Why a spreadsheet? DATA SCIENCE AND ANALYTICS FAQs . • 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. There are more compulsory mathematics and computing modules in the DSA program. Finally, your team needs to deliver these insights as a compelling story. Other specialisations may be added in the future. This course introduces basic Python programming and community best practices such as using Jupyter/Python. 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. 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. 2.5 Days . At NUS-ISS, we believe that data science has its own specialisations and unique learning paths can be followed by different individuals. * Does the higher price of cigarettes deter smoking? 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 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 … But how does one exactly do data science? * How do teenagers and older people differ in the way they use social media? 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. Everything's software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. 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. var searchrbrtype = e.options[searchrbrIndex].value; It looks like you're using Internet Explorer 11 or older. : 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. 5. Then, they have to use critical thinking techniques to justify their insights and reasoning.
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. An accessible, intuitive, and highly efficient base language with speed that exceeds R and Python, makes Julia a formidable language for data science. • 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. 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. 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. Welcome to the Department of Analytics & Operations (DAO)! This book provides you with the know-how to dig those answers out. Updated 17 July 2019 . 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. 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 Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today! 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. The MSc in Data Science and Machine Learning programme is offered jointly by the Department of Mathematics, the Department of Statistics and Applied Probability and the Department of Computer Science with support from the Faculty of Engineering, … (Hons.) A complete list of E-Books packages relevant to School of Computing. The goal of data science is to improve decision making through the analysis of data. You can't change your organization by hiring a few data science superheroes. Subsidised Fees for Singaporeans & Singapore PR (inclusive of GST): $1,000.00. 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; 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. They should pivot their efforts to keep their insights aligned with business value. In order to operate at this level you need to build data science solutions of substance -solutions that solve real problems. 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. Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. It is the next learning curve for those comfortable with Spark and looking to improve their skills. var url2="?SEARCH="; All core and elective modules are worth 4 MCs each, unless stated otherwise. * Who is more likely to use online dating services? 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. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know. 3. Instead, a data science team is exploratory. 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. 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. This is the first textbook on pattern recognition to present the Bayesian viewpoint. with a Major in Statistics [120 MCs] B.Sc. His other books include R for Business Analytics and R for Cloud Computing. 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. Requirements for Completion and Graduation To graduate from our NUS MSc in Accounting programme, you must complete the programme requirements and achieve a Cumulative Average Point (CAP) of at least 3.0 (out […] NUS PhD (Data Science) The NUS PhD (Data Science) programme is jointly hosted by the NUS Graduate School for Integrative Sciences and Engineering (NGS) and the Institute of Data Science (IDS).It prepares students with a distinctive set of interdisciplinary skills for careers in academia or industry. The course then moves on to show how Python can be applied to data m… Certificate in Introduction to Analytics, Cyber Security, AI and Blockchain (1 month)This certificate introduces key concepts in the areas of data and visual analytics using Power BI, statistics, cyber security, blockchain, AI and machine learning. Career options include:• Data Analysts• Business Analyst• Manufacturing and Design Engineers• Researchers working with data. 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. The Programme consists of seven (7) certificates to be conducted within 12 months. 1. 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. It is closely related to the fields of data mining and machine learning, but broader in scope. This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. The NUS-ISS Stackable Certificate Programme in Data Science, leading to the NUS Master of Technology in Enterprise Business Analytics is designed to meet the industry demand for data scientists who can help organisations achieve improved business outcomes through data insights. This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. Certificate in Fundamentals of Data Science (2 months)To provide training in the fundamentals of statistics and programming for data science. * Students may need to read additional modules outside the second major requirements to satisfy the pre-requisites of these modules. 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. [CDATA[ A frequently asked question is how the major in Statistics differs from the major in Data science and Analytics (DSA). 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. 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. 4. Degree Programme in Data Science and Analytics . Trainees are required to equip with a computer Notebook (installed with minimally windows10 OS) when attending lessons. What is this programme? relevant work experience (considered on a case-by-case basis). The book gathers a selection of peer-reviewed contributions presented at the Fifteenth Conference of the International Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015. MTM5004 Maritime Data Analytics This module is a continuation of IE5005 where knowledge learnt about data analytics is applied to tackle maritime-related problems. 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 … Certificate in Data Analytics (2 months)To provide training on specialised skills in the area of data mining and applied statistical methods. Operations managers champion efficiency and the competitive strategy. Trainees must fulfil minimum attendance requirements and pass assessments to qualify for course fee subsidies. The book has three overarching concepts: You should mine your own company for talent. In this book, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. Learn how to build a data science team within your organization rather than hiring from the outside. 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. Course Overview. 