Python AI - Simply Explained Hands-On from Udemy

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 RNG2 Conditional Statements3 Lists and Bundle Storage4 Finite State Machines with Python5 Loops 6 Functions7 Dictionaries 8 Exceptions and Crash Handling 9 Python Built-In Functions10 Python Object Oriented Programming11 Decorators 12 Handling text Files13 Handling Compressed Files14 Data Plotting with Matplotlib15 Directory Management.16 Command Line Based Applications17 Numpy and Math18 Image Processing With OpenCV19 Video Processing20 Object Tracking21 Pandas And Tabular Data22 Python GUI Based Apps23 Converting Python to Stand-Alone Software24 Recommender Systems with Netflix25 OCR and Image to Text Conversion26 Python Data Analysis Breakdown27 Artificial Data Generation28 Python Machine Learning Breakdown29 Features Engineering30 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 Forests43 Reinforcement Learning 44 Natural Language Processing (NLP)45 Building A Messages and Emails Spam FIlter46 Market Segmentation47 Analyzing House Pricing48. Deep learning Breakdown49 Artificial Neural Networks 50 Image Classification 51 Convultional Neural Networks52 Automating Accountant Job53. Building Web Apps54 Flutter For Python Using Flet55 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.

What's inside

Learning objectives

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
Show more
Show less

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
Show more
Show less

Syllabus

Installing And Preparing The Environment

Introduction

Installing Environment

Opening IDE

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers a wide range of topics, from basic Python syntax to advanced concepts like machine learning and deep learning, providing a comprehensive learning experience

Includes modules on data analysis with Pandas, data visualization with Matplotlib and Seaborn, and machine learning algorithms, which are essential tools and techniques in these fields

Explores GUI development, web app creation, and Flutter for Python using Flet, enabling learners to create interactive and visually appealing applications

Delves into image processing with OpenCV, video processing, voice recognition, and OCR, offering specialized knowledge for niche applications and projects

Features numerous hands-on projects throughout the course, allowing learners to apply their knowledge and build a portfolio of Python software

Includes a section on SQL and relational databases using SQLAlchemy, which is a valuable skill for managing and interacting with data in Python applications

Reviews summary

Broad introduction to python and ai

According to learners, this course offers a comprehensive introduction to Python, ranging from absolute basics to advanced topics like AI, Machine Learning, and Deep Learning. Many appreciate the hands-on approach and the abundance of code examples and projects, which helps solidify understanding. The instructor is frequently cited as being responsive and helpful. While the course is praised for making complex subjects like AI simply explained and accessible to beginners, some reviews note that due to its vast scope, it tends to lack depth in certain advanced areas, making it more of a broad overview than a deep dive for experienced practitioners. The inclusion of regular updates is also a positive point, keeping the content relatively fresh.

Explores a wide array of Python applications.

"The course covers everything from Python basics to AI, ML, DL, NLP, GUI, Web Dev, Games, Databases..."

"I was surprised by the sheer number of different areas of Python covered in this one course."

"This course attempts to be the 'only Python course you need', touching upon many, many subjects."

New content sections are added over time.

"It's great that the instructor keeps adding new sections like Web Scraping and Databases."

"I noticed recent updates were added, which shows the course is actively maintained."

"The new Flutter section was a nice bonus I wasn't expecting when I first enrolled."

Instructor actively answers questions and helps.

"The instructor was very quick to respond to my questions in the Q&A section."

"I appreciate the support provided by the instructor throughout the course."

"It was great to have the instructor actively involved and helping troubleshoot issues."

Explains complex concepts simply for newcomers.

"Coming in with almost no Python experience, I found the initial sections very clear and easy to follow."

"The explanations for ML/DL concepts were broken down really well, making them accessible even for someone new."

"Perfect course if you are just starting with Python and want a taste of different fields like AI."

Includes practical coding exercises and demos.

"The hands-on coding examples and projects were the most valuable part of the course for me."

"I really liked how every concept was followed by a coding demo or a small project."

"Building the small games and AI models really helped reinforce the lectures."

Speed varies greatly between sections.

"The start was slow, but then it felt like we zipped through complex topics very quickly."

"Pacing could be more consistent; some parts are extremely detailed, others just skim the surface."

"Found the transition from basics to advanced AI concepts quite abrupt."

Covers many topics but not in great detail.

"While it covers many topics, it's mostly introductory; not enough depth for professional use in specific areas."

"The advanced sections on ML algorithms felt a bit rushed and didn't go into enough mathematical detail."

"Good overview, but if you want to specialize in one area like NLP or CV, you'll need another course."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python AI - Simply Explained Hands-On with these activities:

Review Python Basics

Show steps

Solidify your understanding of fundamental Python concepts before diving into more advanced AI topics. This will make the course material easier to grasp.

