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For the full course:

Lesson for current intake starts on

1 February 2021

Polaris is a structured online training program consisting of masterclass and industry project.

The masterclass is conducted by seasoned data scientist from Merck, so that you will learn essential data analysing skills.


The industry project is a collaboration between TalentLink and SeaMoney, a leading digital payments and financial services provider. You are required to apply the data analysing knowledge to solve the project.

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  • Head of Data Science at MSD China (Merck & Co.)

  • 9 years of experience in data science across internet, healthcare, consulting industries

  • Ex-BCG with focus on SEA TMT sectors.

  • Ex-Garena data scientist in gaming

  • Ph.D. from Nanyang Technological University

Learning Objective

Learn data analysis skillsets -> Keys to getting competitive advantage on career growth.
Work on real project from leading digital payments and financial services provider -> Apply what you have learnt into practice.
Interact with data analyst through live Q&A and feedback session -> Identify areas to improve and close the gap.


Polaris comprises of recorded video courses, live Q&A sessions, and weekly project tasks, and all of these are taking place online. The video courses are pre-recorded and are split into bit-size clips according to curriculum. Weekly project tasks are also assigned weekly and students are required to complete the task within that week. Live Q&A sessions will be organized to enable students to ask questions.

Week 1

The first week is about getting the basic ideas of what a data analytics career looks like in different industries, and what are the transferable skill sets and background knowledge you need to have in order to start your career in data analytics. 

Video Lesson 1: Course overview and syllabus. 

Give opening speech, introduction of course structures & principles and expectations after the course

Video Lesson 2: Data analytics career and industrial overview.

Overview of the differences in data analytics roles, careers paths, background requirement and how data analytics looks like in major industries.

Video Lesson 3: Data analytics toolkits and foundational IT knowledge

Introduce the most commonly used data analytics toolkits and explain how these tools are being used by data analytics professionals


Deliverables of Videos 1-3: has a good idea of the job scopes of being data analytics professionals, have a sense of the expectations of different roles and industries. 

Video Lesson 4: SQL basics 

Database knowledge, concept of data models, SQL language syntax and examples.


Deliverables of Video 4: have the basic concept of database, tables, data model, queries and able to perform basic data extractions, basics descriptive calculations and some advanced calculations. Submit an assignment for review.

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Project Details

For the Data Analytics Masterclass, you will be required to complete a project. The project will have 4 main components:

(1) Perform an SQL task to conduct a series of data extraction and computation;

(2) Perform a Python task to conduct data analysis;

(3) Perform a Python machine learning task;

(4) Presenting your final result with PowerPoint.

Polaris Journey

Register by 29 January 2021

Complete weekly video courses and assignment​s

Attend live Q&A sessions to answer your questions

Submit final report to receive certificate of completion

Top performers will have project opportunity

Structured Curriculum

Structured and practical learning on data analytics

Live Q&A Session

Live Q&A sessions to address individual problems

Flexible Schedule

Flexible learning schedule at your own pace

Solve Real Problem

Application of essential technical knowledge to real-life projects



The top performers of the class will have project opportunity


Upon successful completion of Polaris project tasks, candidates will be awarded certificate of completion.
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You may include this into your resume as project experience and boost your chances in seeking for a job.

Course Fee

SGD 799



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