Basic Data Analytics taught with a simple but powerful graphical user interface (“GUI”) drag-and-drop tool targeted at business analysts requiring more sophisticated capabilities than what a spreadsheet can offer.
Understanding and using data is increasingly an important part of an executive function. Whether you are a business analyst, customer service officer, physiotherapist, procurement officer or HR executive – the ability to understand where potential data is coming from, and to properly collect, clean, and then analyse it, will be an important and critical skill.
This course provides the participant with the knowledge and skills to participate in the organisation’s data analytics process without any coding requirements.
We will cover basic concepts of data analysis, processing of data, and visualisation of raw data and processed data to gain insights, followed by building simple models for classification and prediction.
The participant will also learn to use the free and open source data analytics tool – Orange – a powerful and popular Python-based data analytics tool. Orange has a point-click-drag-and-drop GUI, no programming is required.
At the end of the course, participants would be able to:
- Understand the data analytics end-to-end workflow
- Identify where the potential sources of data can come from
- Use a GUI-based analytics tool to process, clean and prepare data for analysis
- Perform basic analysis such as classification and predictions
- Select the most appropriate analytics model to use for a specific task
- Painting the big picture – Big Data and Data Analytics
- The Data Analytics Process
- Introduction to Machine Learning
- A Primer on Artificial Intelligence
- Introduction to Statistical Concepts
- Data Cleaning Concepts/Techniques
- Analytics with Orange Workshop
- Exploratory Data Analysis and Linear Regression-Predicting HDB Prices
- Logistic Regression-Predicting HDB Prices
Experienced with using Excel in manipulating data, charting and basic analysis. No programming experience required.
Who Should Attend
Business Analysts, Customer Service Managers, Physiotherapists, Procurement Officers, HR Executives and any professionals, managers and executives.
Mode of Training
On-campus or Online (Live)
Dr. Amirhassan Monajemi
Amirhassan Monajemi is a Senior Lecturer in AI and Data Science with the School of Continuing and Lifelong Education (SCALE) at the National University of Singapore (NUS). Before joining the NUS, he was with the Faculty of Computer Engineering, University of Isfahan, Iran, where he was serving as a professor of AI and Machine Learning. He was born in 1968 in Isfahan, Iran. He studied towards BSc and MSc in Computer Engineering at Isfahan University of Technology (IUT), and Shiraz University respectively. He got his PhD in computer engineering, pattern recognition and image processing, from University of Bristol, Bristol, England, in 2005. His research interests include AI, Machine Vision, Data Science, and IoT.
He has taught the Data Science courses, including Data Mining, Advanced Data Mining, AI, and Neural Networks since 2008 at both undergraduate and postgraduate levels. He was awarded the best university teacher of the province in 2012. He also has studied Learning Management Systems, ELearning, and E-Learning for workplaces since 2007.
Dr. Monajemi was the data science advisor of MSC (Mobarakeh Steel Complex,the largest in the country). Moreover, he has registered three patents and published more than a hundred research papers in peer-reviewed, indexed journals and international conferences (IEEE, Elsevier, Springer, and so on), and supervised several Data Science, IoT, and AI industrial projects in various scales, including analysis of the effectiveness of research projects in enterprises, and data mining to extract the common patterns among the unsuccessful BSc students. He is experienced in different subdomains of data science from theory to practice, including data mining and pattern recognition.
Ms. Chua Bee Luan
Chua Bee Luan is a Senior Lecturer in Data Analytics and Visualization with the School of Continuing and Lifelong Education (SCALE) at the National University of Singapore (NUS).
Bee Luan is a passionate educator with more than 14 years of teaching experience in an institute of higher learning. She taught modules in Business Analytics, Data Visualization, Website Design, Business Software, Statistical Methods and Calculus. In her capacity as a lecturer, Bee Luan was involved in developing FutureReady certification courses and conducting SkillsFuture for Digital Workplace courses for the adult learners in the banking and aviation industries. In support of the NUS resilience and growth (R&G) initiative, she also provides training for fresh graduates so that they can continue to learn in the uncertain times of COVID-19.
