Decision Intelligence using Data for Wholesale Trade

Offered by School of Interdisciplinary Studies

Short Course / 6 months/ Delivery Mode: Classroom and Online / TGS No: TGS-2020508942

Course Information
Learning Outcomes
Course Schedule
Lesson Plan
Trainer Profile
Certification
Entry Requirements
Course Fees

Course Information

This advanced course is for Professional, Managers, Executives and Technicians (PMETs) to pursue a career in operations, procurement and sourcing in the wholesale trade sector.

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 harness the best in applied data science in your field of work?

This data analytics course covers core topics in the area of data science, using R as the core programming language, and design thinking to achieve decision intelligence.

Learning Outcomes

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 
Schedule

Next Intake : 3 Jan 2022 – 29 Jun 2022

Application Period: 24 Sep 2021 – 12 Dec 2021

Course Duration: 6 months

Schedule: Mon & Wed, 9am to 5.30pm

Venue: Classroom/Online (Blended)

 

Lesson Plan

Data wrangling & statistics for data
  • 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
Visualization of data with R & Tableau
  • 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
Machine learning modelling for decision intelligence
  • 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
Design thinking mindset for data science and capstone projects
  • 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

Trainer's Profile

Loh Wai Tuck

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

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

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

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.

Certification

Certificate will be awarded to participants who achieve at least 75% attendance and pass assessments.


Entry Requirements

  1. Applicants should have an analytical mindset and an interest to learn problem solving with algorithms and data structures.
  2. Applicants should have basic digital literacy and be willing to acquire programming skills
  3. Preferably with a local Polytechnic Diploma or recognized 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.
  4. Students enrolled into the course are expected to bring along their personal laptop with the Windows 10 operating system installed.

Course Fees

Course Fee is inclusive of GST.

Trainees must fulfil minimum attendance requirements and pass assessments to qualify for course fee subsidies. Trainees who are unable to meet these requirements may be asked to return the course fee subsidies that they have received.

SkillsFuture Credit
This course is eligible for SkillsFuture Credit.

All Singaporeans aged 25 years and above can use their $500 SkillsFuture Credit from the government to pay f​or a wide range of courses. The credits can be used on top of existing course fee subsidies/funding. This is only applicable for self-sponsored applicants and must be applied via the SkillsFuture Portal. More details on the SkillsFuture Credit Claims will be advised upon admission into the course. Find out more about SkillsFuture Credit at www.skillsfuture.sg/credit.

Funding period for this course is from 9 Sep 2020 to 31 Mar 2021.

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.

 

Applicants / Eligibility Fees
Full Fees$12840.00
Singaporeans & Permanent Residents$500.00