Course curriculum
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1
DS_E-Learning Content
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Chapter 1 - Introduction to Python
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Anaconda installation
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Jupyter notebooks
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Chapter 2 - Why Python - Features of Python
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Multi Paradigm
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Open source
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Diversified
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Interpretation
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Easy and simple
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Dynamic typing
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Large Standard library
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Chapter 3 - Numbers and Variables - Numbers
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Operators
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Variables
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Dynamic Typing
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Chapter 4 - Strings
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String Methods
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String Operations
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Immutability
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String Formatting
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Chapter 5 - Lists
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List_Methods
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Tuples
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Dictionaries
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Dic_Methods
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Sets and Booleans
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Chapter 6 - Statements
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For loop
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While loops
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Chapter 7 - Functions
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Decorators
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Generators
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Chapter 8 - Object Oriented Programming (OOP) - Objects and Classes
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Attributes
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Methods
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Inheritance
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Polymorphism
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Supervised Learning
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Supervised Learning PDF
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Unsupervised Learning
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Unsupervised Learning PDF
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2
DS_Hierarchical Clustering from Personifwy_Project 1
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Hierarchical Clustering - Theory
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Hierarchical Clustering - Code
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Hierarchical Clustering IPYNB File
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Mall Customers CSV File
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3
DS_Linear Discriminant Analysis from Personifwy_Project 2
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Wine Classification using LDA
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Wine Classification IPYNB File
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Wine CSV File
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4
Recordings of Project Live Classes
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Execution of Project 1 - Hierarchical Clustering
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Execution of Project 2 - Linear Discriminant Analysis
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5
Project Submission
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Instructions for Submissions
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6
Internship Project - ChatBot from Personifwy
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ChatBot with DialogFlow - Theory
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Copy of ChatBot with DialogFlow - Code
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ChatBot - Code
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Test.qa
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Train.qa
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7
Recording and Submission of Internship Project
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Execution of Internship Project - ChatBot
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Instructions for Internship Project Submission
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