• Digital Ad Fraud Hunting Night: show off your Analytics smarts

    Online fraud is rampant -- from fake Facebook accounts, to fake Instagram followers, to fake Youtube views, to fake ad clicks. It's hard to believe anything is real any more. But how do fraudsters continue to get away with these scams? Join Augustine Fou, a leading ad forensics expert, to see examples of digital ad fraud and roll up your sleeves for an interactive fraud hunting workshop -- where you help find the fraud by looking at analytics. This workshop covers a range of skills that are useful to anyone analyzing web and mobile data. ABOUT THE PRESENTER Dr. Augustine Fou is an independent cybersecurity and ad fraud researcher who helps clients identify and remove fraud impacting their marketing campaigns. He is an industry-recognized thought leader in digital strategy and integrated marketing. Dr. Fou was the former Chief Digital Officer of Omnicom’s Healthcare Consultancy Group, a $100 million agency group serving pharma, medical device, and healthcare clients and served as SVP, digital strategy lead, at McCann Worldgroup/MRM Worldwide. Dr. Fou taught digital strategy at NYU's School of Continuing and Professional Studies and Rutgers University's Center for Management Development. He started his career in New York City with McKinsey & Company. WHO SHOULD ATTEND Anyone interested in web or mobile analytics or want to learn how experts find insights from massive amounts of data. Digital ad forensics provides a great platform to showcase analytics and problem-solving skills. For large brands, millions of dollars of advertising spend are at stake. ABOUT YOUR ORGANIZER Principal Analytics Prep is a leading data analytics bootcamp in New York City. We have provided training and career coaching for both STEM and non-STEM people seeking to start new careers in data science and advanced analytics. Our programs offer a small-group, hands-on, collaborative learning environment, supported by a faculty of hiring managers with 10 years+ of practical industry experience. To learn more, visit our website: https://www.principalanalyticsprep.com

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  • How to Break into Data Science & Analytics

    New York Public Library Science, Industry, and Business Library

    • What we'll do The New York Public Library has invited Kaiser Fung, founder of Principal Analytics Prep, to offer job search guidance to those interested in the field of data science and analytics. Kaiser will give an overview of the field, explain why it is booming, describe career paths, and provide behind-the-scenes insights into the hiring process. Prior to founding Principal Analytics Prep, Kaiser created the Master of Science in Applied Analytics program at Columbia University, and built and managed data teams at Vimeo, SiriusXM Radio and American Express. He is author of the popular dataviz blog, Junk Charts; and two books on statistical thinking in everyday living. See below if you'd like to meet Kaiser before the talk. • What to bring Questions, enthusiasm, open mind • Pre-Talk meeting Kaiser will be available from 4:30-5:30 pm to meet some of you before the talk. If you're interested, please fill out this form, and we will send you details. https://form.jotform.com/91486296695173 • Background matierals Kaiser's blog: https://junkcharts.typepad.com Our Youtube: https://youtube.com/KaiserFungPrincipalAnalyticsPrep Our website: https://www.principalanalyticsprep.com

  • Visual Tools for Explaining Machine Learning Models

    VISUAL TOOLS FOR EXPLAINING MACHINE LEARNING MODELS Presented by Leonardo Auslender Statistical and data science models are considered to be, somewhat pejoratively, black boxes, because their interpretation has not been systematically studied. Molnar’s “Interpretable Machine Learning” (https://christophm.github.io/interpretable-ml-book/) is a notable effort in finding solutions to this problem. Our presentation is humbler. We will present visual tools for model interpretation based on the partial dependency plot (PDP) and its variants, such as marginal PDPs created by the presenter, some of which may be polemical and debatable. The contents are applicable to a wide variety of models. The presentation is based on a binary target model. WHO SHOULD ATTEND You should know the basics of creating statistical or machine learning models. Some familiarity with partial dependency plots is assumed. You can review this article for background: https://christophm.github.io/interpretable-ml-book/pdp.html ABOUT THE PRESENTER Leonardo is a statistician and economist with 30 years of business experience at Cisco, AT&T Bell Labs, Citibank, SAS Institute, etc., He is an expert and invited speaker in the area of Big Data methods, and the intersection of statistical and data mining models. He has written papers and delivered lectures on Variable Selection, Missing Value Imputation, Tree Regression, Support Vector Machines, Market Basket Analysis, Database Marketing, Customer Relationship Management (CRM), GDP and Relative Price Inflation studies, Expectation Formations, Productivity and Technology effects in the economy. ABOUT YOUR ORGANIZER Principal Analytics Prep is a leading data analytics bootcamp in New York City. We have provided training and career coaching for both STEM and non-STEM people seeking to start new careers in data science and advanced analytics. Our programs offer a small-group, hands-on, collaborative learning environment, supported by a faculty of hiring managers with 10 years+ of practical industry experience. To learn more, visit our website: https://www.principalanalyticsprep.com

