Dates 1 Dec & 7 Dec 2020 (9am - 5pm) 10 Dec 2020 (9am - 11am) Duration 2.5 Days Course Overview To gain understanding and working knowledge of Data Analytics and Decision Science. and 4000 Study The last two internship segments take the form of an Honours-level project (DSA4299). – Six additional modules from List A and List B subject to the It also combines data analytics with machine learning. + There must be at least four modules at level 4000 MA3252   Linear and Network Optimisation – MA1102R Calculus Data literacy skills are relevant to everyone – from managers and CXOs to technical professionals. from National University of Singapore. Students will also undertake an industry-driven capstone project module, where they will work with real-life data, providing them with an opportunity to tackle real-life issues and problems in a workplace environment. Currently, his work focusses on enabling risk functions to face the challenges of the digital age, such as machine learning, artificial intelligence, and robotic automation. An ability to function effectively in teams to accomplish a common goal. Julian Lin is a Senior Lecturer in Cybersecurity and Data Analytics with School of Continuing and Lifelong Education (SCALE) at the National University of Singapore (NUS). The Executive Certificate Programme in Data Analytics and Data Visualisation has been designed to support the strategic upskilling needs of employees in data analytics and data visualisation as the Singapore government continues to advocate for wider adoption of analytics by businesses and industries to improve their productivity. * Note: For List B2, i.e., the DSA-recognised modules with hidden pre-requisites, DSA students who wish to read these modules will be provided with academic advice by the Faculty/Department on their study plans where necessary, as such students would have to read ‘additional’ pre-requisite modules. The age of the fourth industrial revolution has seen the explosion of data, with a mind-boggling 2.5 quintillion bytes of data created each day at our current pace. The four-year direct Honours programme in Data Science and Analytics (DSA) is designed to prepare graduates who are ready to acquire, manage and explore data that … 40 16 IDS coordinates and supports data science research initiatives across NUS.The value of the solutions that IDS can provide is through combining the expertise from multiple disciplines to tackle a problem well-roundedly from an all angles. We are taught how to wrangle with big data, develop machine learning models, and then translate them into powerful business insights. Students will also undertake an industry-driven capstone project module, where they will work with real-life data, providing them with an opportunity to tackle real-life issues and problems in a workplace environment. Millions of networked sensors are also embedded in various devices such as mobile phones and tablet computers to sense, create, and communicate data. DSA4211  High-Dimensional Statistical Analysis AY2016/17 To unlock the potential contained within the Big Data requires the application of techniques to explore and convey the key insights. He is a Certified Information Systems Security Professional (CISSP) and has a dozen other IT certifications. School of Business It is the first course in a series of three courses for the Graduate Certificate in Customer Analytics. Big data is now part of every industry sector and function of the global economy. Data scientists are constantly seeking patterns and predicting outcomes from these vast collections of data. (Hons.) Data literacy skills are relevant to everyone – from managers and CXOs to technical professionals. CS3210   Parallel Computing Part IV: Archived Bulletins MA4230   Matrix Computation The NUS degree programme in Data Science and Analytics will equip you with the necessary analytical and communication skills to gain a competitive edge in this rapidly growing field. Yong Loo Lin School of Medicine Strong knowledge of data analytics foundations and fundamentals, including: familiarity with data analytics and programming principles, and; high and broad understanding of the application of analytics in various industrial domains. * 8 MCs of Faculty requirements are fulfilled through the reading of a CS-coded module and a ST/MA-coded module within the DSA curriculum. – DSA2101 Essential Data Analytics Tools: Data Visualisation – DSA3101 Data Science in Practice Department of Analytics & Operations Welcome to the Department of Analytics & Operations (DAO)! To be awarded a B.Sc. This course is part of the Data Science and Graduate Certificate in Customer Analytics Practice Series offered by NUS-ISS. School of Design & Environment 