FI2BCP175 Semester Project 2
FI2BCP175 Semester Project 2
- Course description
- Course CodeFI2BCP175
- Level of Study5.2
- Program of StudyData Analyst 2
- Credits7.5
- Study Plan CoordinatorBertram Haskins, Alec Du Plessis
The semester concludes with a graded project where the candidate must demonstrate practical skills and competence from courses in the first semester. Candidates work independently or in a group on a project, which must be planned, documented and executed according to project criteria. The aim is to carry out a practical project of elements from the previous courses. The candidate also prepares a project plan and an individual reflection report documenting the process and choices made along the way.
The project challenges candidates to use and combine accumulated competence from the first semester and showcase how they can complete larger projects, either individually or across disciplinary boundaries. Candidates are challenged to think and work holistically, providing a solid platform for further learning and understanding the data analysis field.
The candidate:
- can assess own knowledge of the data analysis paradigm through the subjects and topics in the first semester
- has insight into own opportunities for development in programming with Python, programmatic data analysis, databases and cloud-based services
The candidate:
- can explain vocational choices to solve practical and real-world problems and tasks with data analysis
- can find and refer to information and vocational material that is relevant to the given data analysis project
The candidate:
- can plan and carry out data design processes, data models, and applicable techniques based on the given project brief alone or as part of a group and in accordance with ethical principles that apply in appropriately sourced, stored, and used data
- can exchange points of view with their peers and other data specialists such as system architects, data scientists, data engineers, and business intelligence agents and participate in discussions about the development of good data analysis practice
Digital Learning Resources
The learning management system (LMS) is the primary learning platform where students access most of their course materials. The content is presented in various formats, such as text, images, models, videos or podcasts. Each course follows a progression plan, designed to lead students through weekly modules at their own pace. Exercises and assignments (individual or in groups) are embedded throughout the courses to support continuous practice and assessment of the learning outcomes.
Campus Resources
In addition to the digital learning resources, campus students participate in physical learning activities led by teachers as part of the overall delivery.
Guidance
Guidance and feedback from teachers support students' learning journeys, and may be provided synchronously or asynchronously, individually or in groups, via text, video or in-person feedback.
| Form of assessment | Grading scale | Grouping | Duration of assessment |
|---|---|---|---|
Semester Project | Grade A-F | Individual | 4 Week(s) |