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. MTM5004 Maritime Data Analytics This module is a continuation of IE5005 where knowledge learnt about data analytics is applied to tackle maritime-related problems. You'll master data science by answering fascinating questions, such as: * Are religious individuals more or less likely to have extramarital affairs? As a Business Analytics student, you will gain a solid foundation in the statistical and analytical methods that make up the backbone of data science. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data. You should form small, agile-like data teams that focus on delivering valuable insights early and often. 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 His other books include R for Business Analytics and R for Cloud Computing. 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. A. Ohri is the founder of Decisionstats.com and currently works as a senior data scientist. We strive to impact society via education, research and outreach activities, and aspire to be the go-to academic […] Classes will be conducted in full-time mode. This book describes, simply and in general terms, the process of analyzing data. 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. 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. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. 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. Feel free to contact us for help on the following: NUS Libraries' services, resources and facilities; Data Science and Big Data Analytics is about harnessing the power of data for new insights. 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. } window.open(url + searchrbrtype + url2 + encodeURIComponent(searchInput.value) + url3); Data Science gets thrown around in the press like it's magic. This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Trainees must fulfil minimum attendance requirements and pass assessments to qualify for course fee subsidies. relevant work experience (considered on a case-by-case basis). The Programme consists of seven (7) certificates to be conducted within 12 months. 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. The Data Analytics and Consulting Centre is a consulting unit closely linked with the DSA programme. You can't change your organization by hiring a few data science superheroes. (Hons.) The book has three overarching concepts: You should mine your own company for talent. PDC 1 Certificate in Fundamentals of Data Science Module 1 - Introduction to Statistics for Data Science Module 2 - Introduction to Programming for Data Science Semester Two PDC 2 Certificate in Data Analytics Module 3 - Data Mining Techniques Module 4 - Applied Statistical Methods. 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. Presents how to optimize Julia code for performance. 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. * What determines housing prices more: lot size or the number of bedrooms? This includes graduates from private universities as well as overseas institutions and part-time / post-graduate programmes; and. It's not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it's indispensable. Learn how to build a data science team within your organization rather than hiring from the outside. B.Sc. 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. 1 Dec & 7 Dec 2020 (9am – 5pm) 10 Dec 2020 (9am – 11am) Duration. A complete list of E-Books packages relevant to Faculty of Science. With the skills and knowledge gained from this programme, participants will be able to take on new challenges in data analytics and statistics-related work which is critical to the fast growing data-driven economy of Singapore and to the fast changing industry-landscape here. Using well known data science methods that will motivate the reader, Data Science with Julia will get readers up to speed on key features of the Julia language and illustrate its facilities for data science and machine learning work. Dates. For students matriculated in AY2017/18 and after: B.Sc. remove. 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. The course then moves on to show how Python can be applied to data m… What is this programme? 6. A complete list of E-Books packages relevant to School of Computing. Welcome to the Department of Analytics & Operations (DAO)! : 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. 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. For courses on Business Intelligence or Decision Support Systems. * Does the higher price of cigarettes deter smoking? 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. The MSc in Analytics programme is an intensive one-year full-time or two-year part-timeprogramme by coursework, taught in three semesters. This is the first textbook on pattern recognition to present the Bayesian viewpoint. Specialisations A specialisation in Financial Analytics will first be introduced in the 2021 intake. var url="http://linc.nus.edu.sg/search/"; "- Professor Charles Bouveyron, INRIA Chair in Data Science, Universit¿¿te d¿Azur, Nice, France Julia, an open-source programming language, was created to be as easy to use as languages such as R and Python while also as fast as C and Fortran. 1. Ad-hoc Seminar… But how does one exactly do data science? Finally, it considers the future impact of data science and offers principles for success in data science projects. This covers the interface between computer science, statistics, and other … 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. The book is for senior undergraduates, beginning graduate students, or practicing data scientists who want to learn how to use Julia for data science. Trainees are required to equip with a computer Notebook (installed with minimally windows10 OS) when attending lessons. 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. var url3="&searchscope=16" + "&SORT=A"; Applicants who do not meet the entry requirements may be considered for admission to the course based on evidence of at least 5 years of relevant working experience or supporting evidence of competency readiness. Master Data Analytics Hands-On by Solving Fascinating Problems You'll Actually Enjoy! Data is ubiquitous in government and in industry sectors including banking, insurance, healthcare, telecommunications, design and manufacturing, and retail. However, trainees who exit the programme Upon successfully acquiring these 2 PDCs, trainees will be conferred with a Specialist Diploma in Data Science (Data Analytics) from SP• Upon completion of all the certificates, trainees will be awarded with a Certificate in SGUS Specialist Diploma in Data Science & Analytics from SP. with a major in Statistics [160 MCs] B.Sc. The advantages of Julia for data science cannot be understated. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. You can also use the CAP calculator online to simulate different grades and see how they'll affect your CAP. var url2="?SEARCH="; Discusses several important topics in data science including supervised and unsupervised learning. NUS e-OPEN HOUSE 2020 . Unfortunately, there's been nothing easy about learning data science-until now. 3. var searchrbrtype = e.options[searchrbrIndex].value; • The programmes allow trainees to exit without penalty if they are successfully placed into a job or have secured a job on their own accord while undergoing training. *Registration may be closed earlier once seats are filled up. Students will read modules in mathematics, statistics and computer science and will be exposed to the interplay of these three areas in the practice of data science. You can make real changes to your organization by telling compelling data stories. Our stackable modules give learners the ability to choose the exact set of skills they want to master. 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. Today's messy glut of data holds answers to questions no one's even thought to ask. DATA SCIENCE AND ANALYTICS FAQs . The soft methods proposed in this volume represent a collection of tools in these fields that can also be useful for data science. This book expands on titles like: Machine Learning with Spark and Learning Spark. But never fear, the topics are readily applicable and the author laces humor throughout. 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 goal of data science is to improve decision making through the analysis of data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. [CDATA[ Class Schedule:Mon-Fri, 9 am to 6 pm (at least 15 hours or more per week), The following modules will be conducted in the evening (6 - 9 pm):- Introduction to Statistics for Data Science- Data Mining Techniques - Applied Statistical Methods- Building Linear Statistical Models- Building Time Series No previous knowledge of pattern recognition or machine learning concepts is assumed.

