Course Objective
The course aims at giving an overview of Data Engineering foundational concepts. It is tailored for 1st and 2nd year Msc students and PhDs who would like to strengthen their fundamental understanding of Data Engineering, i.e., Data Modelling, Collection, and Wrangling.
Prerequisites
Familiarity with the following concepts is strongly recommended to succeed in the course:
- Algorithm and Data Structures
- Graphs, Trees, Tables, Lists
- Programming Languages
- Java and Python
- (Relational) Databases and Query Languages
- SQL, JsonPath, and openCypher.
- Joins, Aggregations, Table definition, and manipulation (Create, Update, Insert, Alter)
Syllabus (Tentative)
Note: The syllabus might be subject to change and will be adjusted during August
- Data Modelling and Query Languages (2 class + 2 practice)
- Structured Data
- Unstructured Data
- Data Collection (1 class + 1 practice)
- Data Transformation (3 classes + 3 Practices)
- Stream Processing
- Data Pipeline
- Data Wrangling (5 classes + 3 practices)
- Cleansing
- Enrichment
- Augmentation
- Concept Overview (1 class)
- Data Warehouse
- Data Lake
- Data Science
Evaluation Methods'
The course evaluation will be based on assignments (pass/notpass) and a written exam. In the case of a lockdown, we might consider projects or oral presentations.
Contacts
- Lecturer:
- Riccardo Tommasini - riccardo.tommasini@ut.ee
- Teaching Assistants
- Mohamed Ragab
- Hassan Eldeeb
- Samuele Langhi
Suggested Reads