Udemy

Python AI - Simply Explained Hands-On

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  • 2,260 Students
  • Updated 7/2024
  • Certificate Available
4.5
(315 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
1 Hour(s) 36 Minute(s)
Language
English
Taught by
Mouhammad Hamsho, Kemalaldin Hamso
Certificate
  • Available
  • *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
4.5
(315 Ratings)

Course Overview

Python AI - Simply Explained Hands-On

Python Bootcamp: Python Machine Learning, Python Data Science, Task Automation, Computer Vision, Python SQL

This course is Everything you will ever need to Master every detail of Python.

Are you looking to master Python from Basics all the way to Any Software Idea that comes up to your mind?

Then this is the right course for you. Because you will not only learn the basics of the language, but you will learn about all the other python supported packages along tens of Hands-On-Projects!


Update

Pygame RPG Game Design From Scratch was added (With Object Oriented Pattern Design).

Update

Web Scraping using Beautiful Soup and Selenium was added . Including Advanced Debugging Techniques.


Update

Flutter For Python section was added (UI Web/Desktop Design).


Update

SQL And Relational Databases was added (DB Basics and SQLAlchemy ). With simplified Social media project.


Let this list of covered Topics give you an Idea:

1 Python Strings and RNG
2  Conditional Statements
3 Lists and Bundle Storage
4 Finite State Machines with Python
5  Loops
6 Functions
7 Dictionaries
8  Exceptions and Crash Handling
9 Python Built-In Functions
10 Python Object Oriented Programming
11 Decorators
12 Handling text Files
13 Handling  Compressed Files
14 Data Plotting with Matplotlib
15 Directory Management.
16 Command Line Based Applications
17 Numpy and Math
18 Image Processing With OpenCV
19 Video Processing
20 Object Tracking
21 Pandas And Tabular Data
22 Python GUI Based Apps
23 Converting Python to Stand-Alone Software
24 Recommender Systems with Netflix
25 OCR and Image to Text Conversion
26 Python Data Analysis Breakdown
27 Artificial Data Generation
28  Python Machine Learning Breakdown
29 Features Engineering
30 Seaborn for Data Visualization
31 Gaussian Naive Bayes
32 Principal Component Analysis (PCA) 
33 Linear Regression 
34 Polynomial Regression 
35 K-means Clustering 
36 Support Vector Machine (SVM) 
37 Linear Discriminate Analysis (LDA) 
38  t-SNE 
39 Hierarchical Clustering 
40 Time Series Analysis 
41 Decision Trees
42 Random Forests
43 Reinforcement Learning
44 Natural Language Processing (NLP)
45 Building A Messages and Emails Spam FIlter
46 Market Segmentation
47 Analyzing House Pricing
48. Deep learning Breakdown
49  Artificial Neural Networks
50 Image Classification
51 Convultional Neural Networks
52 Automating Accountant Job
53. Building Web Apps
54 Flutter For Python Using Flet
55 Python SQL and Relational Databases (Using SQLAlchemy)
56. Pygame and RPG Advanced Game Development

And more

See all of those concepts? Do you know the amount of people suffering to understand concepts like Machine Learning, Deep Learning and Data Analysis? it is actually very large. But this won't be the case if you take this course!
They will be broken down to very simple terms,
Like explaining to a 5 years old how algorithms works!

Start now an lay a job in one of the hottest Programming language in the market now!

Because of the high diversity of topics in this course, this will be the only Python Course you will need to build any Python Software.

Plus I will be you mentor, so you can ask me any question any time and I will be more than happy to guide you through!



