Teaching (Spring)

Data types

1. None, Numeric (Int, Float, Bool, Complex), Converting from one type to another

2. List, Accessing the elements of a list

3. Tuple, Sets, Dictionary

4. Strings: String manipulation functions (Concatenate, Replace, Slice, Split, Join)

Flow control statements

1. If…Else statement

Looping statements

1. for loop syntax

2. while loop syntax

Functions, Libraries, Classes 

Exception handling

Python libraries for ML

Pandas

1. Pandas DataFrames

2. Introduction

3. Indexing DataFrames

4. Pandas loc and iloc

Numpy

1. Numpy array syntax and parameters

2. Numpy ndarray creation

3. Subsetting numpy arrays

SciPy

1. Functions of SciPy

2. Linear algebra with SciPy

Matplotlib

1. Python matplotlib – Different plots

2. Bar graph

3. Histogram

4. Scatter plot

5. Pie chart

Seaborn

1. Seaborn – Different plots

2. Seaborn: Scatter Plots

Introduction to machine learning

Types of learning

1. Supervised and Unsupervised Learning 

2. Semi-supervised and Reinforcement Learning 

Supervised learning

1. Classification

2. Regression

Unsupervised learning

1. Clustering

Basics of Neural Networks

Basic Steps for Principal Component Analysis (PCA )

1. Calculate the mean 

2. Calculate the covariance matrix

3. Calculate the Eigen Values 

4. Calculate the Eigen Vector 

5. Compute the Principal Component

Python code for PCA