Seminar in data management: basic

ldats2360  2022-2023  Louvain-la-Neuve

Seminar in data management: basic
4.00 credits
15.0 h + 10.0 h
Q1
Teacher(s)
Bugli Céline;
Language
French
Prerequisites
Concepts and tools equivalent to those taught in teaching unit
LSTAT2020Logiciels et programmation statistique de base
Main themes
- Introduction to the SAS system and to SAS/Base programming. - Creation and manipulation of datasets with SAS: importing and exporting datasets, format definition, table merging, variable manipulation, creation and transformation. - Preparation of summary tables, preparation of reports in different formats (txt, html...) - Presentation of the " SAS base programming " certificate.
Learning outcomes

At the end of this learning unit, the student is able to :

1 At the end of this course, the student will master the programming in SAS/Base and will be able to apply its skills on big and complicated data sets.
 
Content
SAS Programming 1: Essentials
  • Use SAS Studio and SAS Enterprise Guide to write and submit SAS programs.
  • Access SAS, Microsoft Excel, and text data.
  • Explore and validate data.
  • Prepare data by subsetting rows and computing new columns.
  • Analyze and report on data.
  • Export data and results to Excel, PDF, and other formats.
  • Use SQL in SAS to query and join tables.
SAS Programming 2: Data Manipulation Techniques
  • understand and control DATA step processing
  • create an accumulating column and process data in groups
  • manipulate data with functions
  • convert column type
  • create custom formats
  • concatenate and merge tables
  • process repetitive code
  • restructure tables.
Teaching methods
In addition to the lectures and computer room exercises, much of the training is done autonomously using the syllabus, SAS documentation, and e-learning tools provided by SAS.
The lectures will be given in co-modal (simultaneous transmission of the course given in auditorium on Teams) and the practical work will be given in face-to-face only.
The modalities foreseen will evolve according to the health situation.
Evaluation methods
The examination of this course consists of a computer-based examination (multiple-choice questions and programming questions, computer-based examination). The SAS Base Programming Certification can be taken instead of the exam for those students who wish to do so.
Other information
A large part of the training is carried out autonomously using materials available on the SAS website (SCYP program). This course is only open to students enrolled and with a good command of passive English.
Online resources
https://moodleucl.uclouvain.be/course/view.php?id=8018
This course is open to all students from Belgian universities after enrolment in the academic programme (Master's or Doctoral students). However, as the number of places is limited, enrolment for students other than those in the Master's degree in statistics, general orientation or biostatistics ou a Master's degree in data sciences can only be made with the agreement of the course holder. This course is also available to students of the UCLouvain University Certificate in Statistics under certain conditions.
The course content is only available after official registration.
Bibliography
Syllabus du cours en vente au début du cours.
Accès à la documentation SAS.
Teaching materials
  • Syllabus du cours en vente au début du cours. Accès à la documentation SAS.
Faculty or entity
LSBA


Programmes / formations proposant cette unité d'enseignement (UE)

Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Data Science : Statistic

Master [120] in Biochemistry and Molecular and Cell Biology

Master [120] in Biomedical Engineering

Master [120] in Statistics: Biostatistics

Advanced Master in Quantitative Methods in the Social Sciences

Master [120] in Actuarial Science

Master [120] in Population and Development Studies

Master [120] in Statistics: General

Approfondissement en statistique et sciences des données

Master [120] in Mathematical Engineering

Certificat d'université : Statistique et science des données (15/30 crédits)