data science and analytics nus modules

The Data Analytics and Consulting Centre is a consulting unit closely linked with the DSA 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. New libraries for data manipulation, visualisation and data modeling have made Python an increasingly exciting alternative to R as a data science language. This covers the interface between computer science, statistics, and other … Data science as it is right now in Singapore (not worldwide), is not an industry of its own. What is this programme? But how does one exactly do data science? To stay and complete the […] 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. It is closely related to the fields of data mining and machine learning, but broader in scope. In this book, you'll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. 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. 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. Participants must complete PDC1 before they can progress to PDC2. var url3="&searchscope=16" + "&SORT=A"; 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. 8 Elective Modules to Choose From 3. Presents how to optimize Julia code for performance. relevant work experience (considered on a case-by-case basis). For courses on Business Intelligence or Decision Support Systems. 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. (Hons.) This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. • 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. var url2="?SEARCH="; 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. 6. 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. B.Sc. } * Do attractive professors get better teaching evaluations? Discusses several important topics in data science including supervised and unsupervised learning. (Hons.) 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. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets. 4. This book offers a brief history of the field, introduces fundamental data concepts, and describes the stages in a data science project. 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. Throughout, the focus is squarely on what matters most: transforming data into insights that are clear, accurate, and can be acted upon. 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. 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. var searchrbrIndex = document.getElementById("searchrbrtype").selectedIndex; "This book is a great way to both start learning data science through the promising Julia language and to become an efficient data scientist." * Why do some purchase iPhones and others Blackberry devices? You can also use the CAP calculator online to simulate different grades and see how they'll affect your CAP. Introduction. // ]]>   as Course NumberLecturer. It shows how Data science employs various programming techniques and methods of data wrangling, data visualization, machine learning, probability and statistics. 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. 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. The secondary readership is data scientists, DBAs, analysts, senior management, HR managers, and performance specialists. You'll learn to work with spreadsheets, aggregate data, evaluate statistical significance, and determine statistical trends. : 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. Feel free to contact us for help on the following: NUS Libraries' services, resources and facilities; 1 Dec & 7 Dec 2020 (9am – 5pm) 10 Dec 2020 (9am – 11am) Duration. (Hons.) 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. remove. 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. Please refer here for the FAQ on SGUS programme. 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. Subsidised Fees for Singaporeans & Singapore PR (inclusive of GST): $1,000.00. A complete list of E-Books packages relevant to School of Business. 2.5 Days . 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. Unfortunately, there's been nothing easy about learning data science-until now. * Who is more likely to use online dating services? Will be an ideal source for people who already know R and want to learn how to use Julia (though no previous knowledge of R or any other programming language is required). And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. They use the scientific method to ask interesting questions and run small experiments. • 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. Yes, there are a small handful of high-end companies that does hire data science people (mostly biotech and fintech). The book also reviews ethical and legal issues, developments in data regulation, and computational approaches to preserving privacy. But don't let the Excel sheets fool you. with a Major in Statistics [120 MCs] B.Sc. 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. //

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