Browse courses on Python Basics

Show steps

Review data types, loops, and functions.
Practice writing simple Python scripts.

Review 'Python Crash Course'

Show steps

Reinforce your Python knowledge with a comprehensive guide that covers the basics and introduces practical projects. This will prepare you for the hands-on projects in the course.

View Python Crash Course, 2nd Edition: A Hands-On,... on Amazon

Show steps

Read the chapters on basic Python syntax and data structures.
Complete the exercises at the end of each chapter.

Build a Simple Chatbot

Show steps

Apply your Python skills to create a basic chatbot using NLP techniques. This project will solidify your understanding of NLP concepts covered in the course.

Show steps

Design the chatbot's functionality and conversation flow.
Implement the chatbot using Python and an NLP library.
Test and refine the chatbot's responses.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Practice Pandas Data Manipulation

Show steps

Sharpen your Pandas skills by working through data manipulation exercises. This will improve your ability to analyze and process data for AI models.

Show steps

Download a sample dataset from Kaggle.
Perform data cleaning, filtering, and aggregation using Pandas.
Visualize the data using Matplotlib or Seaborn.

Create a Blog Post on Linear Regression

Show steps

Deepen your understanding of linear regression by explaining the concept in a blog post. This will help you articulate the key principles and applications of this algorithm.

Show steps

Research linear regression and its applications.
Write a clear and concise blog post explaining the concept.
Include examples and visualizations to illustrate the key points.

Follow OpenCV Tutorials for Object Tracking

Show steps

Enhance your object tracking skills by following OpenCV tutorials. This will provide hands-on experience with video processing techniques.

Show steps

Find OpenCV tutorials on object tracking.
Implement the object tracking algorithms in Python.
Experiment with different tracking methods and parameters.

Review 'Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow'

Show steps

Expand your knowledge of machine learning algorithms and deep learning frameworks with a comprehensive guide. This will provide a deeper understanding of the concepts covered in the course.

View Hands-On Machine Learning with Scikit-Learn,... on Amazon

Show steps

Read the chapters on machine learning algorithms and neural networks.
Work through the code examples and exercises in the book.

Career center

Learners who complete Python AI - Simply Explained Hands-On will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

A Machine Learning Engineer builds and deploys machine learning models. This course helps build a foundation by covering a wide range of machine learning algorithms. The course's practical approach, including hands-on projects and tutorials, gives the learner the experience needed to begin working with the tools and techniques in machine learning. The sections on data analysis and visualization using Matplotlib and Seaborn, data pre-processing, and feature engineering provide essential skills for preparing data for machine learning models. The course also simplifies machine learning algorithms. The coverage of deep learning, including neural networks and convolutional neural networks, enables a machine learning engineer to implement these advanced techniques.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A Data Scientist analyzes complex data to extract insights and inform business decisions. This course provides a broad overview of the tools and techniques needed in data science. The sections on data analysis and visualization using Matplotlib and Seaborn, along with the coverage of Pandas and tabular data, give a data scientist the ability to explore and understand data. The course's coverage of machine learning algorithms, including linear regression, clustering, and support vector machines, enables a data scientist to build predictive models. Furthermore, it covers natural language processing, so a data scientist can work with text data. The course's hands-on projects and real-world examples provide valuable experience for a data scientist.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst collects, cleans, and analyzes data to identify trends and provide insights. This course helps build a foundation for a career as a data analyst. The sections on data analysis and visualization using Matplotlib and Seaborn give a data analyst the skills to create meaningful visualizations. The coverage of Pandas and tabular data enables a data analyst to manipulate and analyze data effectively. The course also covers SQL and relational databases, which a data analyst can use to extract data from databases. Furthermore, it's hands-on projects and examples provide valuable experience for a data analyst looking to enter the field.

See salaries and explore the career path for Data Analyst

Artificial Intelligence Developer

An Artificial Intelligence Developer creates intelligent systems and applications. The comprehensive curriculum helps build a foundation for a career in AI development. The course's focus on machine learning and deep learning algorithms, including neural networks and convolutional neural networks, gives an AI developer the ability to create intelligent models. The sections on natural language processing and computer vision enable an Artificial Intelligence Developer to build systems that can understand and interact with the world. The hands-on projects and practical examples provide experience applying these techniques to real-world problems.

See salaries and explore the career path for Artificial Intelligence Developer

Software Engineer

A Software Engineer designs, develops, and maintains software applications. This course helps build a foundation in software engineering principles and practices. The course's coverage of Python basics, object-oriented programming, and data structures gives a software engineer the fundamental skills. The sections on GUI development and web application building allow a software engineer to create user interfaces and web-based applications. The course also covers topics such as command-line interfaces, file handling, and database interaction, which a software engineer will find helpful.

