A simple python course for beginners

beginning python

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A simple python course for beginners

What You Will Learn!

  • exception handling
  • plotting with matplotlib
  • debugging
  • starting pandas
  • standardisation and normalization
  • starting pyinstaller
  • data types
  • while loops
  • lists
  • tuples
  • polymorphism
  • command line
  • python comments
  • strings and boolean types
  • getting input
  • string to integer conversion
  • if elif else
  • list comprehension
  • file manipulation
  • handling missing data
  • starting flask
  • standardization of data
  • how to make a pie chart
  • how to make a box plot
  • how to make a line chart and scatter plot
  • how to make a bar chart
  • how to make a histogram
  • heatmaps
  • violin graphs
  • pandas
  • numpy
  • jupyter
  • pytable hdfs
  • pymongo
  • sqlalchemy
  • redis
  • pymysql
  • scikit-learn
  • tensorflow
  • keras
  • seaborn
  • plotly

Description

This beginner Python course is a comprehensive introduction to the world of programming using the Python programming language. This course is designed for individuals with little to no prior coding experience, making it an ideal starting point for those looking to embark on a journey into the world of computer programming.


Throughout the course, students are introduced to the fundamental concepts of programming, including variables, data types, and basic operations. They learn how to write and execute simple Python programs, gaining hands-on experience in solving real-world problems using code.


One of the key highlights of the course is the emphasis on Python's simplicity and readability. Python's clean and intuitive syntax makes it an excellent choice for beginners, enabling them to focus on problem-solving rather than grappling with complex syntax rules.


As the course progresses, students delve into more advanced topics, such as conditional statements, loops, and functions. They learn how to control the flow of their programs, allowing them to create more sophisticated and interactive applications.


Data manipulation is another critical aspect covered in the course. Students learn how to work with lists, tuples, dictionaries, and strings, enabling them to store, retrieve, and manipulate data efficiently. This knowledge forms the foundation for more advanced data science and software development concepts.


By the end of the course, students are equipped with the skills to tackle real-world programming challenges. They can create basic applications, automate repetitive tasks, and have a solid understanding of the Python ecosystem. This beginner Python course serves as a stepping stone for those interested in pursuing careers in software development, data analysis, or any field that requires programming skills. It opens doors to a wide range of opportunities in the ever-evolving tech industry and provides a strong foundation for further learning and specialization in Python and other programming languages.

Topics : 


An introduction to Python and an overview of programming languages.


Introduction to Python and its features


Setting up Python environment (interpreter, IDE)


How to write and run your first Python program


An introduction to Python's basic syntax and variables.


Python command line


Python comments


getting input


string to integer conversion


list comprehension


exception handling


polymorphism


debugging


installing pyinstaller


the range function


Data Types and Operators


Numeric data types: int, float, complex


Strings and string manipulation


strings and boolean type variables


strings


Boolean data type and logical operators


Basic arithmetic, comparison, and assignment operators


Type conversion and type casting


changing types of variables


Control Flow


Conditional statements: if, elif, else


if elif else


Using logical operators with conditionals


while loop and list


Looping constructs: while loop, for loop


Iterating over sequences (lists, strings, tuples)


Using break and continue statements


Data Structures Part I


Understanding lists and tuples


Lists: creation, indexing, slicing, appending, and extending


Accessing elements in a list


List methods and operations


List manipulation


lists, tuples and dictionaries


Tuples: creation, accessing elements, immutability


Tuple immutability


Sets: creation, operations, and methods


Using list comprehensions


Data Structures Part II


Dictionaries: creation, accessing elements, dictionary methods


Nested data structures


Combining data structures for complex data organization


Introduction to mutability and immutability


Functions


Defining and calling functions


Function parameters and arguments


Return statements and returning values


Scope of variables: global vs local


Unordered List Item Recursion: concept and examples


Introduction to Object-Oriented Programming (OOP)


Understanding objects and classes


Defining classes and creating objects


Class attributes and methods


Instance attributes and methods


Inheritance and polymorphism basics


File Handling and Modules


Opening, reading, writing, and closing files


File Manipulation 1


File Manipulation video


File modes and file objects


Working with different file formats (text files, CSV, JSON)


Creating and using modules


Understanding modules and importing them 2


Creating and using packages


Exploring the Python Standard Library


Importing modules and packages


Error Handling and Debugging


Understanding exceptions and errors


Using try-except blocks for error handling


Raising exceptions


Debugging techniques and tools


Best practices for writing clean and debuggable code


Reflection and feedback on the course


Networking


Networking Foundations with Python


data analysis


installing pandas


plotting with matplotlib


Planning, designing, and implementing a Python application


handling missing data


standardization


how to plot a bar chart


how to plot a scatter bar and line chart


how to make a pie chart


box chart


histogram


heatmap


violin graphs


pythonic and pandas description


numpy scipy hdf5 matplotlib


jupyter


pytable hdfs


pymongo


sqlalchemy, redis, pymysql, scikit-learn


tensorflow


keras


seaborn, plotly


how to install jupyter on linux


How to install python data analysis libraries in Windows.


numpy arrays


numpy array index


pandas read csv into a data frame


pytables installing


pytables hdf5 : how to install vitables


seaborn examples


seaborn examples ( video )


bokeh


bokeh video


Dask


web development in python


What is flask ( Article )


what is flask ( Video )


Introduction to Flask framework


starting flask


Creating web applications with flask


JSON (JavaScript Object Notation)


Flask-SQLAlchemy


Flask-MongoEngine


Flask-PyMongo


Flask-WTF


CSRF


WTForms


Django


Cross-Site Scripting (XSS)


Model-View-Controller (MVC)


Web application firewalls (WAFs)


Content Security Policy (CSP)


The Open Web Application Security Project (OWASP)


Document Object Model (DOM)


DOM-based XSS


Don't Repeat Yourself (DRY)


Internationalization


Localization


Flask-Login


Flask-Admin


Gunicorn


uWSGI


scipy


scipy constants


scipy constants part 2


scipy constants weights and minutes


tensorflow


starting tensorflow


Tensorflow examples


Special cases


Working with PDF files in python


Integrating payment gateways with python


Machine learning


Light GBM


OpenAI Gym


XGBoost


Hugging Face Transformers


CatBoost


PyTorch


Generative AI


GLM PyTorch


Pyro


NeRF


StyleGAN


Software development


Making the programmer sweat



Databases


MongoDB


NoSQL


Database Interaction with SQLAlchemy


Overview of SQLAlchemy


ORM concepts



CRUD operations


Commercial packages


Routing and views


Anaconda distribution


Development tools


PyCharm


Pylint


Flake8


Visual Studio Code (VS Code)


JetBrains


IntelliJ IDEA


Conda


Git


Mercurial


Subversion


Difference between Conda and Anaconda


Mypy


PIP


Python Package Index (PyPI)


Python Packaging Metadata (PEP 566)


Python Package Index Metadata (PEP 503)


Python Software Foundation (PSF)


Python Enhancement Proposals (PEPs)




Who Should Attend!

  • Beginners to the pyhton language

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Tags

Subscribers

111

Lectures

173

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