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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Jupyter NoteBook Installation Guide
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Book for References
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Assignment
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2
Live Sessions
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Data Science _1st Live Session _03rd APRIL 2021 _ 6:00 pm
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Data Science _2nd Live Session _06th APRIL 2021 _ 6:00 pm
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Data Science _3rd Live Session _08th APRIL 2021 _ 6:00 pm
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Data Science _4th Live Session _13th APRIL 2021 _ 6:00 pm
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Data Science _5th Live Session _15th APRIL 2021 _ 6:00 pm
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Data Science _6th Live Session _17th APRIL 2021 _ 6:00 pm
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Data Science _7th Live Session _20th APRIL 2021 _ 6:00 pm
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Data Science _8th Live Session _22th APRIL 2021 _ 6:00 pm
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Data Science _9th Live Session _27th APRIL 2021 _ 6:00 pm
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Data Science _10th Live Session _29th APRIL 2021 _ 6:00 pm
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Data Science _11th Live Session _01th MAY 2021 _ 6:00 pm
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Data Science _12th Live Session _04th MAY 2021 _ 6:00 pm
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Data Science _13th Live Session _06th MAY 2021 _ 6:00 pm
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Data Science _14th Live Session _08th MAY 2021 _ 6:00 pm
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Data Science _15th Live Session _11th MAY 2021 _ 6:00 pm
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Data Science _16th Live Session _13th MAY 2021 _ 6:00 pm
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Data Science _17th Live Session _15th MAY 2021 _ 6:00 pm
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Data Science _18th Live Session _18th MAY 2021 _ 6:00 pm
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Data Science _19th Live Session _19th MAY 2021 _ 6:00 pm
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Data Science _20th Live Session _20th MAY 2021 _ 6:00 pm
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Data Science _21th Live Session _23th MAY 2021 _ 6:00 pm
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3
Recorded Sessions
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1st Session_03_04-2021
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2nd Session_06_04-2021 Part1
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2nd Session_06_04-2021 Part2
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3rd session_08-04-2021
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4th session_13-04-2021
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5th Session_15-04-2021
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6th Session_17-04-2021
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7th Session _20-04-2021
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8th Session_22-04-2021
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9th Session_27-04-2021
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10th Session_29-04-2021
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11th Session_01-05-2021
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12th Session_04-05-2021
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13th Session_06-05-2021
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14th Session_08-05-2021
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15th Session_11-05-2021
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16th Session_13-05-2021
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17th Session_15-05-2021
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18th Session_18-05-2021
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19th session_19-05-2021
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20th Session_20-05-2021
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21st Session_23-05-2021
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4
Project
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Mini Project Submission
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Major Project
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5
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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6
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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7
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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8
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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9
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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10
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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11
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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12
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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13
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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14
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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File IO and Resource Managements Slide
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15
MTA Exam Objectives
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MTA Exam Objectives
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16
Internship Project 1 - Linear discriminant analysis
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Wine Classification
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Code
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CSV
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17
Internship project -2 _Hierarchical Clustering
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Part-1
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Part-2
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Data Set
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Internship Project Submission Link
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