This course teaches the basic techniques, methodologies, and practical skills required to draw meaningful insights from a variety of data, with the help of the most acclaimed software tools in the data science world (pandas, scikit-learn, Spark, etc.) ...
This course covers advanced topics in deep learning architectures for natural language processing. The focus is on attention-based architectures, structure processing and variational-Bayesian approaches, and why these models are particularly suited to the ...
We teach the fundamental aspects of analyzing and interpreting computer languages, including the techniques to build compilers. You will build a working compiler from an elegant functional language into machine code using a popular backend called LLVM (htt ...
This hands-on course covers tools and methods used by data scientists, from researching solutions to scaling prototypes on Spark clusters. Students engage with the full data engineering and data science pipeline, from data acquisition to extracting insight ...
The course introduces the foundations on which programs and programming languages are built. It introduces syntax, types and semantics as building blocks that together define the properties of a program part or a language. Students will learn how to apply ...
Understanding of the principles and applications of functional programming, the fundamental models of program
execution, application of fundamental methods of program composition, meta-programming through the construction of
interpreters and advanced progr ...
Le cours "Critical Data Studies" s'inscrit dans la nouvelle offre d'enseignements TILT qui propose de croiser des savoirs provenant des SHS et des sciences de l'ingénieur afin d'aborder des thématiques complexes qui nécessitent une méthodologie interdiscip ...