AI

Introduction to Programming and Python

What is programming and its main three concepts

What and why Python

Compiler vs Interpreter

Task Management and Bug Tracking with JIRA

Basics of CMD commands

The concept behind the virtual environment

Python, pip, and Jupyter installation

What are Variables

Variables creation rules

Creating and dealing with quotations

Data types

String Variables

Strings Features

String slicing and indexing

String built in functions and methods

Injection of variables into strings

Numerical Variables

Numerical Variables

Int, float, and complex

Mathematics operation

Comparison Operators

Boolean Variables

Numerical and Boolean

What is the function and why to use it

Function Creating steps

Local and global variables

Functions arguments

Function single and multiple returns

Nested Functions

What is control flow and how do applications work

Elements of control flow

If, elif and else statement

While loop statement

For statement

What is the difference between normal programming and OOP

OOP the main concept

Encapsulation

Abstraction

Inheritance

Polymorphism

Creating and managing lists

Lists Features

Lists built-in functions

List Concatenation and List Replication

Adding, removing, and updating list Items

Lists indexing and slicing

Sets and Tuples

Difference between list, set, and tuple

Sets Features

Sets built-in functions

Sets Join

Tuples Features

Adding, removing, and updating tuple items

Dictionaries

Dictionaries creating

Dictionaries Features

Updating, adding, removing in Dictionaries

Dictionaries merge

Dictionaries' built-in methods

Files and OS with Python

Read files

Write in files

System commands with Python

Databases

Data Types

Database Types

What is a Relational Database

Why MYSQL

Database data types

MYSQL installation

MySQL Constraints (rules)

Most Important SQL Commands

Python and MySQL connection

Connection between Python and databases

Dealing with SQL within Python

Numbers Types

Sets

Intervals

Functions

Summations

Exponents

Logarithms

Euler’s Number

Limits

Derivatives

Integrals

Scalar, vector and matrix

Linear Algebra Introduction

Special Types of Matrices

Operations on Matrices

Matrix Transpose

Numpy

Pandas

Populations, Samples, and Bias

Mean, Median and Mode

Variance and Standard Deviation

Graphs

The Central Limit Theorem

Confidence Intervals

P Values

Hypothesis Testing

Joint

Union

} Conditional

Distributions

Missing values

Outliers

Inconsistent

Data conflict

Label encoding

Basic Linear Regression

Residuals and Squared Errors

Best Fit Line

Gradient Descent

Overfitting and Variance

Stochastic Gradient Descent

The Correlation Coefficient

Prediction Intervals

Multiple Linear Regression

Logistic Function

Multivariable Logistic Regression

Confusion Matrices

Receiver Operator Characteristics / Area Under Curve

Knn, Linear Models, Naive Bayes Classifiers

Decision Trees

Model Evaluation

Support Vector Machines

Evaluating

KMeans

Agglomerative Clustering

DBSCAN

Evaluating

Simple Neural Network

Activation Functions

Forward Propagation

Backpropagation

Weight and Bias Derivatives

Stochastic Gradient Descent

Images Classifier

Face Detection

Object Tracking