This book describes, simply and in general terms, the process of analyzing data. 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). Professor Charles Bouveyron INRIA Chair in Data Science Universit¿¿te d¿Azur, Nice, France, An Introduction to Data : Everything You Need to Know About AI, Big Data and Data Science, Introduction to Data Science : A Python Approach to Concepts, Techniques and Applications, Machine Learning Paradigms : Advances in Data Analytics, New Advances in Statistics and Data Science, Python for R Users : a data science approach. REQUIREMENTS FOR COMPLETION AND GRADUATION To graduate from our NUS MSc in Marketing Analytics and Insights programme, you must complete the programme requirements and achieve a Cumulative Average Point (CAP) of at least 3.0 (out of 5.0). with a major in Statistics [160 MCs] B.Sc. 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. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. (Hons.) Operations managers champion efficiency and the competitive strategy. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon. var url="http://linc.nus.edu.sg/search/"; 7. Our stackable modules give learners the ability to choose the exact set of skills they want to master. Harvard Business Review recently called data science "The Sexiest Job of the 21st Century." People who want a career in Data Science, Business analysts, Business executives, people who want to learn the fundamentals of statistical analysis, data wrangling, visualization, model building, prediction and error-quantification in model predictions. * What determines housing prices more: lot size or the number of bedrooms? 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. No previous knowledge of pattern recognition or machine learning concepts is assumed. } Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell's Outliers: It teaches through a powerful narrative packed with unforgettable stories. CP3209 is an independent study modules (ISM) which will be counted as 2 USP Inquiry module in the Sciences and Technologies domain. To stay and complete the […] What is this programme? The National University of Singapore (NUS), the nation’s highest-ranked university, will offer a new degree program in data science and analytics starting from August this year, it … window.open(url + searchrbrtype + url2 + encodeURIComponent(searchInput.value) + url3); Nope. The Polytechnic reserves the right to shortlist and admit applicants. with a major in Statistics (specialisation in Data Science) [160 MCs] B.Sc. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. The Institute of Data Science (IDS) agglomerates, and further builds on, substantial strengths in data science and analytics in NUS. In addition, the target trainees for SGUS programmes will exclude the following: a) Graduated or graduating in Calendar Year (CY) 2019 / 2020 from ITE, Polytechnics, Universities, and other educational institutions. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. *Certificates may not be conducted according to the sequence listed. As an emerging discipline, data science broadly means different things across different areas. var url3="&searchscope=16" + "&SORT=A"; Business Intelligence, Analytics, and Data Science. The Data Analytics and Consulting Centre is a consulting unit closely linked with the DSA programme. New libraries for data manipulation, visualisation and data modeling have made Python an increasingly exciting alternative to R as a data science language. Why a spreadsheet? DATA SCIENCE AND ANALYTICS FAQs . Insight! The goal of data science is to improve decision making through the analysis of data. For courses on Business Intelligence or Decision Support Systems. 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. If you get an A (5.0) for your 4 MC module, and a B (3.5) for your 2 MC module, then your CAP will be: ((4x5)+(2x3.5))/(4+2) = 4.5. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. It is closely related to the fields of data mining and machine learning, but broader in scope. // ]]>   as Course NumberLecturer. Every chapter is built around real research challenges, so you'll always know why you're doing what you're doing. * Students may need to read additional modules outside the second major requirements to satisfy the pre-requisites of these modules. This course introduces basic Python programming and community best practices such as using Jupyter/Python. His other books include R for Business Analytics and R for Cloud Computing. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. Build a strong foundation in Computing and Analytics. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data. Such jobs involve extracting, cleaning, managing, analysing and modelling data that is useful to the business. However, trainees who exit the programme : How to Build Data Science Teams that Deliver Real Business Value shows that the most important thing you can do now is help your team think about data. Please refer here for the FAQ on SGUS programme. Spark has emerged as the big data platform of choice for data scientists due to its speed, scalability, and easy-to-use APIs.This book deep dives into using Spark to deliver production-grade data science solutions. NUS e-OPEN HOUSE 2020 . You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. 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. Data Science and Big Data Computing This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. 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. Trainees are required to equip with a computer Notebook (installed with minimally windows10 OS) when attending lessons. Introduction. Today data science determines the ads we see online, the books and movies that are recommended to us online, which emails are filtered into our spam folders, and even how much we pay for health insurance. 1. Upon completion of study, students are awarded a Master of Science (MSc) in Analytics degree. The MSc in Analytics programme is an intensive one-year full-time or two-year part-timeprogramme by coursework, taught in three semesters. The DSA major is jointly offered by the Statistics department and the Mathematics department in NUS, with support from the School of Computing. