{"id":11666,"date":"2016-03-30T21:40:52","date_gmt":"2016-03-30T19:40:52","guid":{"rendered":"http:\/\/thekharkivtimes.com\/?p=11666"},"modified":"2016-03-31T11:06:25","modified_gmt":"2016-03-31T09:06:25","slug":"kharkivens-will-be-able-to-visit-8-free-it-workshops","status":"publish","type":"post","link":"https:\/\/thekharkivtimes.com\/2016\/03\/30\/kharkivens-will-be-able-to-visit-8-free-it-workshops\/","title":{"rendered":"Kharkivens will be able to visit 8 free IT workshops"},"content":{"rendered":"<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Starting from March 30, every Wednesday, <strong>Nikolay Pavlov<\/strong>, Data Scientist @ <\/span><a href=\"http:\/\/azzurro.io\/#home\" target=\"_blank\"><span style=\"font-weight: 400;\">Azzurro.io<\/span><\/a><span style=\"font-weight: 400;\">, will hold a series of Data Analysis with R workshops, <\/span><a href=\"http:\/\/dou.ua\/calendar\/10408\/\" target=\"_blank\"><span style=\"font-weight: 400;\">reports<\/span><\/a><span style=\"font-weight: 400;\"> the IP-portal DOU.UA.<\/span><\/p>\n<p style=\"text-align: justify;\">Data Analysis with R includes eight 2-hour sessions dedicated to Data Science.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Participants of the workshops will be able to learn about functional programming (<\/span><a href=\"https:\/\/en.wikipedia.org\/wiki\/Scala_(programming_language)\" target=\"_blank\"><span style=\"font-weight: 400;\">Scala<\/span><\/a><span style=\"font-weight: 400;\">) and machine learning (R&amp;Spark) absolutely free.<\/span><\/p>\n<p style=\"text-align: justify;\">Organizer of training &#8211; Kharkiv Computer Science Group and the informal association of R&amp;D companies and individual researchers.<\/p>\n<p style=\"text-align: justify;\"><strong>Curriculum plan:<\/strong><\/p>\n<p style=\"text-align: justify;\"><strong>Introduction to data<\/strong><br \/>\nR programming language<br \/>\nObservations and variables<br \/>\nRelationship between variables<br \/>\nPopulation and sample<br \/>\nDependent and independent variables<br \/>\nExperimental design and sampling methods<\/p>\n<p style=\"text-align: justify;\"><strong>Data exploration, visualization and cleaning<\/strong><br \/>\nData import, cleaning and manipulations<br \/>\nScatter plot<br \/>\nHistogram, mean, variance and standard deviation<br \/>\nBox plots, quartiles, median and outliers<br \/>\nData transformations<br \/>\nCategorical data, contingency tables and bar plot<\/p>\n<p style=\"text-align: justify;\"><strong>Probability<\/strong><br \/>\nOutcome, random process and Law of Large numbers<br \/>\nDisjoint\/joint outcomes, addition rule<br \/>\nIndependence<br \/>\nConditional, marginal and joint probabilities<br \/>\nMultiplication Rule<br \/>\nBayes theorem<br \/>\nRandom variables, Expected Value, Variance<br \/>\nProbability distributions: PDF, CDF<br \/>\nNormal distribution<br \/>\nGeometric distribution<br \/>\nBinomial distribution<\/p>\n<p style=\"text-align: justify;\"><strong>Statistical Inference<\/strong><br \/>\nPoint estimates<br \/>\nConfidence interval<br \/>\nHypothesis testing<br \/>\nType I, type II errors, power<br \/>\nPaired data, different of two means<br \/>\nT-distribution<br \/>\nInference for categorical data<\/p>\n<p style=\"text-align: justify;\"><strong>Regression analysis<\/strong><br \/>\nLinear regression and least squares (LS)<br \/>\nConditions for fitting regression line<br \/>\nResiduals analysis, R^2<br \/>\nInterpretation and inference<br \/>\nMultiple regression<br \/>\nModel selection<br \/>\nLogistic regression<\/p>\n<p style=\"text-align: justify;\"><strong>Predictive Analytics<\/strong><br \/>\nMachine learning and Supervised learning<br \/>\nRegression \/ Classification<br \/>\nError functions<br \/>\nLinear model<br \/>\nGradient descent, SGD, mini-batches<br \/>\nDecision Trees, Random Forest, Neural Networks, SVM<br \/>\nBias-Variance tradeoff, regularization L1\/L2<br \/>\nCross-validation<br \/>\nHyperparameters tuning<\/p>\n<p style=\"text-align: justify;\"><strong>BigData, R and Apache Spark<\/strong><br \/>\nResilient Distributed Datasets (RDD)<br \/>\nMap-Reduce<br \/>\nSparkR, Data Frame operations<br \/>\nMachine Learning in Spark<\/p>\n<p style=\"text-align: justify;\"><strong>Where<\/strong>: Fabrika.space (<a href=\"https:\/\/goo.gl\/maps\/8gNNK72R2To\" target=\"_blank\">Blagoveshchenska Street, 1<\/a>).<br \/>\n<strong>When<\/strong>: every Wednesday from 30 March to 18 May<br \/>\n<strong>Time<\/strong>: 19:00 to 21:00<br \/>\n<strong>Price<\/strong>: free admission<\/p>\n<p><b>Attention!<\/b><span style=\"font-weight: 400;\"> Be <\/span><a href=\"https:\/\/docs.google.com\/forms\/d\/1wx8OqmPrbkL88KKTi5OIz0Kt_8Waqqk7aqoTYvHlNfc\/viewform\" target=\"_blank\"><span style=\"font-weight: 400;\">registered<\/span><\/a><span style=\"font-weight: 400;\"> and carry a laptop with <\/span><a href=\"https:\/\/www.r-project.org\/\" target=\"_blank\"><span style=\"font-weight: 400;\">pre-installed R language<\/span><\/a><span style=\"font-weight: 400;\"> and <\/span><a href=\"https:\/\/www.rstudio.com\/\" target=\"_blank\"><span style=\"font-weight: 400;\">IDE R-Studio<\/span><\/a><span style=\"font-weight: 400;\">.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Starting from March 30, every Wednesday, Nikolay Pavlov, Data Scientist @ Azzurro.io, will hold a series of Data Analysis with R workshops, reports the IP-portal DOU.UA. Data Analysis with R [&hellip;]<\/p>\n","protected":false},"author":4,"featured_media":11615,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_exactmetrics_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","enabled":false},"version":2}},"categories":[17,19,33,6,409,15],"tags":[3687,761],"class_list":["post-11666","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business","category-education","category-events","category-featured","category-it","category-kharkiv","tag-nikolay-pavlov","tag-workshops"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/thekharkivtimes.com\/wp-content\/uploads\/2016\/03\/2KwmFmNXy9g.jpg","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/posts\/11666","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/comments?post=11666"}],"version-history":[{"count":2,"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/posts\/11666\/revisions"}],"predecessor-version":[{"id":11669,"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/posts\/11666\/revisions\/11669"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/media\/11615"}],"wp:attachment":[{"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/media?parent=11666"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/categories?post=11666"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/thekharkivtimes.com\/wp-json\/wp\/v2\/tags?post=11666"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}