Advanced Algorithms (2225.YR.015029.1)
General information
Type: |
OBL |
Curs: |
1 |
Period: |
S semester |
ECTS Credits: |
6 ECTS |
Teaching Staff:
Group |
Teacher |
Department |
Language |
Year 1 |
Jordi Nin Guerrero |
Operaciones, Innovación y Data Sciences |
ENG |
Prerequisites
- Introduction to AI: Programming Foundations
- Computing Foundations
Previous Knowledge
- Python knowledge
- Data structures
- Basic programming
Workload distribution
Lectures and in-class exercises will represent 50% of the workload. The assignments and the preparation for the exams will represent the other 50% of the workload.
COURSE CONTRIBUTION TO PROGRAM
Transforming big data into unique and proprietary business algorithms translates into transforming the entire enterprise. The only way to process data into actionable insight is to create algorithm-based software. Making sense of large amounts of data via algorithms will improve business decision-making, which translates into significant improvements in business performance.
We understand algorithmic business as the industrialized use of complex mathematical algorithms pivotal to driving improved business decisions or process automation for competitive differentiation. The algorithmic business provides the speed and scale to accelerate digital business to deliver even greater impact.
Course Learning Objectives
This subject introduces the necessary algorithmic foundations required to understand basic algorithms techniques and components to solve different business needs related to operations, customer intelligence and marketing.
CONTENT
1. Introduction to algorithms |
2. Recursivity |
3. Algorithms complexity |
4. Brute force algorithms |
5. Divide and conquer |
6. Searching algorithms |
7. Algorithms on trees |
8. Algorithms on graphs |
Relation between Activities and Contents
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A1: Recursivity |
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A2: Divide and conquer |
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A3: Algorithms on trees |
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A4: Algorithms on graphs |
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Mid-term exam |
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Final exam |
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Attendance |
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Methodology
To achieve the objectives, this 10-week course will be based on lectures, class discussions and practice.
Lecture/Discussion. During theoretical lessons, we will introduce the basic concepts for each topic. These sessions will be devoted to the presentation and discussion of frameworks, concepts, and theories.
Practice. In Practice sessions, we will present the general framework and the background tools. Different practical exercises will then be delivered and discussed in class.
ASSESSMENT
ASSESSMENT BREAKDOWN
Description |
% |
A1: Recursivity |
10 |
A2: Divide and conquer |
10 |
A3: Algorithms on trees |
10 |
A4: Algorithms on graphs |
10 |
Mid-term exam |
25 |
Final exam |
25 |
Attendance |
10 |
Assessment criteria
10 % Attendance
40% Assignments
25% Mid-term exam
25% Final exam
Bibliography
Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford (2022) [1990]. Introduction to Algorithms (4th ed.). MIT Press and McGraw-Hill. ISBN 0-262-04630-X. 1312 pp.
Timetable and sections
Group |
Teacher |
Department |
Year 1 |
Jordi Nin Guerrero |
Operaciones, Innovación y Data Sciences |
Timetable Year 1
From 2023/2/1 to 2023/4/19:
Each Wednesday from 10:45 to 13:15. (Except: 2023/3/15 and 2023/4/5)
Wednesday 2023/3/15 from 9:00 to 12:00.
Monday 2023/5/15 from 9:00 to 12:00.