  • Hands-on Workshop on Blockchain Data & Analytics

    NOTE: When registering, please fill out our pre-Meetup survey: https://form.jotform.com/90706289431157 Our program for 2019 begins with an exciting hands-on workshop on blockchain data and analytics, led by Stavros Zervoudakis, a Chief Data Scientist who has 17 years of industry experience. Stavros will review work that was completed recently on applying machine learning algorithms to solve a classification problem with blockchain addresses and smart contracts. He will conduct a hands-on demonstration of how to query real blockchain data, train the model, and generate output from the model. He will discuss how solving this problem creates value in security-related analytics, user experience optimization and trend analysis. Space is limited, so sign up early. We request that you cancel RSVP to give others your spot if you cannot make it. This event is based on a prior meetup titled "Machine Learning algorithms for the classification of blockchain addresses", and is using data from the Blockchain data warehouse hosted by http://www.Bloxy.info , a lab provided by Bloqchain Science . Bloxy.info is a source of open, reliable, verifiable and objective data about the blockchain. The data is directly extracted from the public blockchain node and processed to be applicable for data mining, information retrieval, graph analysis, machine learning and other well known computer technologies. The data is available as an open interface for any usage and querying by user. Following Along on your Laptop If you like to follow along, bring your laptop. You only need a browser as we will leverage cloud servers. In order to benefit, you should be comfortable with rudimentary coding and data analysis; no knowledge of blockchains is assumed. Speaker Bio Stavros Zervoudakis is an Applied Data Analytics leader, AI Solutions Architect, Chief Data Scientist and a Strategy Implementation executive. With over 17 years hands-on experience, Stavros leads initiatives in Systems Integration, Process Reengineering, Optimization & User Experience, Machine Learning, Deep Learning, and Natural Language Processing & Understanding. As a technologist, Stavros provides corporate executives with clarity and guidance in navigating highly technical AI and data science matters. Utilizing advanced methodologies, tools and best practices, he supports C-Suite decision making with crucial AI and data science insights to successfully implement corporate vision, strategic development and business intelligence solutions. His experience includes oversight, implementation and management of Processes, Programs, Projects, and Data Products for multinational Fortune 100 firms and top startups. Adjunct data science professor at NYU, boot camp instructor on Machine Learning and Python and adviser to startups. Participated in a panel on recent conferences on AI as it applies to the Finance and Shipping industries. Runs a series of workshops at New York University on Blockchain Analytics and AI. Holds a master’s degree in electrical engineering (neural networks) from NJIT. Stavros is your go-to leader to transform your AI vision onto a ROI production-grade product and service.

  • Competing in the World Transformed by the Data Revolution

    New York Public Library Science, Industry, and Business Library

    • What we'll do The New York Public Library has invited Kaiser Fung, founder of Principal Analytics Prep, to speak about the Data Revolution that is transforming our lives. Data about you and us are everywhere, affecting what music you listen to, what news you read, what movies you see, which restaurants you go to, how many steps you take each day, what routes you drive, what schools you attend, what dates you have — you name it, some algorithm is framing your decision-making, whether you know it or not. Kaiser will pry open the black box of data science apps, and present the key themes in the Data Revolution that will affect us for years to come. You will hear about Waze, Google Translate, Captcha, wifi networks, cell phones, route optimization, optical scanning, machine learning models, labeled data, model validation, deep learning, machine bias, fairness of algorithms, conflicts of objectives, cost-benefit analysis, and more. Prior to founding Principal Analytics Prep, Kaiser created the Master of Science in Applied Analytics program at Columbia University, and built and managed data teams at Vimeo, SiriusXM and American Express. He is author of the popular dataviz blog, Junk Charts; and two books on statistical thinking in everyday living. • Who should come Anyone curious about how data, software and algorithms are impacting us; career transitioners who want to connect technical knowledge with the big picture; data scientists who think deeply about the work you do. No technical knowledge is required to understand the talk. • What to bring Questions, enthusiasm, open mind

