CSLL Year 2

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The following is a brief overview of the modules taken in Senior Fresh year

Beside the overview below, current students should be able to follow the links to further information (within the eLearning environment, “Blackboard”, or a module’s own website), or via my.tcd.ie for full details, including assessment criteria and learning outcomes.

Foundation Scholarship Examinations

Students their second year are eligible to take the College Foundation Scholarship examinations if they wish. In exceptional circumstances, the examinations can be taken in third year instead.

Scholarship Presentation recording 2223

Full Year Modules

MAU22C00 – Discrete Mathematics

(Full Year, 10 credits) The mathematical objects studied in this module are fundamental not just for theoretical computer science but constitute the building blocks for formalising problems and writing down algorithms to solve those problems. The aim of the module is to provide a lifelong ability to operate with the mathematical objects and to make students comfortable with mathematical proofs.

Semester One Modules

CSU22061 – Intermediate Programming

(Semester 1, 5 ECTS) Fundamentals of C++ including built-in types and coercion, pointers, arrays, reference parameters, STL containers string and vector structs, classes, inheritance (illustrated by Qt library for GUIs), dynamic memory allocation and recursive data structures.

CSU22011 – Algorithms and Data Structures I

(Semester 1, 5 ECTS) The topics of this module are: the theory and practice of algorithmic design; evaluation algorithm performance; and standard algorithms and data structures.

Semester Two Modules

CSU22012 – Algorithms and Data Structures II

(Semester 2, 5 ECTS) This module continues directly from Algorithms and Data Structures I and addresses topics including recursion, divide-and-conquer, graph traversal and dynamic programming.

CSU22062 – Natural Language Processing

(Semester 2, 5 ECTS) Regular languages, context free languages, feature structures, a brief into to Probailistic Methods in NLP, topic varying year to year,
examples being the use of Hidden Markov models in speech recognition, or
statistical machine translation, a brief into recursive computation of semantic values from grammatical structures.