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. If you continue with this browser, you may see unexpected results. These stories are the best way to communicate your insights about your customers, challenges, and industry. For students matriculated in AY2017/18 and after: B.Sc. // ]]> as Course NumberLecturer. 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. 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. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. However, trainees who exit the programme This book is a distillation of their experience in a format that is applicable to both practitioners and managers in data science. Discusses several important topics in data science including supervised and unsupervised learning. You should form small, agile-like data teams that focus on delivering valuable insights early and often. NUS Bulletin– Essential information that concerns you as a student. window.open(url + searchrbrtype + url2 + encodeURIComponent(searchInput.value) + url3); The book covers the breadth of activities and methods and tools that Data Scientists use. with a major in Statistics (specialisation in Data Science) [160 MCs] B.Sc. 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 Analytics Practicum Module (Self-soucred Internship) 4. Practicum (3 months)This project module provides opportunities for learners embark on an industry project either in-house or in an attachment to a company or at the Digital Building Innovation Centre (DBIC). 3) Any degree from one of the following Singapore universities: NUS, NTU, SMU, SUTD, SIT, or SUSS. This subject guide covers resources available at the NUS Libraries. *Registration may be closed earlier once seats are filled up. 6. var url3="&searchscope=16" + "&SORT=A"; 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. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon. 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. Such jobs involve extracting, cleaning, managing, analysing and modelling data that is useful to the business. The secondary readership is data scientists, DBAs, analysts, senior management, HR managers, and performance specialists. Classes will be conducted in full-time mode. The Polytechnic reserves the right to shortlist and admit applicants. (Hons.) Mr. Ohri's research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces for cloud computing, investigating climate change and knowledge flows. Students will also undertake an industry-driven capstone project module to work on real-life data. Most organizations still focus on objectives and deliverables. 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. 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). New libraries for data manipulation, visualisation and data modeling have made Python an increasingly exciting alternative to R as a data science language. The Data Analytics and Consulting Centre is a consulting unit closely linked with the DSA programme. Data Science : Create Teams That Ask the Right Questions and Deliver Real Value. Focusing on a sequence of tutorials that deliver a working news intelligence service, you will learn about advanced Spark architectures, how to work with geographic data in Spark, and how to tune Spark algorithms so they scale linearly.Style and approachThis is an advanced guide for those with beginner-level familiarity with the Spark architecture and working with Data Science applications. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Corresponding data sets are available at www.wiley.com/go/9781118876138. You can make real changes to your organization by telling compelling data stories. Analytics and Data Science : Advances in Research and Pedagogy, Beginning Data Science in R : Data Analysis, Visualization, and Modelling for the Data Scientist. 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. 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. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. 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. 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. 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. Features: Covers the core components of Julia as well as packages relevant to the input, manipulation and representation of data. Analytics is the art and science of integrating data, modelling and computation to generate insights and decisions that add value. 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. The Data Science and Analytics (DSA) programme is a multidisciplinary undergraduate degree offered by the Department of Build a strong foundation in Computing and Analytics. The book is for senior undergraduates, beginning graduate students, or practicing data scientists who want to learn how to use Julia for data science. * Why do some purchase iPhones and others Blackberry devices? 2. Data Science : Innovative Developments in Data Analysis and Clustering. Understanding data science and data analytics would help managers to remain competitive and relevant in … Dates. You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. A. Ohri is the founder of Decisionstats.com and currently works as a senior data scientist. Data is ubiquitous in government and in industry sectors including banking, insurance, healthcare, telecommunications, design and manufacturing, and retail. 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. You'll master data science by answering fascinating questions, such as: * Are religious individuals more or less likely to have extramarital affairs? 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. remove. 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. 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. Every chapter is built around real research challenges, so you'll always know why you're doing what you're doing. CP3209 is an independent study modules (ISM) which will be counted as 2 USP Inquiry module in the Sciences and Technologies domain. var searchrbrIndex = document.getElementById("searchrbrtype").selectedIndex; It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. 1 Dec & 7 Dec 2020 (9am – 5pm) 10 Dec 2020 (9am – 11am) Duration. Certificate in Communication and Interpersonal Skills (1 month)This certificate covers the key communication areas which include mindset transformation, emotional intelligence (EQ), communications between generations and building digital confidence in the workplace. Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. Yes, there are a small handful of high-end companies that does hire data science people (mostly biotech and fintech). * Do attractive professors get better teaching evaluations? B.Sc. Teach your team to ask the right questions to gain actionable insights into your business. * What determines housing prices more: lot size or the number of bedrooms? A complete list of E-Books packages relevant to Faculty of Science. 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. The Institute of Data Science (IDS) agglomerates, and further builds on, substantial strengths in data science and analytics in NUS. This process is demonstrated by exploring the construction of a sophisticated global news analysis service that uses Spark to generate continuous geopolitical and current affairs insights.You will learn all about the core Spark APIs and take a comprehensive tour of advanced libraries, including Spark SQL, Spark Streaming, MLlib, and more.You will be introduced to advanced techniques and methods that will help you to construct commercial-grade data products. You can also use the CAP calculator online to simulate different grades and see how they'll affect your CAP. 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.