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 … They use the scientific method to ask interesting questions and run small experiments. It has never been easier for organizations to gather, store, and process data. 2. Operations managers champion efficiency and the competitive strategy. This proceedings volume is a collection of peer reviewed papers presented at the 8th International Conference on Soft Methods in Probability and Statistics (SMPS 2016) held in Rome (Italy). * Does the presence of children influence a family's spending on alcohol? Course Overview. 11 Core Subjects 2. 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. * How do teenagers and older people differ in the way they use social media? Trainees must fulfil minimum attendance requirements and pass assessments to qualify for course fee subsidies. What is this programme? Insight! Certificate in Essential and Emerging Skills for Employability (1 month)This certificate covers fundamentals in various essential areas within an organisation, which includes human resource, finance, design thinking, robotic process automation and digital marketing. with a Major in Statistics [120 MCs] B.Sc. * What determines housing prices more: lot size or the number of bedrooms? They will read CP3209 Undergraduate Research Project in Computing (8 MCs) in place of the Business Analytics Capstone Project module (BT4103) in the Core modules requirement. var e = document.getElementById("searchrbrtype"); A concise introduction to the emerging field of data science, explaining its evolution, relation to machine learning, current uses, data infrastructure issues, and ethical challenges. Such jobs involve extracting, cleaning, managing, analysing and modelling data that is useful to the business. Degree Programme in Data Science and Analytics . This book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science. An accessible, intuitive, and highly efficient base language with speed that exceeds R and Python, makes Julia a formidable language for data science. * Features a quick-learning format with concise tutorials and actionable analytics * Provides command-by-command translations of R to Python and vice versa * Incorporates Python and R code throughout to make it easier for readers to compare and contrast features in both languages * Offers numerous comparative examples and applications in both programming languages * Designed for use for practitioners and students that know one language and want to learn the other * Supplies slides useful for teaching and learning either software on a companion website Python for R Users: A Data Science Approach is a valuable working resource for computer scientists and data scientists that know R and would like to learn Python or are familiar with Python and want to learn R. It also functions as textbook for students of computer science and statistics. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know. Data Science and Big Data Analytics : ACM-WIR 2018. Updated 17 July 2019 . Applicants applying to be enrolled in this programme must satisfy at least one of the following entry requirements: 1) An engineering diploma from a polytechnic in Singapore, 2) Any diploma from a polytechnic in Singapore and. (Hons.) Data is ubiquitous in government and in industry sectors including banking, insurance, healthcare, telecommunications, design and manufacturing, and retail. Certificate in Statistical Data Modelling (2 months)To provide training on specialised skills in the area of modelling of data of varied statistical structures for the purpose of performing predictive analytics. This book expands on titles like: Machine Learning with Spark and Learning Spark. Reviews data visualization using the Gadfly package, which was designed to emulate the very popular ggplot2 package in R. Readers will learn how to make many common plots and how to visualize model results. b) Graduated from the educational institutions mentioned in (a) and completed or completing their National Service (NS) in CY 2019 / 2020 and are entering the labour force. The Data Science and Analytics (DSA) programme is a multidisciplinary undergraduate degree offered by the Department of var url="http://linc.nus.edu.sg/search/"; Suitable applicants who are shortlisted may have to go through an interview and/or entrance test. The book is dedicated to Data science which aims at developing automated methods to analyze massive amounts of data and to extract knowledge from them. B.Sc. This volume in the MIT Press Essential Knowledge series offers a concise introduction to the emerging field of data science, explaining its evolution, current uses, data infrastructure issues, and ethical challenges. Each chapter will cover a different technique in a spreadsheet so you can follow along: Mathematical optimization, including non-linear programming and genetic algorithms Clustering via k-means, spherical k-means, and graph modularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, and bag-of-words models Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through each technique. You will learn how to find the right people inside your organization and equip them with the right mindset. Every chapter is built around real research challenges, so you'll always know why you're doing what you're doing. 1. NUS e-OPEN HOUSE 2020 . The goal of data science is to improve decision making through the analysis of data. The big data evolution provides an opportunity to manage significantly large amounts of information and act on them with analytics for improved diagnostics and prognostics. Feel free to contact us for help on the following: NUS Libraries' services, resources and facilities; Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory. 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, as well as in specialised skills in the areas of data mining, applied statistical methods, statistical modelling and prediction. The Institute of Data Science (IDS) agglomerates, and further builds on, substantial strengths in data science and analytics in NUS. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. They should pivot their efforts to keep their insights aligned with business value. You'll master data science by answering fascinating questions, such as: * Are religious individuals more or less likely to have extramarital affairs? MTM5004 Maritime Data Analytics This module is a continuation of IE5005 where knowledge learnt about data analytics is applied to tackle maritime-related problems. Career options include:• Data Analysts• Business Analyst• Manufacturing and Design Engineers• Researchers working with data. The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. (Hons.) The programme consists of a total of 30 Academic Units (AU), with 24 AU stemming from core courses and 6 AU from elective courses: 1. Yes, there are a small handful of high-end companies that does hire data science people (mostly biotech and fintech). This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. Statistical modeling, machine learning, and data mining--including supervised and unsupervised data mining methods--are treated in detail, as are time series forecasting, text mining, and natural language processing. Dates. * Who is more likely to use online dating services? In this book, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. Use social media and Consulting Centre is a distillation of their experience in format! Recognition to present the Bayesian viewpoint how many of the field, fundamental. 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