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This video will introduce the AI Programming in Python - Beginner to Expert course. In this course we will learn Machine Learning (Scikit-learn) and Deep Learning (PyTorch, TensorFlow) and build real-world projects in Computer Vision and NLP using industry-standard tools, then learn critical MLOps skills like Docker for professional model deployment. By the end of this video you will understand the learning objectives for this course.
In this video we will cover tips for getting the most out of this course. By following these tips you won't just learn about AI, you will get hands-on experience building real world AI projects spanning from machine learning to speech recognition. By the end of this video you will be able to maximize your learning potential with these best practices for absorbing the course material.
This video will introduce this section of the course on Introduction to Python for AI. In this section we will install the needed programs for using Python for AI development like VSCode, PyCharm, and Jupyter. By the end of this video you will understand the learning objectives for this section.
In this video we will discuss why Python is the perfect language for AI development. From clean syntax, to powerful libraries like NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch, Python is the leading industry-standard language for AI development.
In this video we will examine some of the real world AI projects that were built with the Python programming language. From X-rays to chat bots to self-driving cars, Python for AI has touched nearly every industry and impacts our daily lives whether we realize it or not.
In this video we will install Python on our machine, whether you are using a Mac, Windows, or Linux operating system. By the end of this section you will have Python up-and-running on your computer.
In this video we will learn what an IDE or Integrated Development Environment is. We will learn about 3 Python IDEs that are great for AI development: Visual Studio Code, PyCharm, and Jupyter. By the end of this video you will understand the benefits of using each of these programs when developing AI using Python programming.
In this video I will walk you through installing the programs we will use in this course. You'll be provided detailed instructions for getting up-and-running with VSCode, PyCharm, and Jupyter on whatever operating system you are running be it Windows, Mac, or Linux. By the end of this video you will have the needed programs installed on your machine to be able to follow along with typing the code I show in each of the videos.
In this video we will get introduced to Jupyter Notebooks. You'll learn what a Jupyter Notebook is and how to work with them. By the end of this video you will have a clear understanding of what a Jupyter Notebook is and the basics on how to use it.
In this hands-on video, we will write our first Python script. This simple hands-on exercise will get you exposed to writing and running Python code, a foundational skill we will utilize throughout the entire course. By the end of this video you will have written your first Python code!
In this video we will learn about using the Terminal, or Command Line, to run Python code. By the end of this video you will have an understanding of how you can use your computer's built-in terminal or command line to work with Python code.
In this video we will take a look at Python versions and virtual environments. You'll gain an understanding of how to manage Python versions on your machine and how to setup a virtual environment to work in. By the end of this video you will understand the concepts of Python versions and virtual environments and how they apply to Python development.
In this video we will learn about two powerful tools for installing Python libraries: pip and conda. By the end of this video you will understand how you can use pip and conda to install libraries of code that give you access to additional functionality for the Python scripts you create.
In this video we will go over the answers and explanations to the quiz questions. By the end of this video you will have a clearer understanding of the section material and be ready to move onto the next section of the course.
In this video we will look at a recap of what we learned in this section of the course, Introduction to Python for AI.
This video will introduce this section of the course: Variables, Data Types, and Operators. By the end of this video you will have a clear understanding of the learning objectives for this section.
This video will help you gain an understanding of variables and assignment in Python. By the end of this video you will understand what variables are and how they get assigned a value in Python programming.
This video will cover the numeric data types that Python supports, which are integers and floats. By the end of this video you will understand the distinction between and integer and a floating point number and how to work with both of these numeric types in Python programming.
This video will go over the string variable type and some basic string operations that can be performed on strings. By the end of this video you will understand what strings are and how to work with them in Python programming.
This video will cover boolean logic and comparisons. By the end of this video you will understand how to work with boolean variables and compare the values of variables in your Python code.
This video will cover converting a variable of one type to another type. By the end of this video you will understand how to perform type conversion in Python programming.
This video will cover the different types of operators in Python programming: arithmetic, assignment, and logical. By the end of this video you will understand the role that each of these types of operators plays and how they work in Python.
This video will cover the some common built-in Python functions. By the end of this video you will know some of the most common functions used in Python programming.
This video will cover string formatting in Python. By the end of this video you will understand how to format strings, what f-Strings are, and how to work with them in your Python code.
In this video, we will put the skills that we learned together in a hands-on project as we build a simple calculator using Python code. By the end of this video you will have a working calculator program and hands-on experience working with the concepts that were taught in this section of the course.
In this video, we will review the quiz questions from the Data Types & Operators quiz and go over the answers and explanations to them. By the end of this video you will have a stronger understanding of the material taught in this section of the course.
In this video we will go over the answer and explanation to the coding exercise for the Variables, Data Types, and Operators section of the course.
In this video we will look at a recap of what we learned in this section of the course, Variables, Data Types, and Operators.
