UNIVERSITY CREDIT RATED QUALIFICATION

Professional Certificate in  Data Science

The Professional Certificate in Data Science provides a foundation in the key knowledge areas required to launch or strengthen  your career in one of the most in demand and fastest growing professions in the world.
COURSE MODE AND DURATION
 Mode: Blended
Duration: 5 months
COURSE FEES
Course Fees before funding
S$ 7,800  
SkillsFuture / PSEA funding eligible

DUAL CERTIFICATION
1.Data Science Institute Professional Certificate
2. Postgraduate Certificate in Data Science*
SOME OF THE ORGANISATIONS OUR STUDENTS AND GRADUATES WORK AT

What skills and knowledge will I gain?

The Professional Certificate in Data Science has been developed by practising data scientists with experience working with major international firms across a wide range of industries. They have identified key skills required for data analysts and data scientists and have also ensured the programme conforms to the European Data Science Framework’s Body of Knowledge.
The course is run as a dual qualification and participants can gain a postgraduate credit-rated qualification on the European Qualifications framework with 30 ECTS credits. These credits can also be used toward's the Institute's Postgraduate Diploma and MSc in Data Science.

Key Skills and Knowledge

  • R and Python programming skills
  • Data management
  • Descriptive and inferential statistics
  • Data visualisation
  • Hypothesis testing
  • Analysis of variance
  • Predictive analytics
  • Business intelligence tools

Tools and Languages

Professional Certificate Programme Modules

You are provided with highly structured and detailed course content, broken down into four distinct units covering core skills and knowledge.  Through our learning management system, you will attend our live group classes, access hundreds of video lessons, data sets, projects and assignments. You will also benefit from tutors that are on hand to provide support and feedback for your exam preparation and project work.
Certificate Modules
MODULE 1

Applied Data Analytics 

Most industry analysis starts with exploratory data analysis. In this module, you will gain a solid understanding of Python and R programming, descriptive statistics, data management, and data visualization. You will learn how to manage and analyze large datasets, uncover trends, and visualize data in ways that support business decisions. This foundational knowledge is crucial for business managers aiming to leverage data for competitive advantage.
  • Exploratory Data Analysis
  • Data management
  • Descriptive statistics
  • Bivariate relationships
  • Data visualisation
MODULE 2

Foundation of Statistics for Data Analytics

A strong foundation in statistics is essential for making informed business decisions. This module covers statistical inference techniques that enable you to draw meaningful conclusions from data. You’ll learn how to test hypotheses, analyze variances, and apply statistical methods to real-world business scenarios, enhancing your ability to make data-driven decisions that can positively impact your organization’s performance.
  • Statistical inference 
  • Principles of statistical inference 
  • Hypothesis Testing
  • Statistical Tests
MODULE 3

Computational Modelling

Predictive modeling is a powerful tool for anticipating future business outcomes. In the computational modelling module, you will learn how to build and validate models that can forecast trends, customer behavior, and other key business metrics. By applying these techniques, business managers and leaders can develop strategies that are proactive rather than reactive, positioning their organizations for success in a competitive marketplace.
  • Predictive Modelling
  • Predictive modelling principles
  • Linear and logistic regression models 
  • Model validation 
  • Foundations of Machine learning
MODULE 4

Capstone Project

In this module, you will select a project from a specific domain relevant to your field of interest. You’ll apply the skills learned throughout the course to solve a real-world problem, providing analysis, insights, and recommendations that could directly benefit your organization. This capstone project not only consolidates your learning but also demonstrates your ability to apply data science techniques to drive business improvements.
  • Data Science in Practice
  • Real world scenarios
  • Presentation and communication skills 
  • Synthesise skills and knowledge

Who is the course for?

The Certificate in Data Science is for people looking to launch a career in data analytics, as well as professionals with experience aiming to strengthen their skill set and gain official recognition. It is aimed at graduates with a bachelor’s degree or equivalent, managers seeking a deeper understanding, and those with relevant professional experience in analytics looking to enhance their employment prospects.  

Entry Requirements:

Diploma OR 
Advanced Diploma OR
Higher Nitec OR
Undergraduate Degree

In addition to meeting formal entry requirements, students should possess:
- Strong numerical skills. -
- An inquisitive mindset and commitment to learning.
- A keen interest in applying data science and analytics to solve real-world business problems.

New Career Entrants
Individuals new to the workforce seeking a foundational entry into the field of data science and analytics
Career Changers
Professionals transitioning from other fields who want to develop essential skills to succeed in data science and analytics
Practising Data Analysts
Those with some analytics experience looking to deepen their skills to advance their careers
Recent Graduates
Graduates of universities, polytechnics and Institutes of Technical Education
Managers and Leaders
Individuals who are serious about leveraging data science and analytics to enhance business performance and make informed strategic decisions.
Upskillers
Those aiming to add data science skills to their existing job roles

Unique Pathway to Internationally recognised Masters in Data Science

The Data Science Institute’s Professional Certificate in Data Science offers a unique pathway to internationally recognized postgraduate qualifications in Data Science—including a Master’s degree—accredited under the European Qualifications Framework. Successful students can join our postgraduate program through Performance-Based Admissions (PBA) or Recognised Prior Learning (RPL) even without an undergraduate degree.

