It can be difficult to find good, unbiased online resources and websites dedicated to data professionals. The Bachelor of Science in Business Analytics provides students with the ability to apply appropriate business analytics techniques so that business data can be transformed into value-added information. The Data Science Forum holds meetings that focus on hot data science topics, machine learning, and business analytics. The reason why data scientists often have masters is because its not that simple a task, and its somewhat of an emerging field. One of the following modules: One of the following modules: D. School of Continuing and Lifelong Education, H. NUS Graduate School for Integrative Sciences and Engineering, 1. However, where a module in List I or Lit II requires ST3131 as pre-requisite, the pre-requisite may not be fulfilled by EC3303. tl:dr of data science: u taking massive amounts of data and one way or another, using proven calculations etc etc generate useful patterns, info that can lead to better decision making etc. Data science is an inter-disciplinary field about processes and systems to extract knowledge or insights from data in various forms and makes use of techniques and theories drawn from the broad areas of computer science, mathematics and statistics. There's an overload of data and analytics helps to make sense of all this. Build a data-driven organisation. They are allowed to read and pass an additional module from List I or List II in lieu of ST3131. Topics include map-reduce as a tool for creating parallel algorithms that operate on very large amount of data, similarity search, data-streaming processing, search engine technology, and clustering of very large high-dimensional datasets. Engineering Science Environmental Engineering Electrical Engineering Industrial & Systems Engineering Materials Science & Engineering Mechanical Engineering Computer Engineering. Even if they have heard of it, they don't know what data science is or how to leverage it to increase its own company's value. Data science is an interdisciplinary field, where processes and systems are used to extract knowledge or insights from data for data-driven decision-making. It aims to develop professionals with business analytics skills that will meet the growing demands of companies looking to improve their operations through data analytics. At its current stage, there isn't exactly a data science technique you can just use right out of the box. DSA4211      High-Dimensional Statistical Analysis Data Science and Analytics Programme. It's actually not a MUST to have a masters, but it definitely helps because traditional courses don't cover data science. MA1513 Linear Algebra with Differential Equations (2 MCs) † Module 4: The Hadoop Ecosystem for Big Data. Investigators: Wynne Hsu (PI), Dept. One additional module from List I or List II † This is me speaking as someone who have been in the industry since the late 1990s. DSA4212      Optimisation for Large-Scale Data-Driven Inference* 2.1 Introduction. MA3252 Linear and Network Optimisation Module 3: Architectural Viewpoints in Big Data. The scope of this analytics-based capability is constantly expanded by the development of new technologies making the generation, collection, and analysis of data much easier. It is the first course in a series of three courses for the Graduate Certificate in Customer Analytics. If you want to do full-fledged data science (modelling, machine learning etc.) * Students who passed EC3303 Econometrics I need not read ST3131. DSA3102 Essential Data Analytics Tools: Convex Optimisation* 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. MA3236 Nonlinear Programming* Saw Swee Hock School of Public Health Data science as it is right now in Singapore (not worldwide), is not an industry of its own. Pass 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. (Hons.) One of the following modules: As many here have said, practically a Masters level certification is a minimum requirement for any data science project. Not many companies in Singapore collect this kind of data, most of them are MNCs. Minors: Financial Mathematics, Mathematics, Statistics. CS2040 Data Structures and Algorithms with a second major in Data Analytics, candidates must satisfy the following: MSc with Data Analytics Specialization. Anyone else also being offered this course? Academic Information / Policies Major: Data Science and Analytics Applicable to cohorts: AY 2017/2018 and after 20 MCs Pass 8 MCs – CS1010/—S/—X Programming Methodology 96 MCs – DSA1101 Introduction to Data Science 36 MCs – MA1101R Linear Algebra I 160 MCs – MA1102R Calculus Pass List A — DSA modules Note: The DSA426X series modules Dr. Julian Lin . Data & Analytics in Life