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).

K2: Understands and applies the most appropriate mathematical, statistical and computational tools within Neuroscience, appropriately using spreadsheets for data management, and appropriate graphical representations for data presentation. S1: Uses a variety of techniques to find, manage, integrate and critically evaluate available information for the development of professional activities in Neuroscience, especially in the digital sphere S7: Comprehends the computational and experimental tools used for analysis and quantification of neuroscience data, and can appropriately apply these tools to significant problems in neuroscience. C2: Apply knowledge about the organisation, structure and function of the Central Nervous System (CNS) to contribute to the evolution and improvement of technologies and systems for computing, data handling and analysis. C3: Apply knowledge about technologies for the study of the Nervous System and the brain (Medical Imaging, brain-machine interfaces) to develop new systems for diagnosis and treatment, as well as and other applications within Neuroscience (Artificial Intelligence, Robotics) with the aims of improving the quality of life and furthering social progress. C4: Uses advanced mathematical, statistical and computational tools to increase and improve knowledge in neuroscience and its applications. C5: Apply your neuroscience knowledge in a unifying and integrated fashion as part of a multidisciplinary team (pharmaceutical sector, health industry, diagnostic techniques, health information technologies, government agencies and regulatory bodies. C6: Apply the results of your comprehensive training to your everyday professional activities, combining Neuroscience knowledge with a solid foundation of ethical responsibility and respect for fundamental rights, diversity and democratic values. C7: Apply the scientific and technical principles you acquired during your undergraduate training, together with your own natural learning capabilities, to better adapt to novel opportunities arising from scientific and technological development.

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 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.