As this class places strong emphasis on the hands-on experience, you will be working with data for the majority of the time in the class. To optimize the learning experience, it is mandatory for all participants to be equipped with a laptop and installed the required the software* before the course.

 

To reduce the environmental impact and contribute to sustainability efforts, ISCA will contribute our part by eliminating the printing of course materials for selected courses with effect from 2023. Tips: To make your paperless learning experience more enjoyable, you may bring along a digital device such as a Windows based laptops or tablets to read your online materials during the class. QR code will be provided in the class for you to download the materials in PDF. Join us and be a Difference Maker!

Programme Objective
 

At the end of the course, the learner will be able to

1. Understand the data analytics process and critical success factors for implementation
2. Apply analytics techniques such as market basket and clustering using Google Colab
3. Learn to perform data cleaning and convert images/scans to digital data using OpenRefine and Tabula (open-source tools) to enhance productivity
4. Learn techniques to visualize data to improve aesthetics using Tableau Public. 

 

This course will cover some of the most practical analytics techniques for classification and regression so that thelearners can discern hidden patterns within your data and identify the winning edge.

For participants who faces ‘dirty’ data or lack of data at work, you will also be exposed to selected open-source tools to improve your productivity; and learn about other processes that you can consider to help your organisation embark on the digitalisation journey with the least cost.

Key takeaways: -

1. Appreciate the capability and limitation of data analytics and critical success factor for implementation
2. Implement analytics techniques such as market basket and clustering to identify correlation between data points 
3. Use open-source tools (example, KNIME) for data cleaning and improve office productivity
4. Visualize data in an attractive manner for effective communication

*Links for software installation:

1. https://openrefine.org/download.html
2. https://tabula.technology/
3. Please ensure that you have a google account or sign up via https://accounts.google.com/signup

Programme Outline

Module 1: Introduction to five-step data analytics process and critical success factors for implementation 

Module 2: Introduction to Google Colab as a quick means to access an IDE and computing power; and apply analytics techniques such as market basket and clustering   

Module 3: Exposure to open-source tools such as OpenRefine and Tabula for data cleaning and convert images/scans to digital data to enhance office productivity

Module 4: Exposure to Tableau Public to quickly visualize data to improve aesthetics.  
 

Training Methodology

A combination of lecture and hands-on exercises is expected for this class. The course has been specially designed to help participants learn analytics techniques and productivity tools that might be relevant to their work so they can apply it back at work.   

Closing Date for Registration 

1 Week before Programme or Until Full Enrolment.  

Intended For

This course is specially designed for professionals who do not have programming background and will like to learn more about how data analytics and other digital tools can help you improve your workplace productivity

Programme Facilitator(s)