Prior to teaching, Bee Luan began her career in the IT industry in multiple roles, from project management to IT consulting in both MNC and SME companies. She had provided consulting services to her clients to streamline their business processes and had successfully rolled out numerous company-wide Enterprise Resource Planning (ERP) projects for companies mostly in trading and manufacturing industries.
Bee Luan graduated with a Bachelor of Science with Honours, double major in Computational Science and Mathematics from NUS. She also holds a Master in Business Administration in Strategic Management from the Nanyang Technological University and had obtained a Certificate in Teaching & Learning (Higher Education). Teaching has always been her passion and Data Analytics is her new area of interest.
Dr. Guo Lei
Guo Lei is an active educator and researcher in data science, behavioural study and design thinking, with extensive experience in delivering practice-based learning programmes and applied research projects with successful results.
Starting her career in Singapore as a marketing practitioner, Dr Guo worked across manufacturing, entertainment and education industries. She was the Chief Representative in China for a Singapore listed company. She was also responsible for setting up Shanghai Office and promoting executive education programmes for NUS Business School in Greater China market.
With the aspiration of bridging the gap between research and practice, Dr Guo pursued her PhD in the UK, where she worked on large-scale research projects with Cambridge University Service Alliance, BAE Systems and China Mobile.
Dr Guo returned to Singapore and joined NUS as a faculty member in 2011. She has particular experience in tackling complex challenges through applied research and education. She was the Principal Investigator for a series of research projects to inform better public transport policy decisions. She consults local and overseas corporate clients on data analytics, user experience design and service innovation. Dr Guo teaches executive programmes of Data Analytics and Design Thinking at NUS. She has a passion for engaging and inspiring working professionals at all levels by applying the theory to real world business applications.
Dr Guo holds a PhD in Marketing from University of Exeter, an MBA from University of Adelaide and a BA in Literature from Beijing Normal University.
Mr. Koo Ping Shung
Koo Ping Shung is an experienced Data Scientist with more than 13 years of relevant experience. He is also currently a Adjunct Senior Faculty with the Singapore University of Social Sciences (SUSS) and a SAS Trainer as well. To date, he has conducted over 1,600 man-hours of data science training. He is also the mentor to the trainees accepted into the IMDA-SAS BIA Programme for 5 intakes.
Ping Shung was a guest lecturer at NUS Institute of Systems Science and previously held an adjunct position in School of Information Systems, Singapore Management University.
Prior to this, he was the Analytics Practicum Manager of the Master of IT in Business (Analytics) at the Singapore Management University School of Information Systems. He managed the industrial relationships through projects and attachments. He often advised companies on the type of data analytics projects they can work on with their data and is a co-supervisor for many Masters students on their data analytics capstone projects. He was an instructor for the DBS Graduate Associate Programme for 3 years, teaching over 200 Graduate Associates on data analytics and received positive ratings. He has also trained professionals from various companies on data analytics and the use of SAS software.
Ping Shung was a facilitator for the IDA Data Science MOOC programme for 2 cohorts (over 300 professionals) and participated in Singapore's first Data Literacy Bootcamp which was co-organised by the IDA Singapore and The World Bank.
Ping Shung through his career has gathered much experience on statistical modeling, from working in the banks, supervising Masters students and doing education research. His data analytics experience range from a wide variety of business functions and industries, gathered from talking to companies or working on data analytics projects.
His strong passion in data analytics and data science can be seen through his involvement in data analytics interest groups, being a Co-founder of DataScience.Sg and former Working Committee Chairman of SAS User Group Singapore and Data Ambassador for one of the DataKind SG project. He also read widely on the different topics related to data science and artificial intelligence, keeping himself up-to-date with their development.
His research interest lies in how data science can help organisations and businesses to be more efficient and effective.
Ping Shung holds an MBA from University of Adelaide. He obtained his bachelor degree in Economics from National University of Singapore, with a minor in Computational Finance.