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Operators

Instructor: Applied AI Course Duration: 14 mins

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Standard Input and Output

Control flow: if else

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Python for Data Science Introduction

1.1

Python, Anaconda and relevant packages installations

23 min

1.2

Why learn Python?

4 min

1.3

Keywords and identifiers

6 min

1.4

comments, indentation and statements

9 min

1.5

Variables and data types in Python

32 min

1.6

Standard Input and Output

7 min

1.7

14 min

1.8

Control flow: if else

10 min

1.9

Control flow: while loop

16 min

1.10

Control flow: for loop

15 min

1.11

Control flow: break and continue

10 min

Plotting for exploratory data analysis (EDA)

2.1

Introduction to IRIS dataset

26 min

2.2

3D scatter plot

6 min

2.3

14 min

2.4

Limitations of Pair Plots

2 min

2.5

Histogram and Introduction to PDF(Probability Density Function)

17 min

2.6

Univariate Analysis using PDF

6 min

2.7

Mean, Variance and Standard Deviation

17 min

2.8

10 min

2.9

Percentiles and Quantiles

9 min

2.10

Box-plot with Whiskers

9 min

2.11

4 min

2.12

Summarizing Plots, Univariate, Bivariate and Multivariate analysis

6 min

2.13

Multivariate Probability Density, Contour Plot

9 min

2.14

Exercise: Perform EDA on Haberman dataset

4 min

Linear Algebra

3.1

4 min

3.2

Introduction to Vectors(2-D, 3-D, n-D)

14 min

3.3

Dot Product and Angle between 2 Vectors,Row Vector,Column Vector

14 min

3.4

Projection and Unit Vector

5 min

3.5

Equation of a line (2-D), Plane(3-D) and Hyperplane (n-D) - Copy

23 min

3.6

Equation of a Circle (2-D), Sphere (3-D) and Hypersphere (n-D)

7 min

3.7

Equation of an Ellipse (2-D), Ellipsoid (3-D) and Hyperellipsoid (n-D)

6 min

3.8

Square, Rectangle

6 min

3.9

Hyper-cube and Hyper-cuboid

3 min