Probability & Statistics
MATH-232
Core for modeling uncertainty, risk, stochastic processes — used in pricing, risk analysis, data science.
Comprehensive foundation in probability theory and statistical analysis essential for quantitative finance and machine learning.
Covers key concepts from basic set theory and combinatorics to advanced topics like hypothesis testing,
statistical modeling, and Bayesian inference.
Random Variables
Statistical Inference
Risk Analysis
Bayesian Methods
Algorithms I
CS-250
Strong foundation in designing efficient algorithms and complexity analysis — essential in quantitative / high-frequency trading.
Fundamental algorithms and data structures: design paradigms (divide & conquer, dynamic programming, greedy), sorting, graph algorithms, analysis of complexity.
Dynamic Programming
Graph Algorithms
Complexity Analysis
High-Frequency Trading
Stochastic Models for Communications
COM-300
Gives tools in stochastic processes which are closely related to models used in quantitative finance.
Stochastic processes and models applied to communications systems (random processes, queuing, Markov models, applications in networking).
Stochastic Processes
Markov Models
Queuing Theory
Quantitative Finance
Cryptographie & Mathématiques Discrètes
AICC-1, AICC-2
Combinaison des fondamentaux des mathématiques discrètes avec les principes cryptographiques appliqués.
Couvre la théorie des nombres, l'arithmétique modulaire, les algorithmes de chiffrement et les protocoles
cryptographiques avancés, formant une base solide pour concevoir des systèmes de sécurité robustes.
Cryptographie
Théorie des nombres
Sécurité
Protocoles
Introduction to Machine Learning
CS-233
Very relevant in finance: prediction, classification, anomaly detection, portfolio optimization.
Basic machine learning methods: supervised/unsupervised learning, regression, classification, clustering, model evaluation.
Supervised Learning
Portfolio Optimization
Anomaly Detection
Model Evaluation
Algebra
MATH-310
Introduction to modern algebra focusing on groups, rings, and fields. Covers integer arithmetic, Bezout's theorem,
dihedral groups, symmetric groups, subgroups, homomorphisms, quotient groups, classification of finite abelian groups,
rings, ideals, polynomial rings, integral domains, Euclidean domains, fields, and finite fields.
Groups
Rings
Fields
Abstract Algebra
Data Intensive Systems
CS-460
Design and implementation of data-intensive systems: relational databases, query optimization, indexing structures (B-trees, hash indexes), transaction management, ACID properties, concurrency control, and distributed data systems. Hands-on with SQL, query planning, and storage engines.
SQL
DBMS
Indexing
Transactions
Query Optimization
Principles of Digital Communications
COM-302
Fundamental concepts of digital communication systems: source and channel coding, modulation schemes (QAM, OFDM), capacity limits (Shannon theorem), error-correcting codes (LDPC, turbo codes), detection theory, and modern receiver design for wireless and wired channels.
Modulation
Channel Coding
Shannon Theory
Signal Detection
OFDM
Software Construction
CS-214
Shows you understand best practices, clean design, maintainability, and ethical software design — important in production-level financial systems.
How to design and implement reliable, maintainable, efficient software using functional programming, abstraction, modularity, verification.
Design Patterns
Functional Programming
Modularity
Verification
Analysis I, II & III
MATH-101, MATH-106, MATH-203(d)
Core foundations in real and multivariate analysis: limits, continuity, sequences/series,
differentiation and integration of single and multivariable functions, ODEs, vector calculus
(grad, div, curl), line/surface integrals, Stokes/Gauss theorems, and Fourier transforms.
Provides rigorous mathematical grounding for modeling and quantitative methods.
Real Analysis
Multivariable Calculus
Vector Calculus
Differential Equations
Fourier Transforms
Distributions
Signal Processing
COM-202
The techniques are related to time series analysis, filtering noise, frequency domain methods — useful in financial data analysis.
Theory and application of signals and systems: Fourier analysis, filtering, discrete-time systems, sampling, transforms.
Time Series Analysis
Fourier Analysis
Filtering
Financial Data
Computer Systems
CS-202
Understanding hardware, performance, memory, concurrency — useful when implementing high-performance financial software.
Operating systems and system-level programming concepts, memory management, concurrency, processes, threads, system calls.
Memory Management
Concurrency
Performance
System Programming
Computer Security & Privacy
COM-301
Security is crucial in software / fintech / banking / traditional platforms; having that foundation is a plus.
Introduction to principles and practice of computer security and privacy: threats, cryptography, access control, secure system design.
Cryptography
Access Control
Fintech Security
Secure Design
Linear Algebra & Geometry
PREPA-032(a), MATH-111(e)
Study of vector spaces, matrices, determinants, and fundamental geometric concepts.
Linear algebra provides critical tools for machine learning, computer graphics, and optimization
algorithms used in both finance and software development.
Vector Spaces
Matrix Operations
Linear Transformations
Eigenvalues
Numerical Methods for Visual Computing & ML
CS-328
Numerical linear algebra, optimization, automatic differentiation, error analysis, methods for visual computing and machine learning.
Critical for implementing efficient algorithms in quantitative finance and data science applications.
Numerical Linear Algebra
Optimization
Automatic Differentiation
Error Analysis
Responsible Software
CS-290
Software development with ethics, responsibility, professional practices, reliability, maintainability.
Essential for building trustworthy systems and understanding the ethical implications of technology.
Ethics
Professional Practices
Reliability
Maintainability
Advanced Analysis & Computational Methods
MATH-101(e), PREPA-031(a), PREPA-031(b), MATH-106(e)
Comprehensive foundation in mathematical analysis including limits, continuity, differentiability,
series convergence, and integration techniques. These concepts provide the theoretical foundation
for quantitative finance and algorithmic problem-solving.
Limits & Continuity
Differentiability
Series & Convergence
Integration Techniques
The Software Enterprise – from Ideas to Products
CS-311
Comprehensive course covering the entire software development lifecycle from conception to production.
Essential for understanding how to build scalable, market-ready technology products.
Product Development
Software Lifecycle
Market Strategy
Scalability
Human-Computer Interaction
CS-213
Study of user interface design, usability, interaction models, user-centered design, evaluation techniques.
Important for creating intuitive applications and platforms.
UI Design
Usability
User-Centered Design
Evaluation
Computer Architecture
CS-270
Study of computer organization and design, including processors, memory hierarchies, and I/O systems.
Understanding how hardware and software interact at a fundamental level to optimize performance
and efficiency in computing systems.
CPU Design
Memory Systems
Pipelining
Cache Organization
Technologies for Democratic Society
CS-234
Study of how technologies interact with society, democracy, public policy, digital rights.
Important for understanding the broader impact of technology on society and regulatory considerations.
Digital Rights
Public Policy
Social Impact
Regulatory
General Physics: Electromagnetism
PHYS-114
Classical electromagnetism: Maxwell's equations, fields, potentials, waves, boundary conditions.
Provides mathematical foundation and problem-solving skills applicable to complex financial modeling.
Maxwell's Equations
Field Theory
Mathematical Modeling
Problem Solving
General Physics: Mechanics
PHYS-101
Classical mechanics covering kinematics, dynamics, conservation laws, oscillations, and wave motion.
Provides strong mathematical foundation and analytical problem-solving skills essential for quantitative analysis.
Kinematics
Dynamics
Conservation Laws
Oscillations
