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Python for Data Science – Beginner to Advanced

This course is inspired by the NPTEL course "Python for Data Science" from IIT Madras, designed for final-year undergraduates. Over four weeks, you'll explore Python-based tools and techniques for analyzing and visualiz…

gurugyaan .in 2 courses
25Lessons
26Students enrolled
90 daysAccess
★ 5.02 ratings

Curriculum

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01

Introduction to Python for Data Science

15:52 · In this opening lesson, you’ll learn why Python is the go-to language for data science and get a solid overvi…
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02

Introduction of Python

12:49 · This lesson introduces the fundamentals of Python and its powerful role in Data Science. You’ll learn the bas…
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03

Introduction to Spyder - Part 1

9:59 · This lesson introduces the Spyder IDE, a powerful tool for Python programming in data science. You will learn…
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04

Introduction to Spyder - Part 2

14:50 · In this lesson, you will continue exploring the Spyder IDE, a powerful tool for Python programming. We will …
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05

Variables and Datatypes

12:15 · In this lesson, you will learn about variables and how to use them in Python. We will understand what dataty…
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06

Operators

21:17 · In this lesson, we will learn about Operators in Python. An operator is a special symbol that performs a com…
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07

Setup of Jupyter

6:58 · This lesson gives you clear, step-by-step instructions to install and start using Jupyter Notebook. You will…
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08

Sequence of data part 1

12:44 · In this video, we explore the sequence data types in Python, which allow us to store and manage multiple valu…
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09

Sequence Data – Part 2

13:54 · In this video, we continue exploring Sequence Data. You will learn how to work with Python’s powerful sequenc…
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10

Sequence data part 3

19:30 · In this lesson, we dive deeper into Sequence Data and explore more advanced concepts. You’ll learn about nest…
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11

Sequence Data – Part 4

35:21 · In this final part of Sequence Data, we bring everything together by exploring advanced concepts and practica…
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12

Numpy

19:54 · This lecture is about NumPy, a powerful Python library used for numerical operations. NumPy stands for Numeri…
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13

Reading data

20:18 · Reading data is the first step to extract information from it. Data can exist broadly in two formats: Structu…
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14

Pandas Dataframes - part 1

22:17
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15

Pandas Dataframes - part 2

24:03
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16

Pandas Dataframes - part 3

18:07
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17

Dealing with missing values

32:10
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18

Exploratory data analysis

29:26
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19

Control structures & Functions

28:13
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20

Data Visualization - Part 1

17:54
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21

Data Visualization-Part 2

34:40
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22

Introduction to ClassificationCase Study

26:27
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23

Classifying Personal Income

34:48
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24

Case Study - Classification

26:36
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25

Introduction to RegressionCase Study

17:56
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About this course

This course is inspired by the NPTEL course "Python for Data Science" from IIT Madras, designed for final-year undergraduates. Over four weeks, you'll explore Python-based tools and techniques for analyzing and visualizing data. What you'll learn: Python basics using Spyder IDE Data types, control structures, functions, and variables NumPy for numerical computations Data handling with Pandas (using the Toyota Corolla dataset) Visualizations with Matplotlib and Seaborn (scatter, line, bar, histogram, box, pair plots) Real-world case studies involving regression (used car price prediction) and classification (personal income classification) Free Course for educational purposes only. All original content belongs to NPTEL (National Programme on Technology Enhanced Learning) and IIT Madras, and is used here with full credit. For the complete certified course, visit: NPTEL Course Page

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