Section outline

    • Introduction

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      Class video - 20/09/2021 (Section: A) URL
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      Class video - 20/09/2021 (Section: B) URL
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      Class video - 22/09/2021 (Section: C) URL
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      Class video - 21/09/2021 (Section: D) URL
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    • Lecture-1

    • Session I: Basics of Python

    • Learning Objectives

      • Discuss the basics of Python
        • Syntax
        • Variable and data types
        • Arithmetic operations
    • Resources of learning

    • Class video

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      Class video - 27/09/2021 (Section: A) URL
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      Class video - 27/09/2021 (Section: B) URL
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    • Lecture-2

    • Session II: Basics of Python

    • Learning Objectives

      • Discuss the basics of Python
        • Conditional logics
        • Loops
    • Resources of learning

    • Class video

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      Class video - 04/10/2021 (Section: A) URL
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      Class video - 07/10/2021 (Section: C) URL
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      Class video - 05/10/2021 (Section: D) URL
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    • Lecture-3

    • Session III: Basics of Python

    • Learning Objectives

      • Discuss the basics of Python
        • Lists
        • Tuples
        • String
        • Function
        • Module
    • Resources of learning

    • Class video

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      Class video - 18/10/2021 (Section: A) URL
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      Class video - 18/10/2021 (Section: B) URL
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      Class video - 28/10/2021 (Section: C) URL
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      Class video - 19/10/2021 (Section: D) URL
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    • Assessment of Python

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    • Lab Evaluation 1 - 25/10/2021 (Section: A)

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      Question URL
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    • Lab Evaluation 1 - 25/10/2021 (Section: B)

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      Question URL
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    • Lab Evaluation 1 - 04/11/2021 (Section: C)

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      Question URL
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    • Lab Evaluation 1 - 26/10/2021 (Section: D)

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      Question URL
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    • Lecture-4

    • Graph searching algorithm

    • Learning Objectives

      • Implementing the following graph algorithms
        • BFS
        • DFS
    • Resources of learning

    • Class video

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      Class video - 01/11/2021 (Section: A) URL
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      Class video - 10/11/2021 (Section: B) URL
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      Class video - 25/11/2021 (Section: C) URL
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      Class video - 02/11/2021 (Section: D) URL
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    • Lecture-5

    • Dataset pre-processing and simple linear regression

    • Learning Objectives

      • Understanding and demonstration of the dataset preprocessing techniques
        • Importing libraries and dataset
        • Taking care of missing data
        • Encoding categorical data
        • Splitting the dataset into the training set and test set
        • Feature scaling
      • Understanding and demonstration of the linear regression algorithm
        • Importing libraries and dataset
        • Preprocessing of the dataset
        • Predicting using linear regression
        • Visualizing the results

    • Class video

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      Class video - 06/12/2021 (Section: A) URL
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      Class video - 08/12/2021 (Section: B) URL
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      Class video - 09/12/2021 (Section: C) URL
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      Class video - 07/12/2021 (Section: D) URL
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    • Lab Final

    • Section: A - 13/12/2021

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      Question file URL
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      Dataset URL
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    • Section: B - 13/12/2021

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      Question file URL
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      Dataset URL
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    • Section: D - 14/12/2021

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      Question file URL
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      Dataset URL
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    • Section: C - 16/12/2021

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      Question file URL
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      Dataset URL
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