See salaries and explore the career path for Software Engineer

Computer Vision Engineer

A Computer Vision Engineer develops systems that can 'see' and interpret images. This course contains valuable information for aspiring computer vision engineers. The sections on image processing with OpenCV and video processing give a computer vision engineer the core skills needed to work with visual data. The course also covers object tracking and OCR, which can be applied to various computer vision tasks. The sections on machine learning and deep learning, especially convolutional neural networks, enable a Computer Vision Engineer to build advanced image recognition systems.

See salaries and explore the career path for Computer Vision Engineer

Natural Language Processing Engineer

A Natural Language Processing Engineer develops systems that can understand and generate human language. This course may be helpful for those seeking a career in natural language processing. The section on natural language processing (NLP) provides a practical introduction to the field. The coverage of machine learning algorithms is also helpful, as machine learning techniques are often used in NLP tasks. The course's hands-on approach and practical examples provide valuable skills for an engineer.

See salaries and explore the career path for Natural Language Processing Engineer

Robotics Engineer

A Robotics Engineer designs, builds, and programs robots. This course may provide useful skills for aspiring robotics engineers. The sections on image and video processing with OpenCV can enable robots to 'see' and interact with their environments. The course's coverage of Python basics, object-oriented programming, and control structures provides a foundation for programming robot behavior. In particular, the section on finite state machines is relevant to robot control. The skills taught will be especially helpful for a robotics engineer.

See salaries and explore the career path for Robotics Engineer

Data Architect

A Data Architect designs and manages an organization's data infrastructure. This course may be useful for aspiring data architects. The course's coverage of SQL and relational databases helps a Data Architect design efficient database systems. The sections on data analysis and data pre-processing are also helpful. The course's overview of various data-related technologies provides a broad perspective for a Data Architect.

See salaries and explore the career path for Data Architect

Business Intelligence Analyst

A Business Intelligence Analyst analyzes data to identify trends and insights that can improve business performance. This course may be useful for those interested in business intelligence. The sections on data analysis and visualization using Matplotlib and Seaborn give a Business Intelligence Analyst the skills to create meaningful reports and dashboards. The coverage of SQL and relational databases is also valuable, as business intelligence analysts often need to extract data from databases. The topics covered will be especially helpful for a Business Intelligence Analyst.

See salaries and explore the career path for Business Intelligence Analyst

Data Visualization Specialist

A Data Visualization Specialist creates visual representations of data to communicate insights. This course may be useful for a Data Visualization Specialist. The sections on data analysis and visualization using Matplotlib and Seaborn are directly relevant to this role. These tools and techniques, taught by the course, enable a Data Visualization Specialist to create compelling and informative visualizations. The course's coverage of Pandas is also useful for manipulating and preparing data for visualization.

See salaries and explore the career path for Data Visualization Specialist

AI Product Manager

An AI Product Manager guides the development and launch of AI-powered products. This course may be useful for aspiring AI product managers. The course's overview of machine learning, deep learning, and natural language processing provides a foundation for understanding the capabilities and limitations of AI technologies. The sections on building web applications and GUI interfaces are also helpful, as AI products often have user interfaces. The knowledge gained can assist an AI Product Manager.

See salaries and explore the career path for AI Product Manager

Financial Analyst

A Financial Analyst analyzes financial data to provide insights and recommendations. This course may be useful for a financial analyst. The sections on data analysis and visualization, using tools like Matplotlib and Seaborn, enables a financial analyst to analyze financial data and present findings in a clear and concise manner. The course's coverage of machine learning algorithms can also be applied to financial modeling and forecasting.

See salaries and explore the career path for Financial Analyst

Game Developer

A Game Developer creates video games for various platforms. This course may be useful for those interested in game development. The sections on Pygame and RPG game development using object-oriented programming provide a foundation for building games. The course's coverage of Python basics, control structures, and data storage formats is also helpful. These aspects will be helpful for a game developer.

See salaries and explore the career path for Game Developer

Web Developer

A Web Developer builds and maintains websites and web applications. This course may be useful for aspiring web developers. The sections on building web applications and GUI interfaces provide a solid starting point for web development. The course's coverage of Python basics, object-oriented programming, and data structures is also helpful. The aspects taught by the course may be useful for a web developer.

See salaries and explore the career path for Web Developer

Python AI - Simply Explained Hands-On

Here's a deal for you

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Broad introduction to python and ai

Activities

Career center

Reading list

Share

Similar courses

Udemy Buyer Protection & Guarantee

Free Lecture Previews

30-Day Money-Back Guarantee

Verified Academic & Industry Partner