Bachelor of Science in Computer Science with specialization in Data Science

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:

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; andLife-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 NameUnits
    Introduction to Computing3
    Computer Programming 13
    Mathematics in the Modern World3
    Understanding the Self3
    Fitness and Wellness2
    English Enhancement Course3
    The University and I2
    National Service Training Program 11

    1st Year • 2nd Semester

    Course NameUnits
    Computer Programming 23
    Discrete Structures 13
    College Algebra3
    Readings in Philippine History3
    Purposive Communication3
    Rhythmic Activities3
    The Family2
    National Service Training Program 21

    2nd Year • 1st Semester

    Course NameUnits
    Discrete Structures 23
    Data Structures and Algorithms3
    Object-oriented Programming3
    Networks and Communication3
    The Contemporary World3
    Art Appreciation3
    Individual Sports (Swimming)2

    2nd Year • 2nd Semester

    Course NameUnits
    Information Management3
    Application Development and Emerging Technologies3
    Algorithms and Complexity3
    System Architecture and Organization3
    Science, Technology and Society3
    Individual and Team Sports2

    3rd Year • 1st Semester

    Course NameUnits
    Operating Systems3
    Automata Theory and Formal Languages3
    Social Issues and Professional Practice 13
    Software Engineering 13
    Parallel and Distributed Computing3
    Data Science Fundamentals3
    Panitikang Filipino3
    Academic Writing3

    3rd Year • 2nd Semester

    Course NameUnits
    Programming Languages3
    Software Engineering 23
    Information Assurance and Security3
    CS Thesis 13
    Intelligent Systems3
    Data Warehousing for Business Intelligence3

    3rd Year • Summer

    Course NameUnits
    Applied Data Science with Python3
    Applied Data Science with R3
    Great Books3

    4th Year • 1st Semester

    Course NameUnits
    Human Computer Interaction1
    System Fundamentals3
    Data Visualization and Storytelling3
    Data Analysis Using Statistical Software3
    CS Thesis 23
    English for Occupational Purposes3
    Foreign Language3
    Rizal’s Life, Works and Writings3

    4th Year • 2nd Semester

    Course NameUnits
    CS Practicum6
    The 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
    The 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.


Manuel S. Enverga University Foundation - Lucena City Lucena

College of Computing and Multimedia Studies CCMS


computer science
data science