Year2 SemesterIII Course Structure

Welcome to the third semester of the second year. This semester builds on the foundations laid in the first two semesters and prepares students for the more specialised modules that appear in later years. The following overview outlines the core modules, optional electives, credit distribution, timetable considerations and assessment methods.

1. Credit Allocation

The semester carries a total of 30 credit points, split between compulsory and elective units. The breakdown is as follows:

• Core Modules 18 credits
• Elective Modules 9 credits
• Project/Practical Component 3 credits

2. Core Modules (18CP)

All students must enrol in the three core modules listed below. These courses deepen theoretical knowledge and develop critical analytical skills.

2.1 Data Structures & Algorithms II

This module extends the introductory concepts covered in Year1. Topics include balanced trees, graph algorithms, dynamic programming, and amortised analysis. Laboratory sessions focus on implementing these structures in a highlevel language and evaluating performance on realistic data sets.

2.2 Digital Signal Processing

Students explore the mathematical foundations of signal analysis, Ztransform, filter design, and discrete Fourier analysis. Practical work involves using MATLAB/Octave to design, simulate, and test FIR and IIR filters on audio and biomedical signals.

2.3 Statistical Inference

The course introduces probability theory, hypothesis testing, confidence intervals, and maximum likelihood estimation. Tutorials reinforce concepts through problemsolving and statistical software (R) for data analysis.

3. Elective Modules (9CP)

Two electives must be chosen from any of the following options. Electives allow students to tailor their learning toward specific interests or career aspirations.

Students may select any combination that totals 9 credits, for example: one 6credit elective plus one 3credit elective, or three 3credit electives if they wish to explore multiple areas.

4. Project / Practical Component (3CP)

A mandatory 3credit practical component runs concurrently with the core modules. This component is a shortduration project that allows students to apply concepts from at least two of the core courses to a realworld problem. Assessment is based on a written report (70%) and an oral presentation (30%).

5. Timetable Overview

Below is a typical weekly timetable. Exact slots may vary each year, so students should confirm the final schedule on the university portal.

6. Assessment Summary

Each module follows a standard assessment pattern, but specific weightings differ. The table below summarises the major assessment components.

7. Study Tips for Success

• Plan early: Allocate dedicated time slots for lab work and project meetings to avoid lastminute rushes.
• Use office hours: Lecturers and lab tutors are available twice a week; bring specific questions rather than general queries.
• Form study groups: Collaborative problemsolving is especially effective for algorithm design and statistical proofs.
• Leverage online resources: Platforms such as Coursera, Khan Academy and official documentation (e.g., MATLAB, R) complement classroom learning.
• Practice past papers: Familiarise yourself with exam formats and typical question styles a month before the assessment period.

8. Contact Information

For further clarification, students may contact the Academic Advisor or the respective module coordinators. Email addresses and office locations are listed on the departmental website.

Good luck with your studiesthis semester is a pivotal step toward achieving your academic and professional goals.