Home 9 Advanced Diploma in Information Technology and Data Science (Mandarin) (E-Learning)

Advanced Diploma in Information Technology and Data Science (Mandarin) (E-Learning)

Programme Overview

The Advanced Diploma in Information Technology and Data Science (Mandarin) (E-Learning) is an online course taught in a virtual learning environment. The medium of instruction will be Mandarin.

This E-Learning course is designed to foster understanding of global marketing rules, the essential skills to formulate overall development strategies, and the ability to make long-term business decisions for enterprises.

Programme Aims

The programme will enable the students to:

  1. Mathematical and Analytical Competence

Be equipped with the mathematical, statistical and machine learning foundations necessary for big data batch and real-time processing. Through training in data mining and big data analysis techniques, students will be able to identify, formulate, analyse and solve big data problems in batch processing, stream processing and complex business scenarios using data-driven methods.

  1. Innovative and Responsible Problem Solving

Be guided, through practices in the financial big data or e-commerce stream, to develop innovative and critical thinking and to design socially responsible solutions. They can take into account financial compliance, data privacy, user rights and industry ethics, ensuring that system designs meet both user needs and regulatory requirements.

  1. Technological Proficiency

Develop in proficiency in using big data batch processing platforms, real-time processing platforms, text mining and analysis tools, blockchain and other cutting-edge technologies and be able to select, develop and apply appropriate technologies, resources and digital tools according to different business scenarios to complete data analysis and system implementation.

  1. Teamwork and Leadership

Cultivate the ability to collaborate effectively in cross-role teams, either as members or leaders, valuing active listening, shared responsibility and team strengths, so as to jointly complete complex big data engineering projects.

  1. Communication and Global Perspective

Enhance the ability to clearly communicate big data analysis results, data mining findings, real-time processing solutions, and the value of blockchain/intelligent recommendation technologies, and to express effectively to peers and the public and also develop awareness of global fintech and e-commerce trends, as well as multicultural data perspectives, understanding the differences in big data applications across regions and industries.

  1. Independent and Lifelong Learning

Foster a mindset of continuously tracking cutting-edge big data technologies and a capacity for self-learning, enabling adaptation to the rapid iteration of data technologies and business models in industries such as finance and e-commerce.

Course/ Assessment Structure

The students are required to study nine (9) core modules for a total of 150 credits. Each credit is equal to 10 learning hours.

Core Modules

        Modules

Credits

  1. Big Data Batch Processing Technology and Its Platform

15

  1. Data Mining Techniques

15

  1. Big Data Analysis Technology

15

  1. Big Data Real-Time Processing Technology and Platform

15

  1. Machine Learning Fundamentals

15

  1. Big Data Marketing

10

  1. Text Mining and Analysis

10

  1. Intelligent Referral Technology and Application

15

  1. E-Commerce Big Data Application Practice

10

Admission Requirement

a. Normal Entry

  1. Min age: 18 years PLUS
  2. Academic Level:
    • Obtained Diploma in Information Technology and Data Science (Mandarin) (E-Learning) from United Seas College OR
    • Obtained a relevant Diploma or equivalent qualification, which has either a GCE ‘A’ level Examination or completion of 12 years of formal education as the qualifying entry requirement, and subject to the approval of USC Academic Board.
  3. Min language requirement:
  • Obtained at least GCE O-Level B4 in Chinese language or equivalent

b. Alternative Entry

Mature candidate of minimum age of thirty (30) with at least eight (8) years of working experience.

    Delivery Requirement

    The programme will be delivered through a blended e-learning approach that combines synchronous and asynchronous modes.

    A total of 32 hours will be conducted through synchronous e-learning, allowing students to engage in real-time interaction with lecturers and peers via live online sessions. These sessions will focus on discussions, collaborative activities, and instructor-led guidance to support active learning.

    A further 304 hours will be allocated to asynchronous e-learning, where students will access digital learning materials, recorded lectures, readings, and self-paced learning activities through the institution’s learning management system. This mode enables flexibility and independent study, allowing learners to manage their learning according to their schedules.

    Assessment for the programme will amount to 32 hours and is not included in the teaching hours. Assessments may include assignments, projects, quizzes, or examinations designed to evaluate students’ achievement of the intended learning outcomes.

    The teaching, learning, and assessment strategy for each module has been designed to ensure that teaching methods are appropriate for achieving the module’s learning objectives.

    Assessments will be conducted via a robust online examination platform, ensuring that online examinations are systematically scheduled, performed, and evaluated with integrity.

    Duration

    The program may be pursued on either a full-time or part-time basis. The full-time modality spans a period of eight (8) months, with instructional sessions allocated three hours per day, five days per week, culminating in a total of 336 instructional hours. Conversely, the part-time modality extends over nine (9) months, with sessions scheduled two hours per day, five days per week, also amounting to a total of 336 instructional hours.

    The minimum required enrollment is 30 students.

    Maximum candidature period for a student to complete the course is 36 months.

    Intake Dates

    Every October

    Target Students

    The programme is specifically designed for individuals who have completed USC’s Diploma in  Information Technology and Data Science (Mandarin) (E-Learning) course and wish to further their education by pursuing an advanced diploma in the same specialisation. It primarily caters to students seeking flexible online learning options, offering the convenience of studying from anywhere in the world. The target audience includes both residents of Singapore and learners residing in Southeast Asia and other countries, provided they meet the entry requirements for this online programme.

    Fee Structure

    Course Fee: SGD 7,000.00 + GST.

    Click here for the miscellaneous and other relevant fees. 

    Take the next step

    Speak with our admissions team to find out if this programme is right for you.