  • How to Break into Data Science & Analytics

    New York Public Library Science, Industry, and Business Library

    • What we'll do The New York Public Library has invited Kaiser Fung, founder of Principal Analytics Prep, to offer job search guidance to those interested in the field of data science and analytics. Kaiser will give an overview of the field, explain why it is booming, describe career paths, and provide behind-the-scenes insights into the hiring process. Prior to founding Principal Analytics Prep, Kaiser created the Master of Science in Applied Analytics program at Columbia University, and built and managed data teams at Vimeo, SiriusXM Radio and American Express. He is author of the popular dataviz blog, Junk Charts; and two books on statistical thinking in everyday living. Please come meet Kaiser. After the talk, there will be a Meet and Greet at a nearby location starting 8:00 pm. • What to bring Questions, enthusiasm, open mind • Important to know If you'd like to reserve a spot at the Meet & Greet, please contact [masked]

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  • Information Session with Founder, Instructors & Alums

    Principal Analytics Prep invites you to attend an Information Session on our Certified Data Specialist program, an immersive 12-week data science and analytics bootcamp based in New York City, founded by industry thought leader Kaiser Fung. Come mingle with our staff, instructors and alumni. Find out why many alumni have described their experience as "life-changing." To see more reviews, please go to: https://www.principalanalyticsprep.com/reviews-full. EVENT DETAILS WHAT: Information Session on Certified Data Specialist program WHEN: November 27, 2018 (Tuesday), 8:00-9:30 pm WHERE: The Ginger Man 11 East 36th Street, New York, NY 10016 HOW TO ATTEND: Register at Eventbrite https://www.eventbrite.com/e/principal-analytics-prep-information-session-november-2018-tickets-52870255357

  • Competing in a World Transformed by the Data Revolution

    NYU Bobst Library (Courtyard area)

    Join Kaiser Fung, founder of Principal Analytics Prep, a premier provider of top-quality data analytics training programs, on an exploration of what the Data Revolution means to you. We are planning an after-event gathering so you can meet and chat with Kaiser. Details will be announced at the talk. If you do not have a valid NYU ID, please make sure you register at this NYU link to get on the guest list: https://nyu.libcal.com/event/4731370 Competing in a World Transformed by the Data Revolution We are living in the Data Revolution, in which data, algorithms and software influence and even control everything we do. New technologies will change the power structure of society, and make new winners and losers. Those who understand how data are being collected, and used will hold a considerable edge in the world transformed by the Data Revolution. In this talk, Kaiser offers an insider’s perspective on current developments in data science, how they can affect you, and how you should cope with them. Time permitting, topics may include successes, partial successes and faux successes in Big Data; Cambridge Analytica and other data breaches; fake data; artificial intelligence; model accuracy; surveillance methods; ethical dilemmas; bias; fairness; anonymity; business models; attitudes toward data-driven decision-making. We assume some familiarity with mainstream media coverage of such topics, and will probe deeper and broader. No technical training is necessary to understand and participate in this conversation. Here are two items of interest to those who will be attending the talk: The Mission Statement of Principal Analytics Prep https://principalanalyticsprep.com/principal-analytics-prep-mission/ Kaiser's Youtube Video about how Facebook collects your data https://www.youtube.com/watch?v=isHt4PvR5Fo If you do not have a valid NYU ID, please make sure you register at this NYU link: https://nyu.libcal.com/event/4731370

