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X-WR-CALNAME:MedTech Boston
X-ORIGINAL-URL:https://medtechboston.medstro.com
X-WR-CALDESC:Events for MedTech Boston
BEGIN:VEVENT
DTSTART;TZID=UTC-4:20180122T190000
DTEND;TZID=UTC-4:20180122T210000
DTSTAMP:20201020T145510
CREATED:20180115T045444Z
LAST-MODIFIED:20180115T045444Z
UID:20011-1516647600-1516654800@medtechboston.medstro.com
SUMMARY:Boston Data Science Training | IT Training | Disruptive Technologies
DESCRIPTION:Next class starting:\n\nJanuary 22 – February 22\, 2018\n\nWeekly Schedule\n\nEvery week\,\nMonday and Thursday\n7:00 PM -9:00 PM (US Pacific Standard Time) each day\n\nPlease confirm your local time \nTraining material\, lab exercises and recordings will be shared after each session with students. \nCourse Overview\nThis Data Science course will help you gain expertise in Machine Learning Algorithms like K-Means Clustering\, Decision Trees\, Random Forest\, Naive Bayes using R. You’ll learn the concepts of Statistics\, Time Series\, Text Mining and an introduction to Deep Learning. You’ll solve real life case studies on Media\, Healthcare\, Social Media\, Aviation\, HR. \nAbout this course\nIn this data science course\, you will learn key concepts in data acquisition\, preparation\, exploration\, and visualization taught alongside practical application oriented examples such as how to build a cloud data science solution using Machine Learning platform\, or with R\, and Python on Azure stack. \nWhat you will learn in this course?\n\nExplore the data science process\nProbability and statistics in data science\nData exploration and visualization\nData ingestion\, cleansing\, and transformation\nIntroduction to machine learning\nThe hands-on elements of this course leverage a combination of R\, Python\, and Machine Learning\n\nWhat are the pre-requisites?\n\nPython programming knowledge\nBasic machine learning knowledge (especially supervised learning)\nBasic statistics knowledge (mean\, variance\, standard deviation\, etc.)\nLinear algebra (vectors\, matrices\, etc.)\nCalculus (differentiation\, integration\, partial derivatives\, etc.)\n\nCourse Outline\n\nData Preprocessing\nLinear And Logistic Regression Models.\nDecision Trees and Random Forest.\nNaive Bayes and Support Vector Machine.\nK-means and Hierarchical Clustering.\nNatural Language Processing.\nArtificial Neural Networks.\nConvolutional Neural Network.\n\n \n\n
URL:https://medtechboston.medstro.com/event/boston-data-science-training-it-training-disruptive-technologies/
LOCATION:Instructor Led Online | Video Conference
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