160 MCs ^ (1) As part of the Data Science and Analytics programme, FoS is planning to co-develop modules on data analytics for functional areas such as business, healthcare and public policy making with other Faculties/Schools. Lee Kuan Yew School of Public Policy The NUS Business Analytics programme can help professionals leverage their organisation’s data to gain insights and make informed decisions. MSc with Data Analytics Specialization. The DSA programme is jointly offered by the Department of Mathematics and the Department of Statistics and Applied Probability in the Faculty of Science, with the collaboration of the School of Computing. Data Science & Artificial Intelligence for Senior Executives, MSc in Pharmaceutical Science & Technology, SGUS: Construction / Facilities Management, Data Analytics & Visualisation for IT Managers, Data Analytics and Visualization for Managers, Data Technology and Management for IT Professionals, Future-proof Businesses with Artificial Intelligence, Octave Programming for AI, Machine Learning and Data Analytics, Capstone Project: Developing a Data Analytics Model, Data Analytics Deployment & Performance Monitoring. Accordingly, a Business Analytics degree from NUS will provide you with the skills and expertise needed to build a career in today's fastest-growing and most exciting profession. Students who underwent the NUS Masters of Science in Business Analytics (MSBA) programme will be well-equipped with skills such as machine learning to excel in the data-analytics field across various industries such as finance, retail, information technology, supply chain, and healthcare. Year 1 96 Yong Siew Toh Conservatory of Music WHY CHOOSE NUS MSc IN MARKETING ANALYTICS AND INSIGHTS? from List B1/ List B2 Build a data-driven organisation. ST4248    Statistical Learning II Education at NUS This is not a comprehensive subject guide, but rather a selective list of materials that are most useful for locating information in Data Science and Analytics. Unfortunately, many organizations lack the talent and structure to turn Big Data Analytics into a common practice. Data is the oil, and data visualisation is the engine that facilitates its true value. Special Term Faculty of Dentistry The NUS Master of Science in Business Analytics (NUS MSBA) program is jointly offered and designed by two globally ranked schools, NUS Business School and NUS Computing. The DSA programme will equip its graduates with the skills to contribute to the activities of these industries. Business Analytics is the perfect degree for anyone interested in Statistics, Business, Computing, and of course, using data to create change. (56 MCs) The Bachelor of Science (Business Analytics) degree programme is an inter-disciplinary undergraduate degree programme offered by the School of Computing with participation from the Business School, Faculty of Engineering, Faculty of Science, and Faculty of Arts and Social Sciences. Our suite of data analytics courses cater to you wherever you are starting from and however in-depth you wish to develop your skills for the workplace. – CS3244 Machine Learning The Master of Science in Business Analytics (MSBA) can be taken either as a 1-year (13-month) intensive full-time programme or a 2-year part-time programme. CS3223   Database Systems Implementation Computation Descriptive Analytics with R for undergraduates (2019, 2020) Faculty page at NUS Business School. We are a new interdepartmental multidisciplinary research group focusing on urban data analysis, geographic data science, and 3D city modelling at the National University of Singapore (NUS), the #1 university in Asia and world’s #11 (QS 2021). – CS2040 Data Structures and Algorithms CS4225  Big Data Systems for Data Science or Massive Data Processing Techniques in Data Science Academic Calendar Saw Swee Hock School of Public Health Data Analytics Data is more readily available in the digital economy. Pass University Requirements AY2017/18   36 MCs DSA4299 Applied Project in Data Science The skills to make sense of data will enable you to make better informed decisions. Internship (full time) We are taught how to wrangle with big data, develop machine learning models, and then translate them into powerful business insights. Data science is an emerging field of study that involves statistical and computational principles, methods and systems for extracting and structuring knowledge from data. Study This course is part of the Software Systems series, Data Science series, Graduate Certificate in Big Data Engineering & Web Analytics as well as Graduate Certificate in Engineering Big Data series offered by … Students are required to fulfill the remaining 8 MCs of Faculty requirements