  • Information Session with Instructors and Alumni

    Harvard Business Startup Studio

    NOTE: For this event, please claim your ticket here using Eventbrite: https://www.eventbrite.com/e/information-session-august-2018-tickets-48653206049 We are hosting an information session on our Data Analytics Bootcamp in our office in New York City. The bootcamp has been successful at launching business careers for graduates starting out in the data science and analytics sector - one of the hottest sectors in the economy right now. There are many possible paths to a data analytics job. Here are just a few we have assisted: * Dropping out of medical school, and becoming a data scientist at a large health insurer * Moving from an operations role at a non-profit to a marketing analytics position at an international advertising agency * Switching from analyzing environmental data for a government agency to being a data scientist for an analytics consultancy * Leaving the academic instructor position behind to join a major agricultural firm as their first data scientist * Quitting a lab assistant position, and joining an exciting tech startup as a data scientist One of our first graduates remarked: "Kaiser, the program's founder, teaches a fantastic class on statistical reasoning that until this day causes me to question assumptions behind analyses and models I see. The other instructors were also a joy to learn from, and teach you not just the technical material but also how it is applied in their various industries... I ended up with multiple job offers, just from the connections I formed in this program. I simply can't recommend this program highly enough." Join our Information Session next Monday to meet our instructors and alumni. WHAT: Information Session for Certified Data Specialist starting September 2018 WHEN: August 13, 2018, 6:30-7:30 pm WHERE: Harvard Business School Startup Studio, 33 Irving Place, 3rd Floor, New York, NY 10003 HOW: Secure your spot today by registering here https://www.eventbrite.com/e/information-session-august-2018-tickets-48653206049

  • Data Analytics Networking Night with Andrew Gelman & Shira Mitchell

    Principal Analytics Prep hosts a networking night for people excited about data. We're honored to have two amazing speakers, Professor Andrew Gelman (Columbia) and Dr. Shira Mitchell (Mathematica Policy Research). The talks cover two essential topics in real-world analytics: story-telling with data (Andrew); and causal inference without true experiments (Shira). Come hear these great talks, and meet other data scientists and analytics people. Food and refreshments will be served. -------------------------------------------------------------------------------------------------- Andrew Gelman is Higgins Professor of Statistics, Professor of Political Science and director of the Applied Statistics Center at Columbia University. His books include Bayesian Data Analysis, Teaching Statistics: A Bag of Tricks, Data Analysis Using Regression and Multilevel/ Hierarchical Models, Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do, and A Quantitative Tour of the Social Sciences. Among his numerous publications is an article in Slate critical of the "power pose" research, co-authored with Principal Analytics Prep founder, Kaiser Fung. Shira Mitchell is a statistician at Mathematica Policy Research, where she works on surveys, small area estimation, and causal inference for health and labor policy. Shira received a PhD in biostatistics and a BA in mathematics from Harvard University. Her dissertation was a collaboration with the Human Rights Data Analysis Group, using hierarchical models to estimate the numbers of casualties in Colombia's armed conflict. She did her postdoctoral fellowship at Columbia University, working with Andrew Gelman and Jeffrey Sachs. ------------------------------------------------------------------------------------------------- Andrew's Talk: "Statistics: Learning From Stories" Here is a paradox: In statistics we aim for representative samples and balanced comparisons, but stories are interesting to the extent that they are surprising and atypical. The resolution of the paradox is that stories can be seen as a form of model checking: we learn from a good story when it refutes some idea we have about the world. We demonstrate with several examples of successes and failures of applied statistics. Shira's Talk: "The Millennium Villages Project" The Millennium Villages Project (MVP) was a 10-year project of the Earth Institute at Columbia University, the United Nations Development Programme, and Millennium Promise, implemented in 10 sub-Saharan African sites, aimed at achieving the Millennium Development Goals—eight globally endorsed targets that address the problems of poverty, health, gender equality, and disease. We evaluated MVP's effect on development indicators. The greatest challenges for causal inference include: a nonrandomized design, limited baseline data for candidate control areas, and the assignment of treatment to only ten sites, limiting effective sample sizes. We fit a hierarchical Bayesian model, in Stan, that partially pools across multiple sites and multiple outcomes to ameliorate the problem of "multiple comparisons", and compare to results from a classical analysis.

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