This video will introduce this section of the course: Control Flow and Functions in Python. By the end of this video you will understand the learning objectives for this section.
In this video we will get introduced to the concept of control flow statements in computer programming. By the end of this video you will understand the theory behind control flow statements and be ready to build hands-on experience in Python.
In this video we will learn about if, elif, and else statements in Python. By the end of this video you will understand what if, elif, and else statements are, the role that they play in computer programming, and how to implement them in Python.
In this video we will learn about using logical operators in conditions. By the end of this video you will understand what logical operators are, how to use them in conditions, and the role that they play in computer programming. You will also have hands-on experience working with them in Python.
In this video we will learn about for loops and how to implement them in Python. By the end of this video you will understand what for loops are, the role that they play in computer programming, and have hands-on experience working with them in Python programming.
In this video we will learn about while loops, along with the break and continue keywords. By the end of this video you will understand these concepts, the role that they play in computer programming, and have hands-on experience working with them in Python.
In this video we will write our first Python function. By the end of this video you will understand what functions are and how to create a function using Python code.
In this video we will learn about function parameters and return values. By the end of this video you will understand what function parameters and return values are and how to work with them in Python programming.
In this video we will learn about scope and the lifetime of variables. By the end of this video you will understand what these concepts mean and how they are using in Python programming.
In this hands-on project we will use the skills that we learned in this section of the course to create a Python program that classifies even and odd numbers. By the end of this video you will have another basic Python project that solidifies the foundational skills you've learned in this section.
In this video, we will review the quiz questions from the Control Flow and Functions in Python quiz and go over the answers and explanations to them. By the end of this video you will have a stronger understanding of the material taught in this section of the course.
In this video we will go over the answer and explanation to the coding exercise for the Control Flow and Functions in Python section of the course.
In this video we will look at a recap of what we learned in this section of the course, Control Flow and Functions in Python.
This video will introduce this section of the course: Collections. By the end of this video you will have a clear understanding of the learning objectives for this section.
In this video we will get introduced to Python lists. By the end of this video you will understand what lists are, how to work with them, and the role that they play in Python programming.
In this video we will learn about indexing, slicing, and modifying lists. By the end of this video you will understand how to perform these crucial operations in Python programming.
In this video we will learn how to loop through lists. By the end of this video you will understand how to loop through lists in Python code.
In this video we will learn about list methods and list comprehensions. By the end of this video you will understand what these are and the role that they play in Python programming.
In this video we will compare and contrast tuples and lists. By the end of this video you will understand the differences between tuples and lists and the pros and cons of each in Python programming.
In this video we will learn how to create and use dictionaries in Python. By the end of this video you will understand what dictionaries are and the role that they play in Python programming.
In this hands-on video we will create a Python program that functions as a grocery store inventory manager. By the end of this video you will have hands-on practice working with the concepts taught in this section of the course.
In this video, we will review the quiz questions from the Collections in Python quiz and go over the answers and explanations to them. By the end of this video you will have a stronger understanding of the material taught in this section of the course.
In this video we will go over the answer and explanation to the coding exercise for the Collections in Python section of the course.
In this video we will look at a recap of what we learned in this section of the course, Collections in Python.
This video will introduce this section of the course, Working with Files and CSV Data. By the end of this video you will understand the learning objectives for this section of the course.
In this video we will learn about reading and writing text files using Python. By the end of this video you will know how to write Python code that can read from, and write to, text files.
In this video we will learn how to work with file paths using Python. By the end of this video you will understand how to programmatically work with file paths using Python code.
In this video we will learn how to handle file exceptions in Python. By the end of this video you will understand how to handle file exceptions using Python code.
In this video we will get introduced to CSV files. By the end of this video you will understand what CSV files are and the role that they play in computer programming.
In this video we will learn how to read a CSV file using Python code. By the end of this video you will understand how to read CSVs using Python.
In this video we will learn how to write to a CSV file using Python code. By the end of this video you will understand how to write to a CSV using Python.
In this video we will use the skills we built up so far in this section to build a hands-on expense tracker program. By the end of this video you will have hands-on experience using the skills you learned to build an expense tracker using Python code.
In this video we will learn some best practices for File I/O in Python. By the end of this video you will understand the best practices for performing File I/O using Python code.
In this video we will use the skills we've built up to create another hands-on project, a program that saves and loads a contact list. By the end of this video you will have used your Python skills to create a program that saves and loads a content list.
In this video we will go over the answers and explanations to the quiz questions.
In this video we will go over the answer and explanation to the coding exercise.
In this video we will look at a recap of what we learned in this section of the course, Working with Files and CSV Data.
This video will introduce this section of the course, Object-Oriented Programming Basics. By the end of this video you will understand the learning objectives for this section of the course.