Sciences Forum @IQPC March 9-11, 2015 Complete a 10-minute Gartner Peer Insights Survey for Data Science and Machine Learning for a $25 USD Visa Prepaid Gift Card* *Once your review is published on Gartner Peer Insights. The specific objectives of the SGUS Specialist Diploma in Data Science and Analytics are to provide training in the fundamentals of statistics and programming for data science, ... NUS, NTU, SMU, SUTD, SIT, or SUSS. NUS Bulletin AY2020/21 Faculty of Law 1. Initially I was excited about this course as I thought the data science field is flourishing and there is nascent demand for data scientists in the industry. I did projects in expert systems and neural networks back then as an engineer in an A-STAR institute, worked in two local startups, then took a data science masters. Module 6: NoSQL Databases for Big Data. The Data Science Forum holds meetings that focus on hot data science topics, machine learning, and business analytics. DSA4211      High-Dimensional Statistical Analysis, DSA4212      Optimisation for Large-Scale Data-Driven Inference*, ST3240          Multivariate Statistical Analysis. Is there a variety of analytics-related mods in NUS to explore? You need to understand the data, figure out its characteristics and then figure out how best to modify the data, figure out if you need more or different data, figure out how to modify a data science technique for the problem at hand. Bulletin Updates Analytics is the art and science of integrating data, modelling and computation to generate insights and decisions that add value. by Dr Lee Yen Teik Through a mix of discussions and experiential exercises, this topic applies scientific methods to translate raw data … School of Design & Environment Topics include map-reduce as a tool for creating parallel algorithms that operate on very large amount of data, similarity search, data-streaming processing, search engine technology, and clustering of very large high-dimensional datasets. Centre for English Language and Communication Collecting data is a skill. Applying them on a statistical level is an even harder skill. 35. The Heidelberg Laureate Forum is the result of a joint initiative of the Heidelberg Institute for Theoretical Studies and the Klaus Tschira Stiftung, and is a one-week event combining scientific, social and outreach activities. We’ve asked our own data analysts to tell us about some of their favorite sites and created this list of must-follow forums, data analytics blogs, and resource centers. Section 1: Introduction to Course and Python Fundamentals – In this introduction, an overview of key Python concepts is covered as well as the motivating factors for building industry professionals to learn to code. Faculty of Arts & Social Sciences This will in turn help organisations to improve their performance, understand their customers better and identify areas for improvement in the organisations' processes. List I^ They are allowed to read and pass an additional module from List I or List II in lieu of ST3131. Updated 17 July 2019 . Initially I was excited about this course as I thought the data science field is flourishing and there is nascent demand for data scientists in the industry. This is something that I don't think a bachelor's degree alone would sufficiently prepare a student to do. But for the large part, most companies do not even know there's such a thing as data science. † Applicable only to students who use MA1513 Linear Algebra with Differential Equations (2 MCs) to fulfil the second major requirements. The GARTNER PEER INSIGHTS Logo is a trademark and service mark of Gartner, Inc. and/or its affiliates and is used herein with permission. ST3248         Statistical Learning I (Hons.) I work as an ML/statistical data analyst overseas. Data Science and Analytics: Main. (Hons.) Levels MA1508E Linear Algebra for Engineering DSA2102 Essential Data Analytics Tools: Numerical Computation † Applicable only to students who use MA1513 Linear Algebra with Differential Equations (2 MCs) to fulfil the second major requirements. This course is part of the Data Science and Graduate Certificate in Customer Analytics Practice Series offered by NUS-ISS. Welcome to /r/singapore the reddit home of the country Singapore. The number of course places taken up NUS for AY 2020/2021 is shown in Table 3. In the past, traditional descriptive analytics could only equip organizations with fundamental operational observations, signaling deviations and raising alarms when necessary. It introduces the various tools and techniques used by data science teams today. Education at NUS One of the following modules: Being able to draw out meaningful insight is even more challenging. 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