This course is the sequel to Data Analytics Begins with Me. This will dive into the use of powerful open source analytics tools such as R and Python, required and best practices in the set-up of a data analytics infrastructure, hiring and building a data science team, including the set-up of a Centre of Excellence for Analytics and data analytics project scoping. The course includes an extensive hands-on on 12 most frequently-used algorithms by a data scientist.
This course introduces the use of powerful open source analytics tools required and best practices in the set-up of a data analytics team and Centre of Excellence for Analytics.
At the end of the programme, participants will be able to:
- Understand what is Big Data, Data Science/Analytics, Machine Learning and Artificial Intelligence
- Describe and manage the Data Analytics process and workflow
- Understand the various tools used for analysis and data platforms required to support the analytics process.
- Identify the competencies required to build a data science team
- Stages in Analytics Projects
- Open Source and Innovation
- Building the Data Science Team
- COE for Analytics
- Privacy, Ethics and Biases
- Project Scoping
- Hands-on session
- Analytics with Orange Workshop (Credit Card Fraud Detection)
- Sentiment Analysis of Survey Data
- The Analytics Dozen (reading materials)
In addition, the participant should have an IT/software project development, architecture or management experience. An understanding of common IT software, databases, programming tools and environments is preferred.
Who Should Attend
Project Managers, IT Managers
Mode of Training
Online Workshop using Zoom
Dr. Amirhassan Monajemi
Dr. 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, E-Learning, 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 sub-domains of data science from theory to practice, including data mining and pattern recognition.
Ms Chua Bee Luan
Ms. 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
Dr 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
Mr 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.