Checking date: 21/02/2025


Course: 2024/2025

Advanced knowledge of Spreadsheets
(17881)
Bachelor in Computer Science and Engineering (Plan: 489 - Estudio: 218)


Coordinating teacher: VELASCO DE DIEGO, MANUEL

Department assigned to the subject: Transversal matters

Type: Compulsory
ECTS Credits: 1.5 ECTS

Course:
Semester:




Objectives
The main objective of this course is to be equipped with the proper skills to apply spreadsheet tools for providing practical solutions through the automation of tasks and data lifecycle management (load, clean, reconcile and exploit using differen techniques depending on the problem specification).
Learning Outcomes
RA1.1: Knowledge and understanding of the mathematics and other basic sciences underlying their engineering specialisation, at a level necessary to achieve the other programme outcomes. RA1.2: Knowledge and understanding of engineering disciplines underlying their specialisation, at a level necessary to achieve the other programme outcomes, including some awareness at their Forefront. RA5.5: Awareness of non-technical ¿ societal, health and safety, environmental, economic and industrial ¿ implications of engineering practice. RA6.1: Ability to gather and interpret relevant data and handle complexity within their field of study, to inform judgements that include reflection on relevant social and ethical issues. RA6.2: Ability to manage complex technical or professional activities or projects in their field of study, taking responsibility for decision making. RA7.1: Ability to communicate effectively information, ideas, problems and solutions with engineering community and society at large. RA7.2: Ability to function effectively in a national and international context, as an individual and as a member of a team and to cooperate effectively with engineers and non-engineers. RA8.1: Ability to recognise the need for and to engage in independent life-long learning. CB3: Students have the ability to gather and interpret relevant data (usually within their field of study) in order to make judgements which include reflection on relevant social, scientific or ethical issues. CB4: Students should be able to communicate information, ideas, problems and solutions to both specialist and non-specialist audiences. CB5: Students will have developed the learning skills necessary to undertake further study with a high degree of autonomy. CG6: Communicate verbally and in writing in a bilingual environment: Spanish, English. CG7: Be able to present and discuss proposals in a team work environment, demonstrating personal and social skills that allow him/her to assume different responsibilities within them. CG8: Be able to communicate respecting others, the equality between men and women and other fundamental rights, as well as obligations to society, the profession and the environment. CG9: Efficiently use ICT resources to write technical reports and project and work reports on computing, as well as quality presentations. CGB2: Understanding and mastery of the basic concepts of fields and waves and electromagnetism, electric circuit theory, electronic circuits, physical princi- ples of semiconductors and logic families, electronic and photonic devices, and their application to the resolution of engineering problems. CGB4: Basic knowledge of the use and programming of computers, operating systems, databases and computer programmes with applications in engineering. CGO9: Ability to solve problems with initiative, decision-making, autonomy and creativity. Ability to know how to communicate and convey the knowledge, skills and abilities of the profession of Technical Engineer in Computer Science. CGO11: Ability to analyse and assess the social and environmental impact of technical solutions, understanding the ethical and professional responsibility of the activity of the Technical Engineer in Computer Science.
Description of contents: programme
Teaching Unit 1: A first contact 1.1-Structure of a spreadsheet: book, sheets and cells.and basic operations 1.2-Working with cells and sheets, data import and references. 1.3-Task automation for this unit Teaching unit TU2: Building, understanding and exploiting data. 2.1-Formula and functions Boolean operators and functions Text Database Descriptive statistics 2.2-Tables and pivot tables 2.3-Data analysis 2.4-Task automation for this unit Teaching unit TU3: Representation of data and information, task automation and applications 3.1-Visualization (pivot charts) 3.2-Spreadsheet applications: forms, mail merge, printing, document generation, etc. 3.3-Task automation for this unit
Learning activities and methodology
LEARNING ACTIVITIES AND METHODOLOGY THEORETICAL-PRACTICAL CLASSES. [12 hours with 100% classroom instruction, 0.48 ECTS] Knowledge and concepts students must acquire. Student receive course notes and will have basic reference texts to facilitate following the classes and carrying out follow up work. Students partake in exercises to resolve practical problems and participate in workshops and evaluation tests, all geared towards acquiring the necessary capabilities. TUTORING SESSIONS. [1 hours of tutoring with 100% on-site attendance, 0.08 ECTS] Individualized attendance (individual tutoring) or in-group (group tutoring) for students with a teacher. STUDENT INDIVIDUAL WORK OR GROUP WORK [24,5 hours with 0 % on-site, 0.98 ECTS] METHODOLOGY THEORY CLASS. Classroom presentations by the teacher with IT and audiovisual support in which the subject`s main concepts are developed, while providing material and bibliography to complement student learning. PRACTICAL CLASS. Resolution of practical cases and problems, posed by the teacher, and carried out individually or in a group. TUTORING SESSIONS. Individualized attendance (individual tutoring sessions) or in-group (group tutoring sessions) for students with a teacher as tutor. Additional note about software resources: -Excel 2013 or higher (Office 365 provided by the University would be recommended). Spanish or English language version, depending on the language of the enrollment group. -To do exercises, a personal computer can be used or you can also connect to the virtual classroom service provided by UC3M.
Assessment System
  • % end-of-term-examination 0
  • % of continuous assessment (assigments, laboratory, practicals...) 100

Calendar of Continuous assessment


Extraordinary call: regulations
Basic Bibliography
  • Conrad Carlberg. Predictive Analytics: Microsoft Excel. Que Publishing. 2012
  • John Walkenbach. Excel 2016 Bible. Willey. 2016
  • Matthew MacDonald.. Excel 2010: The Missing Manual. . O'Reilly.. 2010
Recursos electrónicosElectronic Resources *
Additional Bibliography
  • Cole Nussbaumer Knaflic. Storytelling with Data: A Data Visualization Guide for Business Professionals. Willey. 2015
  • Jordan Goldmeier. Advanced Excel Essentials. APress. 2014
  • Jordan Goldmeier. Dashboards for Excel. APress. 2015
(*) Access to some electronic resources may be restricted to members of the university community and require validation through Campus Global. If you try to connect from outside of the University you will need to set up a VPN


The course syllabus may change due academic events or other reasons.