Course curriculum
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1
Student Guide Book
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Student Guide Book
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Schedule/curriculum Time Table
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2
Introduction Python - Pre - Learning Session
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Python Crash course Introduction
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python Demo n install
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Python Intro and Installation
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Basic python and datatype
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Basic,Number,string
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Data types
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3
Chapter 1 - Control flow
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If else conditions
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While & for loop conditions
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4
chapter -2 Deep Learning
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01_Logistic Regression vs DL
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Copy of TesorFlow and Keras
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5
Chapter 3 - Exception Handling
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Exception Handling
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6
Chapter 4 -Functions
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Functions
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7
Chapter 5 - OOPS
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CLASSES
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Copy of OOP
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8
Chapter -6 Libraries
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Introduction to Libraries
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Library Introduction
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Matplolib
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Numpy
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Pandas
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9
Chapter 7 - Mathematics
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Data
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Linear Algebra
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Statistics
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stats - probs
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10
Chapter 8 - Machine Learning Models
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clustering
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Clustering
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Evaluation Metrics
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Logistic Regression - Feature Regression
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Logistic Regression
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Linear And Logistic
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Simple Linear regression
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Multiple Linear regression
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11
Zoom Live Session links
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ML _1st Live Session_ 05 july,2021 _ 6:00 pm
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ML _2nd Live Session_ 07 july,2021 _ 6:00 pm
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ML_3rd Live Session_ Jul 9, 2021 06:00 PM
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ML_4th Live Session_ Jul 12, 2021 06:00 PM
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ML_5th Live Session_ Jul 14, 2021 06:00 PM
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ML_6th Live Session_ Jul 16, 2021 06:00 PM
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ML_7th Live Session_ Jul 19, 2021 06:00 PM
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ML_8th Live Session_ Jul 21, 2021 06:00 PM
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ML_9th Live Session_ Jul 23, 2021 06:00 PM
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Ml_10th Live Session_ Jul 26, 2021 06:00 PM
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Ml_11th Live Session_ Jul 28, 2021 06:00 PM
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Ml_12th Live Session_ Jul 30, 2021 06:00 PM
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Ml_13th Live Session_ Aug 02, 2021 06:00 PM
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Ml_14th Live Session_ Aug 04, 2021 06:00 PM
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ML_15th Live Session_ Aug 6, 2021 06:00 PM
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ML_16th Live Session_ Aug 9, 2021 06:00 PM
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ML_17th Live Session_ Aug 11, 2021 06:00 PM
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ML_18th Live Session_ Aug 13, 2021 06:00 PM
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ML_19th Live Session_ Aug 16, 2021 06:00 PM
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12
Live Sessions Recordings
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ML_1st Sessions_05-07-2021
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ML_Session_16_08_2021
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Wireless Sound Control (1)
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13
Project
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Major Project
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14
Live Project Instructions
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Orientation Meeting_Live Industrial Project
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15
Internship Project 1_ Tic-Tac-Toe
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Part-1
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Part-2
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16
Internship Project-2_ Restaurant Review using NLP
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Restaurant Review using NLP
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Data Set
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17
Internship Project Live Sessions
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Project 1_ Tic-Tac-Toe
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Project 2- Restaurant Review using NLP
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Project Submission LInk
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Orientation meeting
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18
Module 1: Installing and Starting Python
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1.1: Overview
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1.2: Installing Python
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1.3: Interactive Python
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1.4: Significant Whitespace
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1.5: Python Culture
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1.6: The Python Standard Library
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1.7: Summary
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Installing and Starting Python Slides
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19
Module 2: Scalar Types, Operators and Control Flows
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2.1: Overview
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2.2: Relational Operators
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2.3: Control Flow
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2.4: While Loops
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2.5: Summary
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Scalar Type Operators and Control Flow Slides
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20
Module 3: Introducing Strings, Collections and Iterations
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3.1: Overview
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3.2: String
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3.3: String Literals
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3.4: Bytes
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3.5: List
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3.6: Dictionary
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3.7: For Loop
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3.8: Putting It All Together
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3.9: Summary
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Introducing Strings, Collections and Iterations Slide
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21
Module 4: Modularity
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4.1: Overview
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4.2: Modules
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4.3: Functions
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4.4: Name
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4.5: The Execution Model
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4.6: Command Line Arguments
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4.7: Docstrings
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4.8: Comments
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4.9: Shebang
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4.10: Summary
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Modularity Slides
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22
Module 5: Objects and Types
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5.1: Overview
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5.2: Passing Arguments and Returning Values
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5.3: Function Arguments
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5.4: Python's Type System
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5.5: Scopes
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5.6: Everything is an Object
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5.7: Summary
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Objects and Types
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23
Module 6: Built-in Collections
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6.1: Overview
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6.2: Tuples
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6.3: Strings
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6.4: Ranges
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6.5: Lists
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6.6: Dictionaries
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6.7: Sets
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6.8: Protocols
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6.9: Summary
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Built-in Collections Slides
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Codes for Built-in Collections
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24
Module 7: Exceptions
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7.1: Overview
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7.2: Exceptions and Control Flow
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7.3: Handling Exceptions
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7.4: Exceptions and Programmer Errors
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7.5: Re-raising Exceptions
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7.6: Exceptions and Part of the API
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7.7: Exceptions and Protocols
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7.8: Avoid Explicit Type Checks
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7.9: It's Easier to Ask Forgiveness Than Permission
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7.10: Cleanup Actions
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7.11: Platform Specific Code
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7.12: Summary
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Exceptions Slide
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25
Module 8: Iterations and Iterables
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8.1 Overview
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8.2: List and Set Comprehensions
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8.3: Dictionary Comprehensions
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8.4: Filtering Comprehensions
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8.5: Iteration Protocols
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8.6: Generator Functions
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8.7: Maintaining State in Generators
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8.8: Laziness and the Infinite
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8.9: Generator Expressions
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8.10: Iteration Tools
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8.11: Summary
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Iteration and Iterables Slides
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26
Module 9: Classes
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9.1: Overview
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9.2: Classes
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9.3: Defining Classes
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9.4: Instance Methods
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9.5: Instance Initializers
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9.6: A Second Class
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9.7: Collaborating Classes
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9.8: Booking Seats
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9.9: Methods for Implementation Details
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9.10: Object Oriented Design with Function Objects
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9.11: Polymorphism and Duck Typing
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9.12: Inheritance and Implementation Sharing
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9.13: Summary
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Classes Slides
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27
Module 10: File IO and Resource Managements
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10.1: Overview
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10.2: Opening Files
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10.3: Writing Text
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10.4: Reading Text
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10.5: Appending Text
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10.6: Iterating Over Files
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10.7: Closing Files with Finally
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10.8: With Blocks
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10.9: Binary Files
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10.10: Bitwise Operators
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10.11: Pixel Data
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10.12: Reading Binary Data
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10.13: File-like Objects
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10.14: Context Manager
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10.15: Summary
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IO and Resource Managements Slide
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28
MTA Exam Objectives
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MTA Exam Objectives
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