DATA PRODUCT I (VISUALISATION) CAPSTONE (Part of SCTP Certificate in Data Analytics with AI)
About This Course
In this final Capstone project, learner will be immersed in a practical and integrative experience in applying the knowledge and skills learnt throughout the entire course. Building on the techniques learnt in data modelling, visualisation and transformation, learners will be tasked to solve business scenarios by analysing and deriving insights using real-world dataset. Learner will showcase in this capstone project a final data product on data visualisation that delivers innovative, data-driven solutions to stakeholders in this end-to-end project development.
What You'll Learn
> Propose Problem Statement and Data Product plan to solve business challenges.
> Design Conceptual and Logical data models to support data product development.
> Perform exploratory data analysis to identify underlying data patterns, trends and analytical insights using data visualisation tools.
> Construct Extract-Transform-Load (ETL) pipelines to process data from various sources using programming.
> Deploy Data Product using Data Visualisation to resolve the business challenges.
This course is part of SCTP Data Analytics with AI
(1) The list of topics covered in this course:
> Problem Statement Framing
> Data Modelling
> Data Visualisation
> Data Transformation
> Data Product Design
(2) Instructional Methods:
> Supervised Field and Practical Training
> Capstone Development via Agile Methodology
> One-year Udemy subscription offering access to curated course titles, enabling self-directed learning to complement formal training. Learners can explore and develop skills at their own pace through this comprehensive online learning platform
(3) Duration of Course:
200 hours
Entry Requirements
Applicants for the course should possess a diploma/degree from a local polytechnic/university or is a ITE graduate with minimum of 2 years working experience, preferably in a related field. Holders of other equivalent academic qualification from foreign institutions will be considered on a case-by-case basis.
Applicants who do not meet the entry requirements may be considered for admission to the course based on evidence of at least 5 years of relevant working experience or supporting evidence of competency readiness. Suitable applicants who are shortlisted may have to go through an interview and/or a proficiency test.