Bachelor of Science in
Computer Science
with specialization in Data Science
The Bachelor of Science in Computer Science (BSCS) program includes the study of computing concepts and theories, algorithmic foundations, and new developments in computing. The program prepares students to design and create algorithmically complex software and develop new and effective algorithms for solving computing problems.
Program Educational Objectives
Three (3) years after graduation, alumni of BS in Computer Science programs shall:
| OBJECTIVES | GRADUATE ATTRIBUTES |
|---|---|
| 1 Be employed in the IT industry or established a technology startup company; | Competent and equipped with research-based and entrepreneurial spirit |
| 2 Demonstrate professionalism, competence and innovativeness in conceptualizing, developing, and implementing computing solutions; | Ethical, critical thinker, problem solver, creative, and innovative |
| 3 Embark in lifelong learning or research to attune to the continuous innovation in the computing and IT profession; and | Life-long learner |
| 4 Exhibit leadership, teamwork, and commitment to their respective local or global organizations. | Collaborative and with leadership skills |
- Program Outcomes
- Apply knowledge of computing fundamentals, knowledge of a computing specialization, and mathematics, science, and domain knowledge appropriate for the computing specialization to the abstraction and conceptualization of computing models from defined problems and requirements;
- Identify, analyze, formulate, research literature, and solve complex computing problems and requirements reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines;
- Apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems in a way that demonstrates comprehension of the tradeoffs involved in design choices;
- Have knowledge and understanding of information security issues in relation to the design, development and use of information systems;
- Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations;
- Create, select, adapt and apply appropriate techniques, resources and modern computing tools to complex computing activities, with an understanding of the limitations to accomplish a common goal;
- Function effectively as an individual and as a member or leader in diverse teams and in multidisciplinary settings;
- Communicate effectively with the computing community and with society at large about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions;
- Recognize the legal, social, ethical, and professional issues involved in the utilization of computer technology and be guided by the adoption of appropriate professional, ethical and legal practices;
- Possess technopreneurship mindset;
- Recognize the need, and have the ability, to engage in independent learning for continual development as a computing professional; and
- Preserve and promote “Filipino historical and cultural heritage”.
- Curriculum
1st Year • 1st Semester
Course Name Units Introduction to Computing 3 Computer Programming 1 3 Mathematics in the Modern World 3 Understanding the Self 3 Fitness and Wellness 2 English Enhancement Course 3 The University and I 2 National Service Training Program 1 1 1st Year • 2nd Semester
Course Name Units Computer Programming 2 3 Discrete Structures 1 3 College Algebra 3 Readings in Philippine History 3 Purposive Communication 3 Rhythmic Activities 3 The Family 2 National Service Training Program 2 1 2nd Year • 1st Semester
Course Name Units Discrete Structures 2 3 Data Structures and Algorithms 3 Object-oriented Programming 3 Networks and Communication 3 Calculus 3 The Contemporary World 3 Art Appreciation 3 Individual Sports (Swimming) 2 2nd Year • 2nd Semester
Course Name Units Information Management 3 Application Development and Emerging Technologies 3 Algorithms and Complexity 3 System Architecture and Organization 3 Science, Technology and Society 3 Ethics 3 Individual and Team Sports 2 3rd Year • 1st Semester
Course Name Units Operating Systems 3 Automata Theory and Formal Languages 3 Social Issues and Professional Practice 1 3 Software Engineering 1 3 Parallel and Distributed Computing 3 Data Science Fundamentals 3 Panitikang Filipino 3 Academic Writing 3 3rd Year • 2nd Semester
Course Name Units Programming Languages 3 Software Engineering 2 3 Information Assurance and Security 3 CS Thesis 1 3 Technopreneurship 3 Intelligent Systems 3 Data Warehousing for Business Intelligence 3 Retorika 3 3rd Year • Summer
Course Name Units Applied Data Science with Python 3 Applied Data Science with R 3 Great Books 3 4th Year • 1st Semester
Course Name Units Human Computer Interaction 1 System Fundamentals 3 Data Visualization and Storytelling 3 Data Analysis Using Statistical Software 3 CS Thesis 2 3 English for Occupational Purposes 3 Foreign Language 3 Rizal’s Life, Works and Writings 3 4th Year • 2nd Semester
Course Name Units CS Practicum 6 infoDisclaimerThe curriculum is subject to modification without prior notice. For precise and current listings, kindly coordinate with our registrar department.
- Estimated Fees
Particular Amount Estimated Total Fees per semester (including tuition and other fees) ₱32,748.00 infoDisclaimerThe particulars and corresponding amounts are subject to modification without prior notice. For precise and current listings, kindly coordinate with our treasury and assessment department.
- Career Opportunities
Entry-level Positions:
- Data Analyst: Entry-level data analysts work on collecting, cleaning, and analyzing data to provide insights and support decision-making.
- Junior Data Scientist: These professionals assist senior data scientists in tasks such as model development, data preprocessing, and data visualization.
- Research Assistant: Data science graduates can work as research assistants in academic institutions, helping professors and researchers with data analysis for research projects.
- Business Intelligence Analyst: BI analysts focus on creating reports and dashboards for business performance tracking and data visualization.
- Data Engineer: Junior data engineers help design, build, and maintain data pipelines and databases.
Mid-Level Positions:
- Data Scientist: Mid-level data scientists take on more complex tasks, such as developing predictive models, conducting in-depth data analysis, and contributing to decision-making processes.
- Machine Learning Engineer: ML engineers build and deploy machine learning models, working closely with data scientists to put models into production.
- Data Analyst Team Lead: Team leads manage a group of data analysts and coordinate data-related projects.
- Senior Data Engineer: These professionals take a lead role in designing and optimizing data infrastructure.
- Analytics Manager: Analytics managers oversee a team of analysts and are responsible for setting the analytical strategy and goals for the organization.
Senior-Level Positions:
- Principal Data Scientist: Senior data scientists work on high-impact projects, lead research, and provide strategic data-driven insights to the organization.
- Data Science Manager: These professionals manage and lead data science teams, ensuring projects are executed efficiently and effectively.
- Director of Data Science: Directors oversee the entire data science department, set long-term goals, and align data initiatives with business objectives.
- Chief Data Officer (CDO): CDOs are responsible for the organization's data strategy, governance, and data-related decision-making at the executive level.
- Senior Machine Learning Engineer: Senior ML engineers lead the development and deployment of complex machine learning systems.
Managerial/Executive Positions:
- Head of Data Science: As the head of data science, these executives are responsible for the overall strategy, performance, and impact of the data science department.
- Chief Analytics Officer (CAO): CAOs oversee the organization's analytics strategy, aligning it with business goals, and are responsible for driving data-driven decision-making.
- Chief Information Officer (CIO): CIOs have overall responsibility for the organization's data and technology strategy.
- Chief Technology Officer (CTO): CTOs focus on the technology stack, infrastructure, and technical aspects of data management.
- Chief Executive Officer (CEO): In some cases, data scientists with extensive business acumen may become CEOs of data-driven companies, where their data science background informs strategic decisions.
Campus
Manuel S. Enverga University Foundation - Lucena City Lucena
College of Computing and Multimedia Studies CCMS
Keywords
BSCS
CS
computer science
data science
CCMS
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