In this video we will learn what OOP is and why it matters. By the end of this video you will understand what object oriented programming is, the role that it plays in coding, and why it matters.
In this video we will learn how to create a class in Python. By the end of this video you will have created your first class using Python code.
In this video we will learn how to use the init() function to initialize an object in Python. By the end of this video you will understand the role that init() plays and how to make use of it in your Python programs.
In this video we will learn how to add attributes and methods to classes in Python. By the end of this video you will understand how attributes and methods can be added to a class.
In this video we will learn about instance and class variables. By the end of this video you will understand the difference between instance variables and class variables and how to work with both using Python code.
In this video we will learn about the basics of inheritance. By the end of this video you will understand what inheritance is and the basic concepts of inheritance in computer programming.
In this video we will learn about method overriding and the super() function. By the end of this video you will understand what method overriding is and how to use the super() function in your Python code.
In this hands-on video we will use the skills we've built up so far in this section to create a bank account class. By the end of this video you will have implemented a bank account class in Python.
In this video we will learn about object-oriented programming in an AI context. By the end of this video you will understand how the OOP concepts we have been learning about can be applied to AI development.
In this video we will go over the answers and explanations to the quiz questions from the quiz.
In this video we will go over the answer and explanation to the coding exercise for object-oriented programming basics.
This video will recap what we learned in this section of the course, Object-Oriented Programming Basics.
This video will introduce this section of the course, Using NumPy for Arrays and Math. By the end of this video you will understand the learning objectives for this section.
In this video we will get introduced to NumPy and why it matters in the context of AI development with Python. By the end of this video you will understand what NumPy is and the role that it plays in AI coding using the Python programming language.
In this video we will learn how to create arrays with NumPy. By the end of this video you will understand how to create arrays in NumPy, which is an essential skill for AI development with Python.
In this video we will learn about array indexing and slicing. By the end of this video you will understand how to perform array indexing and slicing using NumPy in Python.
In this video we will learn about broadcasting and vectorization. By the end of this video you will understand what broadcasting and vectorization are and how to implement them in your Python code using NumPy.
In this video we will learn about some of the functions we will commonly use in NumPy when building AI projects in Python. By the end of this video you will have an understanding fo some of the most commonly used NumPy functions.
In this video we will learn how to perform math operations on arrays using NumPy. By the end of this video you will understand how you can perform array math operations using NumPy.
In this video we will learn about reshaping and flattening arrays. By the end of this video you will understand how to perform reshaping and flattening of arrays using NumPy with Python for your AI development projects.
In this video we will learn how to use NumPy for random number generation. By the end of this video you will understand how to generate random numbers using NumPy, which is a common task you will perform when coding AI projects using Python code.
In this video we will learn about matrix multiplication. By the end of this video you will understand how to perform matrix multiplication using Python and NumPy, an essential skill when building AI programs using Python.
In this video we will use the skills we learned in this section to build a hands-on project, a dice roll simulator. By the end of this video you will have developed a dice roll simulator using NumPy and Python.
In this video we will go over the answers and explanations ot the quiz questions from the quiz.
In this video we will go over the answer and explanation to the coding exercise for array operations and filtering with NumPy.
This video will recap what we learned in this section of the course, Using NumPy for Arrays and Math.
This video will introduce this section of the course, Getting Started with Pandas for DataFrames. By the end of this video you will understand the learning objectives for this section of the course.
This video will introduce you to Pandas and DataFrames. By the end of this video you will understand what DataFrames in Pandas are and the role that they play in AI development using Python.
In this video we will learn how to create a DataFrame from scratch. By the end of this video you will understand how to create a DataFrame in Pandas.
In this video we will learn how to load CSV data into a DataFrame. By the end of this video you will understand how to load CSV data into a DataFrame using Pandas.
In this video we will learn how to view and inspect DataFrames. By the end of this video you will understand how to view and inspect DataFrames in Pandas.
In this video we will learn about filtering rows and selecting columns. By the end of this video you will understand how to filter rows and select columns using Pandas.
In this video we will learn how to add and remove columns using Pandas. By the end of this video you will understand how to use Pandas to add and remove columns from DataFrames.
In this video we will learn how to handle missing data in a DataFrame with Pandas. By the end of this video you will understand how to use Pandas to handle data missing from a DataFrame.
In this video we will learn about sorting and aggregating DataFrame data with Pandas. By the end of this video you will understand how to use Pandas to sort and aggregate data.
In this video we will use the skills we learned in this section to build a sales report generator hands-on. By the end of this video you will have a Sales Report Generator project you built hands-on using Pandas.
This video will go over the answers and explanations to the quiz questions for the quiz on Getting Started with Pandas for DataFrames.
This video will go over the answer and explanation to the coding exercise. By the end of this video you will have a better understanding of the material from this section of the course.
This video will recap what we learned in this section of the course, Getting Started with Pandas for DataFrames.