By Tan Chee Chiang, Research Computing, NUS Information Technology, on 12 May 2020

We launched Data Engineering support services a while ago to support and accelerate data centric research such as in Analytics and AI. NUS Bulletin– Essential information that concerns you as a student. 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. For each problem, you'll walk through defining your question and the answers you'll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. New libraries for data manipulation, visualisation and data modeling have made Python an increasingly exciting alternative to R as a data science language. A frequently asked question is how the major in Statistics differs from the major in Data science and Analytics (DSA). Why a spreadsheet? It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. Certificate in Fundamentals of Data Science (2 months)To provide training in the fundamentals of statistics and programming for data science. A managerial approach to understanding business intelligence systems. Finally, your team needs to deliver these insights as a compelling story. The authors have extensive experience both managing data analysts and conducting their own data analyses, and have carefully observed what produces coherent results and what fails to produce useful insights into data. This book assumes working knowledge of data science, common machine learning methods, and popular data science tools, and assumes you have previously run proof of concept studies and built prototypes.What You Will Learn* Learn the design patterns that integrate Spark into industrialized data science pipelines* See how commercial data scientists design scalable code and reusable code for data science services* Explore cutting edge data science methods so that you can study trends and causality* Discover advanced programming techniques using RDD and the DataFrame and Dataset APIs* Find out how Spark can be used as a universal ingestion engine tool and as a web scraper* Practice the implementation of advanced topics in graph processing, such as community detection and contact chaining* Get to know the best practices when performing Extended Exploratory Data Analysis, commonly used in commercial data science teams* Study advanced Spark concepts, solution design patterns, and integration architectures* Demonstrate powerful data science pipelinesIn DetailData science seeks to transform the world using data, and this is typically achieved through disrupting and changing real processes in real industries.

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