from any two of the following subject groups: Chemical Sciences, Life Sciences, Physical Sciences or Multidisciplinary & Interdisciplinary Sciences; but not from the following subject groups: Computing Sciences and Mathematical & Statistical Sciences. Semester 1 The new NUS Institute of Data Science will coordinate these interdisciplinary efforts and create a critical mass of researchers focused on this important area of research. Levels 3000 DSA426x Sense-making Case Analysis: YY and ZZ Choo Wei Jie, Darren (Data Science & Analytics): NUS Science- Zheng Lu Merit Scholarship. In their third and fourth years of study, students will also delve deep into subject matters such as computation and optimisation, computer algorithms, database and data processing, data mining and machine learning, and high-dimensional statistics. 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). Data Science and Analytics at NUS There is a substantial shortfall worldwide in data scientists — individuals with expertise in data analytics. She has been awarded the NUS Annual Teaching Excellence Award and was placed on the Honour Roll for her commitment and performance in teaching. Pass Data science is an emerging field of study that involves statistical and computational principles, methods and systems for extracting and structuring knowledge from data. Part I: General Students in the DSA programme have the option to participate in co-op education which comprises the following study/internship sequence: Singapore is a financial hub, with key industries focusing on biomedical sciences, health care, manufacturing, e-commerce and sustainable energy, among others. However, creating intelligence and gleaning real insights from this data is what continues to elude organisations.” – Competing on Analytics: The New Science of Winning. CS4248   Natural Language Processing Faculty Requirements The Data Analytics and Consulting Centre is a consulting unit closely linked with the DSA programme. The NUS degree programme in Data Science and Analytics (DSA) equips students with analytical and communication skills to extract insights from data … Our Master of Science in Marketing Analytics and Insights programme is designed to groom recent graduates to meet the growing demand for data analysts across the industries to address marketing-related issues – predicting demand and trend, understanding consumer preferences and behavioural patterns, creating new product … ST3240    Multivariate Statistical Analysis The NUS Co-Operative (Co-Op) Education Programme formally integrates academic studies with relevant work experience, where students complete multiple internship stints alternating with regular academic semesters over their candidature at NUS thus forming an integral part of the student’s learning experience. The NUS Co-Operative (Co-Op) Education Programme formally integrates academic studies with relevant work experience, where students complete multiple internship stints alternating with regular academic semesters over their candidature at NUS thus forming an integral part of the student’s learning experience. Business Analytics is the perfect degree for anyone interested in Statistics, Business, Computing, and of course, using data to create change. August intake (AY2021/22) Opens on: 12th Oct 2020, Monday; Closes on: 31th Jan 2021, Sunday; ADMISSION CYCLE This module introduces basic data analytics concepts with a focus on applications that industrial and systems engineers commonly deal with. Analytics is the art and science of integrating data, modelling and computation to generate insights and decisions that add value. ST3247    Simulation + A maximum of two DSA426x series modules can be used to fulfil this requirement – ST2132 Mathematical Statistics Internship (full time) Internship (full time) Graduation Requirements The first three internship segments ride on the Undergraduate Professional Internship Programme (UPIP) of the Faculty of Science. Analytics is the art and science of integrating data, modelling and computation to generate insights and decisions that add value. Note that the BT4101 project selection process takes place one semester ahead of the semester in which the students commence BT4101. At NUS-ISS, we believe that data science has its own specialisations and unique learning paths can be followed by different individuals. Big Data Analytics Technology Students learn to analyse data that cannot fit in the computer’s memory and apply such analysis to web applications. From beginner courses that introduce basic concepts to more technical programming and visualisation techniques, you will acquire data analytics skills and learn the real-life applications of data science. Study About