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. What Your Will Learn: Create data science teams from existing talent in your organization to cost-efficiently extract maximum business value from your organization's data Understand key data science terms and concepts  Follow practical guidance to create and integrate an effective data science team with key roles and the responsibilities for each team member  Utilize the data science life cycle (DSLC) to model essential processes and practices for delivering value Use sprints and storytelling to help your team stay on track and adapt to new knowledge Who This Book Is For Data science project managers and team leaders. He has advised multiple startups in analytics off-shoring, analytics services, and analytics education, as well as using social media to enhance buzz for analytics products. This book provides you with the know-how to dig those answers out. A complete list of E-Books packages relevant to School of Computing. 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. At NUS-ISS, we believe that data science has its own specialisations and unique learning paths can be followed by different individuals. The book has three overarching concepts: You should mine your own company for talent. The Data Science Handbook : advice and insights from 25 amazing data scientists, Dictionary of Computer and Internet Terms, Computer Technology Encyclopedia : Quick Reference for Students & Professionals, Encyclopedia of Applied and Computational Mathematics, Encyclopedia of Machine Learning and Data Mining, McGraw-Hill Concise Encyclopedia of Science & Technology, Wiley Encyclopedia of Computer Science and Engineering. Yes, there are a small handful of high-end companies that does hire data science people (mostly biotech and fintech). * Does the higher price of cigarettes deter smoking? Exploring the relationship of data science with statistics, a well-established and principled data-analytic discipline, this book provides insights about commonalities in approach, and differences in emphasis.Featuring chapters from established authors in both disciplines, the book also presents a number of applications and accompanying papers. Besides speed and ease of use, there are already over 1,900 packages available and Julia can interface (either directly or through packages) with libraries written in R, Python, Matlab, C, C++ or Fortran. Learn how to build a data science team within your organization rather than hiring from the outside. But for the large part, most companies do not even know there's such a thing as data science. 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. The Programme consists of seven (7) certificates to be conducted within 12 months. A. Ohri is the founder of Decisionstats.com and currently works as a senior data scientist. and Non-Linear Statistical Models, Lessons will be conducted in online synchronous/asynchronous or face-to-face mode, Best viewed using Internet Explorer 10 and above, latest 2 versions of Mozilla Firefox, Safari and Google Chrome, Professional & Adult Continuing Education (PACE) Academy, SGUS Specialist Diploma in Data Science and Analytics, Joint Polytechnic Admissions Exercise (JPAE), Other Scholarships & Sponsorships for Polytechnic Studies, Keeping in Touch with SP after Graduation, COVID-19 Announcement - SP Service Providers, a C6 or better in Additional Mathematics in the O-level examinations; or, a C grade or better in a one-semester polytechnic mathematics module that substantially covers the Additional Mathematics syllabus or. Graduates of the course will be trained in preparing data, summarising and presenting data, performing statistical analysis of univariate and multivariate data, using descriptive models to uncover patterns in data, developing, applying and deploying predictive models and quantifying risks associated with prediction. But don't let the Excel sheets fool you. The formula here is quite simple, and you can find more about the CAP system on the NUS website. Certificate in Data Analytics (2 months)To provide training on specialised skills in the area of data mining and applied statistical methods. Subsidised Fees for Singaporeans & Singapore PR (inclusive of GST): $1,000.00. This is the first textbook on pattern recognition to present the Bayesian viewpoint. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Mastering Spark for Data Science is a practical tutorial that uses core Spark APIs and takes a deep dive into advanced libraries including: Spark SQL, visual streaming, and MLlib. But never fear, the topics are readily applicable and the author laces humor throughout. without a valid reason may be asked to return the course fee subsidy that they have received.• Refund of paid course fees will be pro-rated based on certificates that have not commenced• Trainees who wish to exit from the programme Management coach Doug Rose walks you through the process of creating and managing effective data science teams. This includes graduates from private universities as well as overseas institutions and part-time / post-graduate programmes; and. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know. Learn the basics in our introductory modules on topics such as Mathematics, Statistics, Economics, Accounting, Marketing, Decision Science, Industrial and Systems Engineering, Computer Science and Information Systems. Participants must complete PDC1 before they can progress to PDC2. Trainees who are unable to meet these requirements may be asked to return the course fee subsidies that they have received. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis. IDS is a research institute that will be the focal point for all data science research and translation, education and related activities at NUS, which aims to contribute to Singapore’s Smart Nation initiative by developing deep and strategic capabilities in data science, analytics and optimisation, and cybersecurity. 2.5 Days . Other specialisations may be added in the future. A complete list of E-Books packages relevant to Faculty of Science. The Data Science and Analytics (DSA) programme is a multidisciplinary undergraduate degree offered by the Department of Instead, a data science team is exploratory. If you continue with this browser, you may see unexpected results. remove. It considers data infrastructure and the challenges posed by integrating data from multiple sources, introduces the basics of machine learning, and discusses how to link machine learning expertise with real-world problems. 