With the ongoing digital revolution and advancements in technology, organizations can dramatically improve their effectiveness by collecting and analysing insights from relevant data. What is needed to equip yourself to succeed with applied data science in your field of work?
Data Science Bootcamp equips participants with the knowledge and skills of data science, using R as the core programming language so that they can harness the predictive power of data to solve interesting problems. Through the Bootcamp, participants will also be equipped with Tableau, and acquire a design thinking mindset to achieve decision intelligence.
This advanced part-time course is for Professionals, Managers, Executives, and Technicians (PMETs) to jump-start a career in data science.
View course schedule here.
You will be equipped with programming tools used to analyze and visualize data. You will learn and apply concepts related to statistics for data, machine learning algorithms and design thinking. While computer systems can execute calculations meticulously, this course aims to develop participants who are capable of leading data-led projects responsibly, through the use of decision intelligence to turn information into better actions.
Course Date: TBC
Application Period: TBC
Duration: 6 months (part-time)
Delivery Mode: Classroom and Online
- Code with the R programming language using RStudio and RMarkdown
- Learn intermediate R functions to manage and aggregate data
- Clean data and manipulate using Tidyverse dplyr package
- Acquire basic descriptive statistics concepts
- Gain insights with exploratory data analysis using cases with industry applications
- Asynchronous learning using DataCamp
- Generate visualization plots with ggplot2 using RStudio
- Generate flexdashboard
- Build interactive plots and maps
- Develop impactful visualizations using Tableau
- Design interactive Tableau dashboards that provide real-time value
- Dive deep into machine learning algorithms
- Learn the mathematical concepts under that hood of algorithms
- Supervised and unsupervised machine learning
- Build regression and classification models
- Linear regression, logistic regression, decision trees, random forest, knn, Naive Bayes, K-means, hierarchical clustering, time series and neural networks
- Evaluate, validate and tune models for improve performances
- Understand the design thinking process
- Learn from design thinking use cases applied to data science
- Acquire strategies for decision intelligence
- Build a demonstrable capstone project to showcase competency in data visualization and machine learning
Loh Wai Tuck is a senior lecturer at the School of Interdisciplinary Studies, Ngee Ann Polytechnic.
He has 14 years of software development, with application development and project management experience. He also contributed at least 14 years to the teaching of Math and IT. He had previously provided regional support on technical consultancy of GIS solutions and has a broad exposure to both the technical and management aspects of software development life cycles. With many years of training experience and working with corporate clients, he is fully equipped with adult training and coaching skills.
Karen Tan is a senior lecturer at the School of Interdisciplinary Studies, Ngee Ann Polytechnic.
She is motivated to make STEM learning accessible to all. Her involvement in the development of autonomous vehicles in the last few years lured her into machine learning. She in continuously sharpening her skills in the area of data science and wants to work on projects for the social good. Her prior work experiences in the manufacturing and engineering sector equipped her with technical readiness. She strongly believes in training skills that can be applied at the workplace.
Dr Ricky Chua is a trainer at the School of Interdisciplinary Studies, Ngee Ann Polytechnic. He has an active interest in applying data science to investments and financial trading. An educator since 1999, Ricky has taught a myriad of subjects ranging from investing, to materials science, to mathematics, to data science. His one biggest passion is in teaching and learning, and he is known for his highly energetic presence in class. Combined with the use of learning activities that make learning applicable and fun, Ricky makes the special effort to ensure all his students are entertained as they learn.
Zhang Ziwei is a lecturer at the School of Engineering, Ngee Ann Polytechnic. She has worked as a school data analyst since 2018. Ziwei has very strong interest in data science and is proficient in data visualization. She believes that data science will change the way people live and work in the near future. She is trained in data analytics in R and continues to expand her capability in Tableau, R and Python to make data insightful and applicable.
Certificate of Performance will be awarded to participants who achieve at least 75% attendance and pass assessments.
- Preferably with a local Polytechnic Diploma or recognised Degree (with English as the medium of instruction) in business, engineering, technology, or any other disciplines with at least one (1) year of relevant work experience.
- Applicants should have an analytical mindset and an interest to learn problem solving with algorithms and data structures.
- Applicants should have basic digital literacy and be willing to acquire programming skills
Important: Students enrolled in the course are expected to bring their personal laptops with the Windows 10 operating system.
Funding period for this course is from 1 Oct 2021 to 30 Sep 2024.
All Singaporeans aged 25 and above can use their $500 SkillsFuture Credit from the government to pay for a wide range of approved skills-related courses. Visit the SkillsFuture Credit website to choose from the courses available on the Training Exchange course directory.
Union Training Assistance Programme (UTAP)
NTUC members enjoy 50% unfunded course fee support for up to $250 each year (or up to $500 for NTUC members aged 40 years old and above) when you sign up for courses supported under UTAP (Union Training Assistance Programme). Please visit e2i’s website to find out more.
*Additional course fee funding
Additional course fee funding support of up to 95% of course fees for jobseekers with greater needs. Individuals must be Singapore Citizens and meet one of the following eligibility criteria:
- Long-term unemployed individuals (unemployed for six months or more); or
- Individuals in need of financial assistance – ComCare, Short-to-Medium Term Assistance (SMTA) recipients or Workfare Income Supplement (WIS) recipients; or
- Persons with Disabilities
For more information on course fee subsidies, please refer to SSG website here.
Ngee Ann Polytechnic reserves the right to reschedule/cancel any programme, modify the fees and amend information without prior notice.
(Course fee is payable upon acceptance. It is inclusive of 7% GST and subject to review.)
|GST payable for all funding-eligible applicants*||$378|
|GST payable for full course fees||$1260|
*As per SSG’s policy, the GST payable is calculated based on 7% after the baseline funding subsidy of 70%.
|Applicants / Eligibility||Fees|
|Full course fee||$19260.00|
|Singaporeans aged below 40, Permanent Residents||$5778.00|
|Singaporeans aged 40 & above qualified for SkillsFuture Mid-Career Enhanced Subsidy||$2178.00|
|Eligible Applicants for Additional Course Fee Funding Support*||$1278.00|