NUS Welcome to the Department of Analytics & Operations (DAO)! Teaching Institutions Students will learn how to communicate the main features of a data set, quantify relationships in data, predict using historical data, select between different data models and appreciate how data insights can influence decisions. Major Requirements Through this course, gain insights on big data applications, analytics, and machine learning, and learn to leverage them for better business decisions. Study B.Sc. Programme Structure and Curriculum Rationale. Mr Chan holds a Bachelor Degree (First-Class Honours) and a Master’s Degree in Engineering from the National University of Singapore (NUS). Part III: Modules The emerging phenomena of Big Data – large pools of data sets that can be captured, communicated, aggregated, stored, and analyzed – has presented companies and organisations with trillions of bytes of information about their customers, suppliers, and operations. Ashok is the author of the book Marketing Analytics, a Practitioner's Guide to Marketing Analytics and Research Methods. Tan Wye Yan (Data Science & Analytics): Kwan Im Thong Cho Temple Science Merit Scholarship .   + There must be at least two modules each from List A and At NUS-ISS, we believe that data science has its own specialisations and unique learning paths can be followed by different individuals. Master in Business Analytics - This course in Business Analytics is jointly offered by the School of Computing and the National University of Singapore Business School. Data Analytics Academic/Training Unit: SCALE Department Module/Course Title Module/Course Code Course Type INSTITUTE OF SYSTEMS SCIENCE NICF - Predictive Analytics - Insights of Trends following restrictions: Data Analytics Consulting Centre Block S16, Level 7 6 Science Drive 2 Faculty of Science National University of Singapore Singapore 117546 dacc@nus.edu.sg Business Hours Monday to Thursday: 8.30 am – 6.00 pm Friday: 8.30 am – 5.30 pm Summary of Requirements   List B2 — DSA-recognised modules (with hidden pre-requisites) * (Hons.) To be awarded a B.Sc.   8 MCs* Administrative Policies / Procedures CS4231   Parallel and Distributed Algorithms Major Requirements This capability based on data analytics is emerging as a critical factor to achieve competitive advantage. B.Acc, National University of Singapore Ruth is an Associate Professor of Finance who teaches Financial Markets, Financial Management and Corporate Finance. CS4224   Distributed Databases Faculty of Law Cumulative Major MCs Students will read modules in Mathematics, Statistics and Computer Science, and be exposed to the interplay between these three key areas in the practice of data science. CS4234   Optimisation Algorithms NUS Bulletin AY2020/21 ST3233    Applied Time Series Analysis Established in 2016, the NUS Smart Nation Research Cluster supports and complements Singapore’s Smart Nation Initiative by developing strategic capabilities in data science, analytics and optimisation, artificial intelligence, as well as cybersecurity. ST3239    Survey Methodology with a primary major in Data Science and Analytics, candidates must satisfy the following: – CS1010/CS1010S/CS1010X Programming Methodology, – DSA2101 Essential Data Analytics Tools: Data Visualisation, – DSA2102 Essential Data Analytics Tools: Numerical, – MA2311 Techniques in Advanced Calculus or MA2104 Multivariable Calculus, – DSA3102 Essential Data Analytics Tools: Convex Optimisation, – DSA4199 Honours Project in Data Science or, – Six additional modules from List A and List B subject to the, + There must be at least two modules each from List A and, + A maximum of two DSA426x series modules can be used to fulfil this requirement, + There must be at least four modules at level 4000, DSA4211  High-Dimensional Statistical Analysis, DSA4212  Optimisation for Large-Scale Data-Driven Inference, DSA426x Sense-making Case Analysis: YY and ZZ, List B1 — DSA-recognised modules (no hidden pre-requisites), ST3232    Design and Analysis of Experiments, ST3240    Multivariate Statistical Analysis, ST4231    Computer Intensive Statistical Methods, List B2 — DSA-recognised modules (with hidden pre-requisites) *, CS3230   Design and Analysis of Algorithms, CS3243 Introduction to Artificial Intelligence, CS4225  Big Data Systems for Data Science or Massive Data Processing Techniques in Data Science, CS4231   Parallel and Distributed Algorithms, CS4243   Computer Vision and Pattern Recognition. MA4270 Data Modelling and Computation Data science is an interdisciplinary field, where processes and systems are used to extract knowledge or insights from data for data-driven decision-making.

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