Master of Science in Computer Engineering (MSCPE)

CPE110M

Embedded Systems

This course provides advanced topics in embedded systems design using contemporary practice; interrupt-driven, reactive, real-time, object-oriented, and distributed client/server embedded systems. Students are required to design and implement an embedded system based on the selected application area.

CPE413M

Computer Algorithms

This course introduces the design and analysis of algorithms. Students will explore different algorithm design paradigms like divide-and-conquer, dynamic programming, and greedy approaches. They will gain practical experience with various applications, including sorting, searching, graph algorithms, and string processing. Additionally, the course emphasizes analyzing algorithms using different complexity measures (worst-case, average-case, amortized) to understand their efficiency.

CPE311M

Distributed Computer Networking

This course focuses on the role, model, and needs of representative distributed computer networking applications, reference models of computer networks, transporting information reliably through mechanisms and protocols, network interconnection, addressing, routing, and related issues, as well as local, regional, and long-distance networks

CPE510M

Computer Architecture and Organization

This course focuses on the underlying design principles and the impact of these principles on computer performance. General topics include design methodology, processor design, control design, memory organization, system organization, and parallel processing

CPE511M

Digital System Design

This course introduces the graduate student to a new way of designing digital systems using Hardware Description Language. The students will be immersed in various machine problems that will train their skill in hardware modelling. Emphasis will be given to their ability to make their model 100% synthesizable on a target hardware library i.e., the Field Programmable Gate Array.

CPE512M

Electronic Product Design and Development

This course provides in-depth training and hands-on experience on electronic product design and development. Topics include product planning, methodology, component selection, prototyping, product testing, and project documentation.

CPE513M

Microprocessor Core Architecture Design

This course is a follow up course for the Digital Systems and Design as its prerequisite. The Computer Engineering graduate student will be taught how to analyze the control and datapath of a given microprocessor.  Timing and signal flow within the entire operation of the microprocessor will be analyzed first. The students will then be asked to implement the core architecture hardware model using Hardware Description Language.

CPE210M

Advanced Robotics

This course aims to educate students about the concepts behind robotics technology that are in research, industries, and manufacturing processes. Studies on robot kinematics and transformations are conducted. The mathematics of robot manipulation and manipulator modeling are discussed. Robotic sensory devices are investigated to demonstrate the role played by internal sensors in the control of individual robotic joints, and also by external sensors in providing the robot with knowledge about its external environment. Special attention is focused on the development of a multi-robot cooperative system. Theoretical concepts and real-time applications of cooperative mobile robots are studied. Computer considerations for vision, path planning, and navigation for autonomous mobile robots are analyzed. The students are required to do research papers and oral presentations on topics concerning robot applications for humanity.

CPE290M

Hardware Human-Machine Interface

This course tackles the foundation of human-machine interaction and applies it in the design, implementation, and/or evaluation of everyday things. Topics include interaction design, user modeling, design techniques, prototyping, and evaluation. For this course, human-machine interaction with hardware integration is a must.

CPE310M

Computer Communications

This course introduces the principles and practice of computer networking, emphasizing data communication and the lower layers of the OSI and TCP/IP protocol architectures. It covers a wide range of topics, including network architectures, protocols, algorithms, and applications. This course will provide a comprehensive introduction to computer communication, covering both the theoretical and practical aspects of the field.

CPE312M

Network Management

This course focuses on network architectures, the role of virtual networks, quality of service, provision of multicast, network reliability, and principles of network management.

CPE313M

Network Security

This course focuses on network security, including computer and information security.  It includes discussions and practical exercises in risk management, threat modeling, applied cryptography, malicious software, computer communications security, intrusion detection and prevention, software and operating system security, auditing and forensics, reverse engineering, and social engineering.

CPE390M

Blockchain and Software-Defined

This course explores the advanced concepts and applications of blockchain technology and software-defined networking (SDN) in the context of computer engineering. Students will gain a deep understanding of the underlying principles, design, and implementation of blockchain systems and SDN, along with their real-world applications.

CPE391M

Fundamentals and Security in Internet of Things

This course aims to introduce the concept of IoT and its impact on our daily lives, to understand the architecture and components of IoT, and to address the challenges and solutions of deploying IoT in reality. Students will learn to make design trade-offs between communication and computation costs and hardware and software. In addition, cybersecurity is a critical design issue of the IoT system. From this course, students will become aware of the cybersecurity issues raised by IoT and gain knowledge of the related security techniques such as the blockchain technology. Students will also be required to model an IoT system and implement security techniques.

CPE410M

Fundamentals of Machines Learning

This course will introduce the fundamental concepts of machine learning, including supervised learning, unsupervised learning, and reinforcement learning. Students will also learn about a variety of machine-learning algorithms, such as linear regression, logistic regression, decision trees, support vector machines, neural networks, and clustering. The course will also cover the practical aspects of machine learning, such as data preparation, model selection, and evaluation.

CPE411M

Neural Networks and Deep Learning

This course will cover a comprehensive introduction to neural networks and deep learning theories, algorithms, and applications. Topics include artificial neural networks, deep learning, convolutional neural networks, recurrent neural networks, autoencoders, generative adversarial networks (GANs), optimization algorithms, regularization, transfer learning, and ethical implications of neural networks

CPE412M

Data Mining on Massively Big Data Sets

This course will explore the techniques and algorithms used in data mining and machine learning to analyze extensive datasets. It will focus on utilizing MapReduce and Spark for developing parallel algorithms capable of handling large data volumes.

The course covers a range of topics, such as: Identifying frequent itemsets and association rules, searching for near neighbors in high-dimensional data, applying Locality Sensitive Hashing (LSH), reducing dimensionality, building recommendation systems, executing clustering techniques, analyzing links, conducting large-scale supervised machine learning, processing data streams, extracting structured data from the web, and understanding web advertising strategies.

CPE490M

Principles of Computer Vision

The course introduces the concepts involving computer vision. Foundational concepts shall be discussed, which are imaging concepts, features, reconstruction, and perception. Image processing algorithms shall also be discussed. With these concepts, designing a computer vision system shall also be discussed with specific applications.

COE5000

Engineering Orientation

The course includes topics on the DLSU history, mission statement, organizational structure, key officers/offices; the Brothers of the Christian Schools, the life and writings of St. John Baptist de la Salle; Lasallian core values and professional ethics.

COE996M

Oral Comprehensive Exam

COE5200

Methods of Research

A study of the fundamentals of research designs, analysis and interpretations of data, project feasibility studies, and qualitative research techniques

COE571M

Techpreneurship

This course takes the participant through entrepreneurship in technology ventures, which is about commercializing technology ideas into viable enterprises. It is about training techies, scientists and researchers in the skills and attitudes of entrepreneurs, about empowering them to realize the opportunities and commercial values arising from their ideas, technologies, technology applications or products.       The course examines the development of ideas and how   these are translated into opportunities and eventually businesses; it challenges the students to go through the process of writing a business plan, which will be their final output in this course.