Sep 10thBig Data for Data ScienceMIE 1628Lecture 1Introduction into Big Data
Lecture outline•Introductions, instructor’s experience•Data science objectives•Emergence of big data industry •What is Big Data & Hadoop: –History of Hadoop•Course outline, marking scheme•Final project discussion •Technology for this course •Important Hadoop concepts
SUMMARYComputer Scientist with 18 years of experience in applying mathematical & statistical techniques to complex data-intensive problems in finance and academiaLead Data Scientist, TD Bank2018 – PresentNLP, Semantic Topic Modelling, Optical Character Recognition, Sentiment Modelling, Wealth ManagementPrincipal Data Scientist, Manager, Capital One UK/Canada2015 – 2018Fraud Modelling (first AI based application fraud model in the UK and first self-learning, self-deploying transactional fraud model in the world)TEACHING : University of Nottingham2014-15Industry Teaching Sessions2015-20McMaster, AI and Machine Learning2020University of Toronto2020EDUCATIONUniversity of NottinghamDoctor of Philosophy in Computer Science2012-2015Istanbul Technical University2010 –2012MSc Robotics / Computer EngineeringIsfahan University 1998 – 2003BSc Computer EngineeringInstructor’s background Shahriar Asta
Survey for enrolled participantsYou will receive an email with a request to answer a few questions.Please fill out the survey by next class, it will help me adjust curriculum to fit your background and programming skills: –What department are you affiliated with? (MEIE, others) –Have you taken any data science courses (machine learning, statistics etc)? –What programing languages and environments do you have experience with: •Java, C++, Python, R, Matlab, SAS, SQL, other –What big data solutions do you have experience with? •None, Hive, Impala, Spark, Kafka, HDFS, Azure, Ambari, Zookeper–What topics would you like to cover and focus on in the class?
Business background and motivation for this course
My experience with enterprise data science and big dataCanadian retailUS retailWholesaleCorporate•Personal and commercial banking•Wealth•Insurance •Canada: .~15M customersRevenue: $21B (2017)•Personal & business banking•Wealth management :•U.S. ~8 million retail customersRevenue: $10.2B (2017)•Capital markets•Corporate and investment bankingRevenue: $3.2B (2017)Revenue: $1.6B (2017)The Banking BusinessKey Product Groups: Personal banking: •Personal deposits •Consumer Lending •Credit cards and Merchant solutions•Auto finance Business Banking•Commercial banking •Small Business Banking Wealth: •Direct Investing•Asset Management •AdviceInsuranceIncludes trade data, planner/advisor information, securities, mutual funds, market data …
Long term technology trends transforming enterprisesBig dataBlockchainData science AIMobile and DigitalBanks becoming technology companiesProcess AutomationBiometrics and adaptive securityCloudIofT