The digital era is here to stay and it created an important commodity – data. Future proof your career by building deep skills to work with data.
In collaboration with AI Singapore (AISG), SP offers a Minor in Data & Artificial Intelligence. This Minor is open to all students except for students from Data & AI disciplines.
Students will take five (5) prescribed elective modules to build relevant data skills and be able to apply skills learnt in a relevant industry project, curated by SP Data Science and Analytics Centre with support from AISG, for their internship. Students who successfully complete both the Minor and internship will be awarded an additional e-certificate in AISG’s AI Data Apprenticeship Programme (AIDP).
Guidance on how the five elective modules should be taken:
Students will need to successfully complete the first block of elective modules (Fundamentals and Automation of Data Anaylsis, Programming for Data Science) in any sequence. Students will then progress to undertake the second block of elective modules (Data Visualisation for Business, Thinking with Data for Decision Making) in any sequence. Upon successful completion of the electives in the second block students will undertake the last elective module (Machine learning in Python).
Students who successfully complete all five elective modules will earn a Minor in Data & AI.
The synopses of the five elective modules are as follows:
|1.Fundamentals and Automation of Data Analysis||This elective equips students with skills in data analysis and its automation, that AISG’s AIDP program trains its participants in. This practical elective is designed to equip students with the essential skills to perform data analysis using Excel. It further aims to equip students with the necessary skills to automate repetitive data analysis tasks in Excel, using Robotic Process Automation (RPA). In particular, this elective provides a much needed platform to train students in the integration of RPA with Excel to automate tedious, monotonous and repetitive tasks with the important aim of making the data analysis pipeline efficient.|
|2. Programming for Data Science||This module provides students with the fundamental skills to code applications to retrieve, clean and visualize data using the Python programming language. Students will learn how to apply Python packages to describe data, explore data and to create visualizations that can help them gain useful insights from it.|
|3. Data Visualization for Business||This module is designed to equip students with practical skills needed in processing, summarising and understanding data through visual analytics, in particular, via exposure to the Power BI platform and Python programming. Students will develop an appreciation of the visualization workflow and an understanding of the types of visuals that may be created for representing data, based on the complexity of the problem. The students will also acquire the skill of developing data dashboards progressively, via the integration of Power BI and Python, to facilitate effective monitoring of data. Students will apply skills learnt in the course, in creative ways to develop dashboards with real world data.|
|4. Thinking with Data for Decision Making||This module aims to equip students with sound statistical concepts and techniques to conduct exploratory data analysis for various types of datasets, to draw insights and make inferences. Students will be trained to use Python and its libraries to represent, analyse and interpret data.|
|5. Machine Learning in Python||This module introduces participants to the fundamentals machine learning (ML) techniques. Students will be introduced to various Low-code tools for Machine Learning (e.g. Microsoft Azure Machine Learning Studio, Orange Data Mining, and PyCaret/Scikit-Learn Python ML Library). Students will apply the knowledge gained to build a functional ML models. This model can be for improved data analysis beyond classic statistical techniques|
Samples of past projects with students’ involvement
DSAC provides opportunities for SP students to be involved in the Centre’s industry projects, events and roadshows.
DSAC encourages students to join local AI groups. For example, you may want to check out SPAI, a student-led AI club in SP consisting of a community of AI enthusiasts determined to serve society through AI. Find out more about SPAI here.
Internship @ DSAC
What do our interns have to say?
Keane Ng, (Survey Feedback Analysis System), Sep 21- Feb 22, SoC Diploma in IT
“Internship at DSAC was a fufilling experience to help me grow and learn through an industry perspective. Helping to integrate emerging technology into companies/services that are growing.
I love that we have our own space to work at first of all, I also have kind supervisors/mentors & colleagues that help me to go through the project at a suitable pace, helping me to learn on the job as well.”
Li Xinyi, (Computer Vision Project), Sep 21- Feb 22, SoC Diploma in IT
“Very relevant to what I’ve learnt in school with a conducive environment for learning. I liked that the people around me were very welcoming and generally very helpful with any problems I had which made the internship a pleasant experience.”
Chan Choon Qi, (RPA Project Using TagUI), Sep 21- Feb 22, SoC Diploma in IT
“Everything is great! 5 months of learning a lot of new things that I did not see before in my 3 years of polytechnic education. 5 months not wasted but enjoyed.”
Wan Zhenyu, (RPA Project Using TagUI), Sep 21- Feb 22, SoC Diploma in IT
“My internship has been meaningful as I have been learning a number of interesting things. While it may have been stressful, it was also fun and worth it.”
Damian Tan, (Text to Speech Project), Sep 21- Feb 22, SoC Diploma in IT
“I like being able to explore Speech to Text and NLP in general and being able to code independently. I have learnt a lot during this period, and enjoyed my time in this internship.”
ADJUNCT TEACHING OPPORTUNITIES
There are opportunities for adjunct teaching of short courses related to Data Science and modules within our Specialist Diplomas.
Interested parties, please email to firstname.lastname@example.org.