs of both recent high school graduates and working professionals looking to upskill or change careers. The programme’s strong industry connections and focus on practical applications ensure that students are well-prepared to contribute effectively in various industries, providing valuable insights through data analysis and playing a crucial role in the evolving landscape of data science and analytics.

Graduates of the Diploma of Data Science and Analytics will be equipped with the knowledge and skills necessary to pursue careers in fields such as data analysis, business intelligence, market research, and customer relationship management. The programme’s emphasis on hands-on learning and ethical considerations sets it apart, producing graduates who are not only technically proficient but also socially responsible data professionals.



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Course Overview

COURSE CODECOURSE NAME
YEAR ISEMESTER I
DDA110Python Programming
DDA111Fundamentals of Mathematics
DDA112Basic Statistics
DDA113Introduction to Information Technology
DDA114Communication Skills and Learning Skills for Employability
DDA115Digital Electronics
  
YEAR ISEMESTER II
DDA120Numerical Analysis and Computation
DDA121Internet of Things
DDA122R Programming
DDA123Internet Technologies and Web Design
DDA124Data Science Essentials
DDA125Design Thinking
  
YEAR IISEMESTER I
DDA210Database Development and Management 1
DDA211Statistical Data Analysis
DDA212Business Cloud Computing
DDA213Computer Networks & Data Communication
  
Recess Term
DDA214Industrial Training/Internship
  
YEAR IISEMESTER II
DDA220Data Analysis and Visualization
DDA221Data Wrangling
DDA222Emerging Trends in Data Analytics
DDA223Tools for Data Science and Analytics
DDA224Graduation project
DDA225Front End Development


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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.


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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.


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