Data Visualisation For Data-Driven Decision Making
Various methods for presenting data for visualisation as well as how to choose between them. Fundamentals of data presentation using tables, graphs, images and video animations. Create engaging visualisations using graphs, images and video animations. Data summaries, working with tables, presenting…
Learning outcomes
At the end of the course, the students should be able to: 1. utilise techniques that are applied in preparing and producing data into a form that meets the needs of particular and varied audiences; and 2. develop logical, meaningful skills that bothers not just on the relevance of the data that informed the particular outcomes, but also on the real-world implications of how these outcomes are factored into decision-making processes.
Course contents
Various methods for presenting data for visualisation as well as how to choose between them. Fundamentals of data presentation using tables, graphs, images and video animations. Create engaging visualisations using graphs, images and video animations. Data summaries, working with tables, presenting data through graphs and plots, presenting data through video animation, creating interactive/augmented visualisation of data (ability to zoom into sections). Lab work: Practical experiments on different methods of presenting data for visualisation. Practice on how to use graphs, tables, images, and video on animation for data presentation. DTS 497: Final Year Project I (3 Units C: PH 135) Learning Outcomes At the end of this course, students should be able to: 1. identify a researchable project topic in Data Science; 2. search and review literature pertinent to identified problem statements; 3. acknowledge and reference sources of information used in the research report; 4. conceptualise and design a research methodology to address an identified problem; 5. determine tools for analysing data collected based on research objectives; 6. write a coherent proposal on the research project to be conducted; and 7. orally present the written project proposal. Course Contents An independent or group investigation of appropriate software, hardware, communication and networks or IT related problems in Data Science carried out under the supervision of a lecturer. Before registering, the student must submit a written proposal to the supervisor to review. The proposal should give a brief outline of the project, estimated schedule of completion, and computer resources needed. A formal written report is essential and an oral presentation may also be required. DTS 498: Final Year Project II (3 Units C: PH 135) Learning Outcomes At the end of this course, students should be able to: 1. demonstrate technical skills in Data Science; New Computing 115 2. demonstrate generic transferable…