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Introduction to Data Science 6
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What is Big Data?Lecture1.1
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Big Data ApplicationsLecture1.2
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What is Data Science?Lecture1.3
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Data Science ComponentsLecture1.4
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Data Science ProcessLecture1.5
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Tools and TechnologyLecture1.6
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Python Basics 5
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IntroductionLecture2.1
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Variables and OperatorsLecture2.2
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Data StructuresLecture2.3
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Control Flow StatementsLecture2.4
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OOPs ConceptsLecture2.5
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Python Libraries 4
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NumpyLecture3.1
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PandasLecture3.2
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MatplotlibLecture3.3
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SeabornLecture3.4
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Statistics 4
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BasicsLecture4.1
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Descriptive StatisticsLecture4.2
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Inferential StatisticsLecture4.3
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Hypothesis TestingLecture4.4
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Machine Learning Concepts 11
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Introduction to MLLecture5.1
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Types of MLLecture5.2
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Linear RegressionLecture5.3
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Logistic RegressionLecture5.4
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Decision TreesLecture5.5
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Random ForestLecture5.6
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Support Vector MachineLecture5.7
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KNNLecture5.8
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Ensemble LearningLecture5.9
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ClusteringLecture5.10
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Implementation Using Scikit-learnLecture5.11
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Neaural Networks and Deep Learning 4
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Intro. to Neural Neural NetworksLecture6.1
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Intro. to Deep Learning(DL)Lecture6.2
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Convolutional Networks(CNN)Lecture6.3
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DL Using Tensorflow/KerasLecture6.4
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Capstone Project #1 0
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Capstone Project #2 0
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Apache Hadoop 5
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Introduction to HadoopLecture9.1
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Hadoop InstallationsLecture9.2
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HDFSLecture9.3
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MapReduce APILecture9.4
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ExamplesLecture9.5
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Apache Spark 7
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Introduction to SparkLecture10.1
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Spark InstallationLecture10.2
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RDDsLecture10.3
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Spark StreamingLecture10.4
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Data FramesLecture10.5
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MLLIBLecture10.6
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ExamplesLecture10.7
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