NUS AMP – AI/ML, Data Science and Business Analytics
According to Glassdoor, data science is one of the top three jobs in America in 2020. It boasts a high job satisfaction rating, along with a median salary of $107,801. With more than 2.5 quintillion bytes of new data generated every day, it’s no surprise that there’s a growing demand for professionals who can process, interpret, and leverage information in just about every industry. According to an HBS article, data science is the process of deriving meaningful insights from raw data. Data science aims to make sense of the copious amounts of data, also referred to as big data, that today’s organizations maintain. Practitioners of data science—whether they’re data scientists or other professionals skilled in data, such as analysts, engineers, or statisticians—use scientific methods, algorithms, and systems to draw actionable conclusions with big data. These individuals are concerned with the deeper meaning hidden within data and what it means for the future, according to the article. The emphasis in this course is on the core concepts and their real-world applications. This course helps gain the foundational data science skills to prepare for a career or advanced learning and covers the broad areas of data science with help of examples in a comprehensive manner.
Course Learning Objectives:
- Learn the basic understanding of data science with an outlook of data as well as different buzzwords of data science.
- Develop an outlook for Analytics, AI/ML, and its tools and techniques by understanding their deeper aspects.
- Gain an understanding of data and analytics from Orange’s perspectives and learn different aspects with examples.
- Earn a perspective of visualizing and reporting data by understanding its importance, methods, and use cases.
- Acquire an understanding of the fundamentals of decision analysis and forecasting.
Faculty
Dr Guo Lei
Dr Guo 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. Dr Guo has a passion for engaging and inspiring working professionals at all levels by applying the theory to real world business problems.
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.
Syllabus
- Analytics and AI/ML tools and techniques
- Data Visualization and Reporting
- Decision Analysis and Forecasting
Learning Objectives:
- Learn the basic understanding of data science with an outlook of data as well as different buzzwords of data science.
- Develop an outlook for Analytics, AI/ML, and its tools and techniques by understanding their deeper aspects.
- Gain an understanding of data and analytics from Orange’s perspectives and learn different aspects with examples.
Module Components:
Video Lectures:
- Introduction to Business Analytics
- Let’s talk about Data Science
- Getting Started with Orange: Welcome to Orange
- Data Workflows
- Widgets and Channels
- Loading Your Data
- Making Predictions with Orange
- Model Evaluation and Scoring with Orange
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Workshop 1 for Sep 17_AMP
Readings:
- Data Science vs Business Intelligence: same but completely different
- When Business Analytics meets Machine Learning
- Data Pre-processing: Concepts
- Machine Learning | An Introduction
- Machine Learning Classifiers
- AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the Difference?
Quiz:
- Analytics and AI/ML tools and techniques
Learning Objectives:
- Earn a perspective of visualizing and reporting data by understanding its importance, methods, and use cases.
Module Components:
Video Lectures:
- The Joy of Stats
- Why Data Visualization Matters?
- Tableau Basics for Beginners
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Workshop 2 for Sep 23_AMP
Readings:
- Data Visualization 101
- A Reader on Data Visualization, Case Studies
- A Day in the Life of Americans
Quiz:
- Data Visualization and Reporting
Learning Objectives:
- Acquire an understanding of the fundamentals of decision analysis and forecasting.
Module Components:
Video Lectures:
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Workshop 3 for Oct 01_AMP
Quiz:
- Decision Analysis and Forecasting