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. The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to code in Python and Python users to program in R. Short on theory and long on actionable analytics, it provides readers with a detailed comparative introduction and overview of both languages and features concise tutorials with command-by-command translations--complete with sample code--of R to Python and Python to R. Following an introduction to both languages, the author cuts to the chase with step-by-step coverage of the full range of pertinent programming features and functions, including data input, data inspection/data quality, data analysis, and data visualization. Unfortunately, there's been nothing easy about learning data science-until now. You can make real changes to your organization by telling compelling data stories. 8 Elective Modules to Choose From 3. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability--and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases, Data Smart : using data science to transform information into insight. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. Ad-hoc Seminar… Data Science and Big Data Analytics is about harnessing the power of data for new insights. Data Science : Innovative Developments in Data Analysis and Clustering. The secondary readership is data scientists, DBAs, analysts, senior management, HR managers, and performance specialists. • Upon completion of the modules in each certificate (certificate 1-3, 6-7), trainees will be awarded a Certificate of Completion• Upon completion of all modules in certificate 4 and 5, trainees will be awarded with the Post-Diploma Certificates (PDC) respectively. It delivers the most complete range of analytical solutions, using simple to advanced statistical techniques, predictive analytics and data mining technology to help organisations turn data into business insights.

On 21 March 2007, SUSS and SPSS signed an MOU to promote training and continuing education in Business Analytics. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. The objective of the programme is to provide foundational training in the fundamental concepts and methods in statistics and programming as well as in specialized skills in specific domains in data science such as Data Analytics, and Statistical Data Modelling. They should pivot their efforts to keep their insights aligned with business value. 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. A frequently asked question is how the major in Statistics differs from the major in Data science and Analytics (DSA). For students matriculated in AY2017/18 and after: B.Sc. We strive to impact society via education, research and outreach activities, and aspire to be the go-to academic […] To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice. Classes will be conducted in full-time mode. var searchrbrIndex = document.getElementById("searchrbrtype").selectedIndex; * Do attractive professors get better teaching evaluations? Data Science and Big Data Analytics : ACM-WIR 2018. 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 … The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. The course then moves on to show how Python can be applied to data m… It's not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it's indispensable. This book expands on titles like: Machine Learning with Spark and Learning Spark. They use the scientific method to ask interesting questions and run small experiments. 3) Any degree from one of the following Singapore universities: NUS, NTU, SMU, SUTD, SIT, or SUSS. It's comfortable! Understanding data science and data analytics would help managers to remain competitive and relevant in … var searchrbrtype = e.options[searchrbrIndex].value; Master Data Analytics Hands-On by Solving Fascinating Problems You'll Actually Enjoy! Master the techniques and sophisticated analytics used to construct Spark-based solutions that scale to deliver production-grade data science productsAbout This Book* Develop and apply advanced analytical techniques with Spark* Learn how to tell a compelling story with data science using Spark's ecosystem* Explore data at scale and work with cutting edge data science methodsWho This Book Is ForThis book is for those who have beginner-level familiarity with the Spark architecture and data science applications, especially those who are looking for a challenge and want to learn cutting edge techniques. function RBRSearchGo(){ 5. 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. An accessible, intuitive, and highly efficient base language with speed that exceeds R and Python, makes Julia a formidable language for data science. Students will complete 5 essential modules to build a cross-disciplinary foundation for Business Analytics and engage in rigorous study beyond the assumed disciplinary borders. Everything's software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. 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. You'll learn to work with spreadsheets, aggregate data, evaluate statistical significance, and determine statistical trends. Suitable applicants who are shortlisted may have to go through an interview and/or entrance test. Most organizations still focus on objectives and deliverables. 11 Core Subjects 2. Applicant must be a Singapore Citizen or Singapore Permanent Resident aged 21 and above, and is able to commit to the full-time training schedule. But how does one exactly do data science? This course aims to quickly bring up to speed a programmer or business analyst who already knows how to programme in Python to begin using Python as a data science tool. Data Science and Predictive Analytics : Biomedical and Health Applications using R, Data Science for Healthcare : Methodologies and Applications, Data Science Landscape : Towards Research Standards and Protocols, "This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist. Who is more likely to use critical thinking techniques to justify their insights and that... Disciplinary borders Dec 2020 ( 9am – 5pm ) 10 Dec 2020 ( 9am – 11am ).. -Solutions that solve real problems skills they want a new pair of Chuck Taylors handful high-end! Components of Julia as well as packages relevant to School of Computing to a... 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