Performance-Based Admissions (PBA) and Recognised Prior Learning (RPL) provide non-traditional routes to postgraduate diplomas and Master’s degrees, considering alternative education backgrounds  from polytechnics, private education institutes, or Institutes of Technical Education and professional working experience
Professional Certificate in
Data Science 
30 ECTS credits
Postgraduate Diploma in
Data Science
60 ECTS credits

MSc. in Data Science
90 ECTS Credits

Employment opportunites across multiple roles and industries

Holders of the Professional Certificate in Data Science will find opportunities in data analytics and data science roles across a wide range of sectors. Data Science and analytics have become  central to organisations and are used across a wide array of industries and business functions.  Here are some examples listed  below:
  • JOB ROLES
  • INDUSTRIES 
  • Data Analyst
  • Finance
  • Business Intelligence (BI) Analyst
  • Healthcare 
  • Cybersecurity Data Analyst
  • Retail 
  • Financial Analyst
  • E-commerce 
  • Risk Analyst
  • Technology
  • Marketing Data Analyst
  • Manufacturing
  • Sales Operations Analyst
  • Energy
  • Healthcare Data Analyst
  • Telecom
  • Operations Data Analyst
  • Environment and Sustainability
  • Environment and Sustainability
  • Government and Public sector

Programme Delivery

Our unique, hands-on learning experience combined with our interactive learning platform and  industry case studies, real worlds data sets, project based assessment led by expert instructors and tutor support allows learners to build their knowledge and practice applying it before bringing it into a professional setting.
Blended Learning Approach
This course combines classroom and online lectures, workshops, and a robust learning platform. It provides face-to-face interactions and the flexibility of online learning, catering to busy professionals.
Course Duration and Commitment
Complete the Professional Certificate in Data Science in five months or less, balancing study time, group sessions, mentorship, project work, and exams, suitable for working professionals and business leaders.
Online Course Content
Course materials are organized into the four course modules on our learning management system, featuring recorded lectures, slides, case studies, quizzes, and practice assignments with real-world business cases.
Communication and Collaboration
Engage in group sessions and one-on-one interactions with mentors, while also networking and collaborating with peers to build valuable professional connections.
Assessment and Projects
Assessments include assignments, exams, and a capstone project using real-world data. This allows you to integrate course elements and apply your skills to address relevant business challenges.
Expert Tutor Support
Expert tutors are on hand to guide you through the course, prepare you for exams and support your project work

Fees and Funding

Full Course Fees before funding

Professional Certificate in Data Science:
Module 1: Applied Data Analytics – $1,200
Module 2: Foundation of Statistics for Data Analytics – $1,800
Module 3: Computational Modelling – $3,000
Module 4: Data Analytics Capstone Project – $1,800
Total Fee – $7,800
(Note: Prices are in Singapore Dollars (SGD) and subject to 9% GST. Funding options are available for eligible

How to Apply and further information

To find our more about the programme email enquiries@trainingvision.edu.sg
Phone +65 88768065

This course is delivered by our training partner in Singapore, Training Vision Institute, and is eligible for SkillsFuture subsidy, SkillsFuture Credit, and PSEA for Singapore citizens and permanent residents.

Singapore citizens aged 40 and above may receive up to 70% funding, while those aged 25 and above, along with permanent residents and LTVP+ holders, are eligible for up to 50% funding. Any remaining fees can be offset using SkillsFuture Credit, PSEA, or UTAP, reducing the need for cash payments. Those aged 21 to 30 may use PSEA for further support.

 PROFESSIONAL Certificate in DATA SCIENCE

Find out more

Please complete this form and a member of our team will get in touch with you to explain how it works.
eiuropean accredited programme (ECTS)

Accreditation

Data Science Institute is a full member college of Woolf, offering accredited degrees under the European Standards and Guidelines (Brussels 2015). Woolf is a global collegiate Higher Education Institution licensed in Europe (license 2019-015), and the operative Policy of Quality Assurance allows member colleges to share the same standards of accreditation while independently managing their own students and faculty. Courses with ECTS credits are specifically designated as such.

See what our students say about us

Mohammed Hamad

Analytics Lead

DXC Technologies

“The course is very strong technically and the support was excellent”

Jehad Mossa

Senior Manager

PWC

“The overall course programme is very complete and I developed my data science knowledge substantially”

Manuel Tanpoco

(Ed.D, MBA)

Professor of Mathematics La Salle University

“As a mathematician and lecturer, I was impressed with the course content and explanation of the statistical methods and algorithms. I also benefited greatly from learning Python and R”

Mohammed Hamad

Analytics Lead

DXC Technologies

“The course is very strong technically and the support was excellent”

Jehad Mossa

Senior Manager

PWC

“The overall course programme is very complete and I developed my data science knowledge substantially”

Manuel Tanpoco

(Ed.D, MBA)

Professor of Mathematics La Salle University

“As a mathematician and lecturer, I was impressed with the course content and explanation of the statistical methods and algorithms. I also benefited greatly from learning Python and R”