Toronto Package Comparison

Compare options for the Toronto data science bootcamp. Curriculum is covered in 5 day-long courses.

Note: You can sign up for any of the courses offered below, it is not necessary to register for all courses.
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PREDICTIVE MODELING: AN INTRODUCTION
BUILDING ROBUST ML MODELS
UNSUPERVISED LEARNING AND TEXT ANALYTICS
REGRESSION AND RANKING
DATA ENGINEERING

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8:00 – 8:15 amSetup Your WorkstationIntroductionIntroductionIntroductionIntroduction
8:15 – 9:30 amIntroductionBuilding a Predictive Model in RBuild Your Own Model (Hands-on Lab)Introduction to RegressionBig Data Engineering
9:30 am – 9:45 am Break TimeBreak TimeBreak TimeBreak TimeBreak Time
9:45 – 11:00 amData ExplorationEvaluation of Classification ModelOnline ExperimentationGradient DescentDistributed Systems
11:00 – 11:15 amBreak TimeBreak TimeBreak TimeBreak TimeBreak Time
11:15 – 12:30 amData VisualizationCross ValidationA/B TestingEvaluation of Regression ModelsDeploy Your Own Hadoop Cluster
12:30 – 1:30 pmLunch TimeLunch TimeLunch TimeLunch TimeLunch Time
1:30 – 2:45 pmFeature Engineering with RBuilding Generalized Predictive ModelsUnsupervised Learning and K-means ClusteringRegression (Hands-on Lab)Data Ingestion
2:45 – 3:00 pmBreak TimeBreak TimeBreak TimeBreak TimeBreak Time
3:00 – 4:30 pmGetting Started with Predictive AnalyticsDeploying a Predictive Model as a Web ServiceText Analytics FundamentalsRecommender Systems FundamentalsStream Processing
4:30 –4:45 pm Break TimeBreak TimeBreak TimeBreak TimeBreak Time
4:45 – 6:00 pmIntroduction to Classification Models Introduction to Ensemble MethodsText Analytics (Hands-on Lab)Create Your Own RecommemderIOT Hackathon