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1. Introduction to Artificial Intelligence 3
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What is Artificial Intelligence?Lecture1.1
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History of AILecture1.2
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ApplicationsLecture1.3
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Python Fundamentals 5
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Intro. to PythonLecture2.1
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Variables and OperatorsLecture2.2
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Data TypesLecture2.3
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Control Flow StatementsLecture2.4
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OOPs ConceptsLecture2.5
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Statistics 4
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Basic ConceptsLecture3.1
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Descriptive StatisticsLecture3.2
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Inferential StatisticsLecture3.3
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Hypothesis TestingLecture3.4
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Machine Learning 12
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Intro. to Machine Learning(ML)Lecture4.1
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Types of MLLecture4.2
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Linear RegressionLecture4.3
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Logistics RegressionLecture4.4
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Decision TreesLecture4.5
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Random ForestLecture4.6
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Support Vector MachinesLecture4.7
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KNNLecture4.8
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Ensemble LearningLecture4.9
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ClusteringLecture4.10
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Developing ML models using Scikit-learnLecture4.11
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Caste StudiesLecture4.12
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Capstone Project#3 0
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5. Deep Learning Using Tensorflow and Keras 4
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Intro. to Neural NetworksLecture6.1
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Intro to Deep LearningLecture6.2
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Convolutional Neural Networks(CNN)Lecture6.3
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Developing DL Models using TensorFlow and KerasLecture6.4
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Computer Vision Using OpenCV 5
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What is Computer Vision?Lecture8.1
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OpenCV BasicsLecture8.2
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Image DetectionLecture8.3
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Face DetectionLecture8.4
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Object DetectionLecture8.5
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Natural Language Processing 3
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Basic Concepts of Text ProcessingLecture9.1
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Lexical ProcessingLecture9.2
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Syntax and SemanticsLecture9.3
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Capstone Project#2 0
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Final Quiz 0
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Reinforcement Learning 4
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Intro. to RLLecture12.1
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Basic ConceptsLecture12.2
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Markov Decision ProcessesLecture12.3
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Q-learningLecture12.4
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