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Test

Instructor: Applied AI Course Duration: 30 mins

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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
Operators

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
2.1
Introduction to IRIS dataset and 2D scatter plot

26 min
2.2
3D scatter plot

6 min
2.3
Pair plots

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
CDF(Cumulative Distribution Function)

2.8
Mean, Variance and Standard Deviation

17 min
2.9
Median

10 min
2.10
Percentiles and Quantiles

9 min
2.11
IQR(Inter Quartile Range) and MAD(Median Absolute Deviation)

30 min
2.12
Box-plot with Whiskers

9 min
2.13
Violin Plots

4 min
2.14
Summarizing Plots, Univariate, Bivariate and Multivariate analysis

6 min
2.15
Multivariate Probability Density, Contour Plot

9 min
2.16
Exercise: Perform EDA on Haberman dataset

4 min
3.1
Why learn it ?

4 min
3.2
Introduction to Vectors(2-D, 3-D, n-D) , Row Vector and Column Vector

14 min
3.3
Equation of a line (2-D), Plane(3-D) and Hyperplane (n-D), Plane Passing through origin, Normal to a Plane

23 min
3.4
Dot Product and Angle between 2 Vectors

14 min
3.5
Projection and Unit Vector

5 min
3.6
Hyper Cube,Hyper Cuboid

3 min
3.7
Distance of a point from a Plane/Hyperplane, Half-Spaces

10 min
3.8
Equation of a Circle (2-D), Sphere (3-D) and Hypersphere (n-D)

7 min
3.9
Equation of an Ellipse (2-D), Ellipsoid (3-D) and Hyperellipsoid (n-D)

6 min
3.10
Assignment[Optional]

30 min
4.1
Test

30 min