Python Programming – Multithreading, OOP, NumPy and Pandas

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Chapter 2: Why to Learn Python Programming Language?

Lecture 1: Why to learn Python?

Chapter 3: Environment Setup

Lecture 1: Installing Python

Lecture 2: Installing PyCharm

Chapter 4: ### PYTHON FUNDAMENTALS ###

Lecture 1: Python fundamentals

Chapter 5: Python Basics

Lecture 1: First steps in Python

Lecture 2: What are the basic data types?

Lecture 3: Booleans

Lecture 4: Strings

Lecture 5: String slicing

Lecture 6: Type casting

Lecture 7: Operators

Lecture 8: Conditional statements

Lecture 9: How to use multiple conditions?

Lecture 10: Exercise – conditional statements

Lecture 11: Solution – conditional statements

Lecture 12: Logical operators

Lecture 13: Loops – for loop

Lecture 14: Loops – while loop

Lecture 15: Exercise: calculating the average

Lecture 16: Solution: calculating the average

Lecture 17: What are nested loops?

Lecture 18: Enumerate

Lecture 19: Break and continue

Lecture 20: Calculating Fibonacci-numbers

Lecture 21: Exercise: Fibonacci-numbers

Lecture 22: Solution: Fibonacci-numbers

Chapter 6: Functions in Python

Lecture 1: What are functions?

Lecture 2: Defining functions

Lecture 3: Positional arguments and keyword arguments

Lecture 4: Returning values

Lecture 5: Returning multiple values

Lecture 6: Solution – functions

Lecture 7: Yield operator

Lecture 8: Local and global variables

Lecture 9: What are the most relevant built-in functions?

Lecture 10: What is recursion?

Lecture 11: Solution – recursion

Lecture 12: Local vs global variables

Lecture 13: The __main__ function

Chapter 7: Data Structures in Python

Lecture 1: How to measure the running time of algorithms?

Lecture 2: Data structures introduction

Lecture 3: What are array data structures?

Lecture 4: What are lists in Python?

Lecture 5: Arrays introduction – operations

Lecture 6: Lists in Python

Lecture 7: Lists in Python – advanced operations

Lecture 8: Lists in Python – list comprehension

Lecture 9: (!!!) Python lists and arrays

Lecture 10: Exercise: list comprehension

Lecture 11: Solution – list comprehension

Lecture 12: Measuring running time of lists

Lecture 13: What are tuples?

Lecture 14: Mutability and immutability

Lecture 15: What are linked list data structures?

Lecture 16: Doubly linked list implementation in Python

Lecture 17: Hashing and O(1) running time complexity

Lecture 18: Dictionaries in Python

Lecture 19: Sets in Python

Lecture 20: Exercise: constructing dictionaries

Lecture 21: Solution: constructing dictionaries

Lecture 22: Sorting

Chapter 8: Object Oriented Programming (OOP)

Lecture 1: What is object oriented programming (OOP)?

Lecture 2: Class and objects basics

Lecture 3: Using the constructor

Lecture 4: Class variables and instance variables

Lecture 5: Exercise: constructing classes

Lecture 6: Solution: constructing classes

Lecture 7: Private variables and name mangling

Lecture 8: What is inheritance in OOP?

Lecture 9: The super keyword

Lecture 10: Function (method) override

Lecture 11: What is polymorphism?

Lecture 12: Polymorphism and abstraction example

Lecture 13: Exercise: abstraction

Lecture 14: Solution: abstraction

Lecture 15: Modules

Lecture 16: The __str__ function

Lecture 17: Comparing objects – overriding functions

Chapter 9: Memory Management

Lecture 1: What are stack and heap memory?

Lecture 2: Stack memory and heap memory simulation

Lecture 3: Garbage collection and reference counting

Lecture 4: Revisiting the types of variables

Lecture 5: The == and the is operators

Lecture 6: Call by reference and value