Course Content

  • 55 section(s)
  • 503 lecture(s)
  • Section 1 Installing And Preparing The Environment
  • Section 2 Strings , Random Number Generators and CLI Game Fun
  • Section 3 Conditional Statements and Branching
  • Section 4 Lists and Bundle Data storage
  • Section 5 Finite State Machines In Python
  • Section 6 Loops and Data Iteration
  • Section 7 Organizing Code With Python Functions
  • Section 8 Graphical Game: Build Your First Ping Pong
  • Section 9 Data Storage With Python Dictionaries
  • Section 10 Exceptions and Preventing Program Crash
  • Section 11 Lambda and Built-In Functions
  • Section 12 Python Object Oriented Programming
  • Section 13 Decorators and Wrapper Functions
  • Section 14 Pygame: RPG Game Development using Object Oriented Programming
  • Section 15 Read/Write Zip/Unzip Files
  • Section 16 Introduction To Matplotlib
  • Section 17 Directory Management
  • Section 18 Building Command Line Applications
  • Section 19 Numpy and Advanced Data structures
  • Section 20 Image Processing with OpenCV
  • Section 21 Video Processing
  • Section 22 Object Tracking In Video
  • Section 23 The Jupyter Notebook
  • Section 24 Pandas and Tabular Data Processing
  • Section 25 GUI Apps
  • Section 26 GUI App Portfolio Project
  • Section 27 Converting Python To Stand-Alone Software
  • Section 28 Flutter For Python - UI
  • Section 29 Portfolio Project: Netflix Recommender Systems Introduction
  • Section 30 OCR and Image To Text Conversion
  • Section 31 GUI Automation And Speech Recognition
  • Section 32 Selenium: Webforms Automation
  • Section 33 Web Scraping With Selenium & Beautiful Soup
  • Section 34 Starting Data Science: Artificial Data
  • Section 35 ML Terminologies Easily Explained
  • Section 36 Data Preprocessing And Features Engineering
  • Section 37 Seaborn
  • Section 38 Gaussian Naive Bayes
  • Section 39 Principal Component Analysis (PCA)
  • Section 40 Linear And Polynomial Regression
  • Section 41 K-means and Classification Models
  • Section 42 Support Vector Machine (SVM)
  • Section 43 Linear Discriminate Analysis (LDA)
  • Section 44 t-SNE
  • Section 45 Hierarchical Clustering
  • Section 46 Random Forests And Decision Trees
  • Section 47 Reinforcement Machine Learning and Teaching Models
  • Section 48 Natural Language Processing (NLP) and Text Comprehension
  • Section 49 NLP Portfolio Project
  • Section 50 Deep Learning With Artificial Neural Networks
  • Section 51 Deep Learning Portfolio Project
  • Section 52 Deep Learning Image Classification Portfolio Project
  • Section 53 Artificial Intelligence Web Apps
  • Section 54 AI Web App Portfolio Project
  • Section 55 SQL And Relational Databases (SQL Alchemy and SQLite)

What You’ll Learn

  • Basics Of Python
  • Python Object Oriented Programming
  • Numpy and Pandas for Data Analysis
  • Image Processing with OpenCV
  • Video Processing with OpenCV
  • Voice Recognition And Voice Automation
  • OCR for Converting Images to Text
  • Data Analysis And Visualization Using Matplotlib And Seaborn
  • Data Pre-Processing For Machine And Deep Learning
  • Machine Learning Algorithms Simply Explained And Coded
  • Deep Learning Algorithms
  • Natural Language Processing (NLP)
  • Reinforcement Learning And Self Learning Algorithms
  • Automating The Boring Tasks
  • Building Command Line Interfaces
  • Building GUI Interfaces
  • Building Web-based Machine Learning Apps
  • Flutter For Python -Flet
  • Databases
  • SQLAlchemy
  • Web Scraping With Bs4 and selenium


Reviews

  • B
    Brian Price
    4.0

    Good instructor very clear and gives good information on core concepts but only 4 stars the course is a bit dated for those trying to follow coding examples.

  • I
    ISAAC O
    5.0

    The instructor is very knowledgeable

  • S
    Steve Howard
    4.0

    So far, a bit basic for me. My career was as a programmer, and I have been playing with Python for a while. I hope there is some discussion later regarding various libraries available. Hopefully there will be some AI integration tips

  • P
    Pallavi Dwivedi
    3.0

    I have done python course few years back thats why I could recollect many of the things but if its for beginners then at some points things and particular topic isnt clear .

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