Diploma in Data Analytics

Cloud computing has become a high demanding skill to many companies as they speed up their adoption of such digital tools. As the market for cloud services is vast and growing, many companies are built and run on the cloud, and they need talents who have the skills to help them drive technical architecture, design, and delivery of cloud systems. LSBF Singapore aims to bridge the education to career divide by adequately preparing students with the skills and knowledge to enter high-demand technology fields.

The AWS cloud computing curricula has been incorporated into the Diploma in Data Analytics, under the ‘Cloud Computing’ module at LSBF Singapore. Currently, LSBF is working towards expanding the scope of collaboration and integrating this into other modules and programmes being planned to be rolled out in the near future. 

The Diploma in Data Analytics programme consists of essential core modules such as Statistical Analytics, Data Visualisation, Data Analytics, Machine Learning, Cloud Computing, App Development, Internet of Things, and Project Management. All of which are essential and foundational skill sets and knowledge domains for those who intend to blaze a path in this industry.

All students participating in the Diploma in Data Analytics programme at LSBF Singapore will be enrolled in AWS Educate. LSBF students will be provided with AWS Promotional Credits to gain real-world and hands-on experience using AWS cloud technology. Learn more about the partnership here

Diploma in Data Analytics

Key Facts

  • Duration: 8 months (full-time), 12 months (part-time)
  • Intake dates: Start in January, April, July, October
  • Delivery Mode:
    • Live Online
    • On campus
  • Fees: SGD $4,980 (local students) / SGD $7,500 (international students)
  • Discount available: up to 5% OFF* for July intake


    *T&C apply. 

Throughout the course, students are fully supported and their development is checked frequently by progress assessments. Student performance and satisfaction is monitored to ensure that the course meets students’ academic and personal development needs; and industry contacts ensure that the programme is relevant and suitable for the demands of a career in the industry. With the Diploma in Data Analytics, graduates can pursue entry-level occupations across many industries, such as business analysts, web and social media analysts, and research analysts. 

The main aim of the Diploma in Data Analytics is to give students the knowledge and practical insight into the workings of the business analytics industry. In particular, students will get an insight into how big data is managed and useful information extracted to better make informed decisions. Holders of the Diploma will be able to demonstrate detailed knowledge and critical understanding of the major concepts in big data management. 

The Diploma in Data Analytics aims to:

  • Develop students’ competence and practical skills in big data management.
  • To lay the foundation for future pathway and continuing professional development.
  • To provide students with the relevant knowledge and understanding of big data management as it relates to the wider business context
  • The knowledge and skills that will enable them to follow a career in all areas of business analytics and a wide range of careers in business, finance, marketing, logistics and administration.

Graduates of the Diploma in Data Analytics should be able to provide pivotal support to various departments within an organisation across all industries. In particular, their practical knowledge of the big data management and its application in the business environment will make Graduates of the Diploma in Data Analytics valuable members of any organisation.

On successful completion of this programme, students should be able to:

  • demonstrate relevant business analytics knowledge and understanding of the basic principles of big data management which will equip them with an awareness of the operation of analytics in all aspects of their careers
  • demonstrate proficiency in identifying analytical issues and know how to use the their knowledge effectively across a range of problems
  • interpret situations which require analytical input and contribute meaningful and calculated solutions in a timely manner
  • effectively communicate information, arguments and analysis in a variety of forms to specialist and non-specialist audience
  • demonstrate cognitive skills of critical thinking, analysis and synthesis
  • demonstrate effective problem solving and decision making using appropriate quantitative and qualitative skills including identifying, formulating and solving problems
  • take and demonstrate responsibility for their own learning and continuing personal and professional development
  • undertake further training, develop existing skills and acquire new competences that will enable them to assume significant responsibility within organisations

Assessment Outline

Mid-Term Quiz 1 20%
Mid-Term Quiz 2 20%
Final Project 60%
Total: 100%

Assessments Profile

  1. Quiz 1 & 2 (40%)
    • This will be in the form of an in-class quiz, individual basis.
    • Students to be communicated on quiz and assessment outlines/ parameters before course and unit commencement.
    • Students are tasked to submit the Quiz.
  2. Final Project (60%)
  • Students to be communicated on the final project and assessment outlines/ parameters before course and unit commencement.
  • Lecturer will go through with the students and highlight the importance of relevant topics during the final revision class.
  • Students are required to submit the final project.

Student must achieve an overall passing grade of 40%. If students fail to achieve an overall passing grade of 40%, students will be permitted one retake attempt in each failed assessment and failure of this retake will require students to re-module the failed module(s) again in full prior to additional retake attempt.

Lectures, tutorials, seminars, workshops


STP Holders: 90%
Non-STP Holders: 75%

1 : 40

Minimum Age: 18 years

Local students shall possess one of the following:

  • At least two passes in GCE ‘A’ Level
  • International Baccalaureate (24 points)
  • Local Polytechnic Diploma in any field

International students shall possess one of the following:

  • Completion of Year 12 High School Qualification or equivalent qualification from respective home countries
  • Completed International Baccalaureate (24 points)
  • Equivalent Local Polytechnic Diploma in any field in respective home countries



Both local and international students MUST fulfil the minimum English language entry requirement of one of the following (except Mandarin programmes):

  • Achieved grade C6 or better in English language in GCE O level
  • Pass in English Language in Year 10 High School qualification or equivalent
  • IELTS 5.5/TOEFL 550
  • Completed LSBF Preparatory Course in English Upper Intermediate Level

Students with non-standard entry requirements (e.g. other PEI qualification, lack of equivalent Year 12 in home country, etc.) will be assessed on a case by case basis subject to approval of the Academic Board.

Full-time students attend three hours per day plus directed/independent study for a period of 8 months from Monday to Friday. Part-time students attend three-hour lessons, two or three nights a week for a period of 12 months.


This module will get students familiar with basic statistical concepts and applications for collection, analysis and interpretation of data for decision making using data.

This module is to prepare students for data preparation and ETL data from different sources and combine them into a single dataset. Students perform more machine learning concepts and algorithms and apply them for text mining and image analytics.

This module will get the student familiar with concepts of machine learning and data mining for predictive analytics. Students learn what are the algorithms available, what they do and how to choose the best one and apply it to their data. Students learn to make predictions with the output of the model and compare them across different models. Students will be able to apply these concepts in business application and other fields by studying patterns in the data and using them to make predictions.

This module is to prepare students for performing tasks in the cloud. Students are introduced to the concepts of cloud computing such as data bases & storage, creating virtual servers and security.

This module will get the student familiar with concepts of IOT data for analysis. Students learn how to extract IOT data and store in a cloud server. Students perform data extraction from IOT devices and display the data for monitor in the web.The monitored data will be store in the cloud server. Student will learn to download data for data analysis.

This module is to prepare students for creating simple apps to be deployed. Students will learn how to design the interface for their apps and store and manipulate data, have logic sequences and making decision (logic) as well as mobile features. Students will also learn how to automate processes in app logic.

This module will get the student familiar with concepts of project management following closely the PMBOK syllabus. Students will grasp the concepts of project management and will benefit greatly in their business & IT undertaking. Students will know the stages of each project from start to finish and all the various disciplines of project management lifecycle.

This module will get the student familiar with state-of-the-art visualisation capabilities. Students will use BI software to visualise data for insights and analysis. Create own calculated fields and parameters, as well as join and blend different data sources.

Request More Information

Contact a programme advisor by calling
+65 6580 7700

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