This video will introduce this section of the course, Intro to Data Visualization (Matplotlib + Seaborn). By the end of this video you will have an understanding of the learning objectives for this section of the course.
In this video we will learn about why data visualization is important. By the end of this video you will understand why data visualization is so critical with regards to AI development.
In this video we will get introduced to Matplotlib. By the end of this video you will understand what Matplotlib is and the role that it plays in the industry.
In this video we will learn about line plots and scatter plots. By the end of this video you will understand the usefulness of line plots and scatter plots and how to create them with Python code using Matplotlib.
In this video we will learn about bar charts and histograms. By the end of this video you will understand the usefulness of barcharts and histograms and how to create them with Python code using Matplotlib.
In this video we will learn how to customize the appearance of our graphs using Matplotlib. By the end of this video you will understand how to use Matplotlib to customize graph appearance.
In this video we will learn about subplots and grid layouts. By the end of this video you will understand what subplots and grid layouts are and how to implement them with Python code using Matplotlib.
In this video we will get introduced to Seaborn. By the end of this video you will understand what Seaborn is and why it is useful for data analysis tasks in Python.
In this video we will learn about heatmaps and pairplots. By the end of this video you will understand how to use Python with Seaborn to create heatmaps and pairplots for your data.
In this video we will get hands-on practice using the concepts taught in this section of the course for visualizing a COVID-19 dataset. By the end of this video you will have another hands-on project you can add to your portfolio of work.
In this video we will go over the answers and explanations to the quiz questions on Intro to Data Visualization (Matplotlib + Seaborn).
In this video we will go over the answer and explanation to the coding exercise on Intro to Data Visualization (Matplotlib + Seaborn).
In this video we will look at a recap of what we learned in this section of the course, Intro to Data Visualization (Matplotlib + Seaborn).
This course contains the use of artificial intelligence. Note from the Instructor: While I used AI to help structure my scripts to ensure no key concepts were missed and generated some images to provide clearer visual examples than traditional stock photos could offer, every lecture is personally taught, recorded, voiced by me to ensure you get the authentic, expert-led experience you expect. Feel free to watch the free preview videos to check out the quality and see my teaching style in action!
Are you ready to bridge the gap between AI theory and real-world implementation? Welcome to AI Programming in Python - Beginner to Expert, the ultimate, hands-on blueprint designed to take you from absolute scratch to deploying professional-grade Artificial Intelligence systems.
The biggest problem with most AI courses is that they give you plenty of math lectures but zero production experience. This course completely flips the script. You will build 50 distinct, hands-on AI projects, writing every line of code yourself, progressing linearly from foundational Python syntax to building bleeding-edge neural networks and generative models.
By the time you finish, you won’t just understand how AI works—you will have a massive, enterprise-grade portfolio to prove it.
Why Take This Course?
50 Real-World Projects: No boring slide-decks. You learn by doing, building everything from a basic data automation script to an advanced game-playing agent.
Zero Experience Required: We start from the absolute fundamentals. If you’ve never written a single line of code, our step-by-step, linear approach ensures you are never left behind.
Production & Deployment Focus: Knowing how to train a model in a notebook isn't enough anymore. You will learn how to containerize and ship your models into interactive web applications that anyone can use.
The Capstone Portfolio Piece: Together, we will build a full SaaS AI app end-to-end including the frontend, backend, authentication, and AI integration code.
A Comprehensive, Step-by-Step Curriculum
I have meticulously engineered this curriculum to scale seamlessly with your skillset:
Foundations of Data Science: Master data manipulation and automated cleaning using NumPy and Pandas, and build stunning statistical visuals with Matplotlib and Seaborn.
Classic Machine Learning from Scratch: Demystify the core math by hard-coding foundational algorithms like Linear Regression, K-Nearest Neighbors (KNN), Decision Trees, and Random Forests.
Advanced Architecture & Deep Learning: Dive deep into computer vision and sequential processing by building Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs/LSTMs) using industry-standard design.
The Bleeding Edge (Generative AI & NLP): Code Generative Adversarial Networks (GANs), implement custom Transformers, handle semantic text search with Word2Vec, and integrate pre-trained models via Hugging Face.
Reinforcement Learning & Games: Program Deep Q-Networks (DQNs) to train autonomous AI agents capable of mastering custom game environments.
Mangement & DevOps: Transition your models to the real world by utilizing Docker for containerization and building front-end user interfaces with Flask and Streamlit.
What You Get When You Enroll:
Full lifetime access to all HD video lectures.
Clean, production-ready downloadable source code for all 50 projects.
Practical assignments, quizzes, and coding challenges to lock in your skills.
Access to an active Q&A community for support whenever you get stuck.
Stop watching AI change the world from the sidelines. Scroll up, click "Enroll Now," and build the future—one project at a time.