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AI Programming with Python

Nanodegree Program

Develop a strong foundation in Python programming for AI, utilizing tools like NumPy, pandas, and Matplotlib for data analysis and visualization. Learn how to use, build, and train machine learning models with popular Python libraries. Implement neural networks using PyTorch. Gain practical experience with deep learning frameworks by applying your skills through hands-on projects. Explore generative AI with Transformer neural networks, learn to build, train, and deploy them with PyTorch, and leverage pre-trained models for natural language processing tasks. Designed for individuals with basic programming experience, this program prepares you for advanced studies in AI and machine learning, equipping you with the skills to begin a career in AI programming.

Develop a strong foundation in Python programming for AI, utilizing tools like NumPy, pandas, and Matplotlib for data analysis and visualization. Learn how to use, build, and train machine learning models with popular Python libraries. Implement neural networks using PyTorch. Gain practical experience with deep learning frameworks by applying your skills through hands-on projects. Explore generative AI with Transformer neural networks, learn to build, train, and deploy them with PyTorch, and leverage pre-trained models for natural language processing tasks. Designed for individuals with basic programming experience, this program prepares you for advanced studies in AI and machine learning, equipping you with the skills to begin a career in AI programming.

  • Beginner

  • 3 months

  • Last Updated January 14, 2025

Skills you'll learn:

NumPymatplotlib

Prerequisites:

Elementary algebraBasic Python

Beginner

3 months

Last Updated January 14, 2025

Skills you'll learn:

NumPy • matplotlib • Vector visualization • Python data types

Prerequisites:

Elementary algebra • Basic Python

Skills that demand high salaries

Python developers, particularly those working in AI, are experiencing substantial demand with a projected job growth rate of 25% between 2021 and 2031.*

Salary info from Talent.com

AI Developer

  1. Low

    $102,474

  2. Average

    $130,662

  3. High

    $179,600

Skills that demand high salaries

AI Developer

Python developers, particularly those working in AI, are experiencing substantial demand with a projected job growth rate of 25% between 2021 and 2031.*

Salary Ranges

Low
$102,474
Average
$130,662
High
$179,600
Salary info from Talent.com

Courses In This Program

Course 1 2 hours

Introduction to AI Programming

Welcome to the AI programming with python Nanodegree Program! Come and explore the beautiful world of AI.

Lesson 1

Welcome to AI Programming with Python

Welcome to the AI Programming with Python Nanodegree program!

Lesson 2

Getting Help

You are starting a challenging but rewarding journey! Take 5 minutes to read how to get help with projects and content.

Lesson 3

Get Help with Your Account

What to do if you have questions about your account or general questions about the program.

Course 2 1 month

Introduction to Python for AI Programmers

Start coding with Python, drawing upon libraries and automation scripts to solve complex problems quickly.

Lesson 1

Why Python Programming for AI

Welcome to Introduction to Python! Here's an overview of the course.

Lesson 2

Using Python Data Types and Operators in AI Programming

Familiarize yourself with the building blocks of Python! Learn about data types and operators, built-in functions, type conversion, whitespace, and style guidelines.

Lesson 3

Python Data Structures in AI Programming

Use data structures to order and group different data types together! Learn about the types of data structures in Python, along with more useful built-in functions and operators.

Lesson 4

Using Control Flow in AI Programming

Build logic into your code with control flow tools! Learn about conditional statements, repeating code with loops and useful built-in functions, and list comprehensions.

Lesson 5

Using Python Functions in AI Programming

Learn how to use functions to improve and reuse your code! Learn about functions, variable scope, documentation, lambda expressions, iterators, and generators.

Lesson 6

Python Scripting for AI Programming

Set up your own programming environment to write and run Python scripts locally! Learn good scripting practices, interact with different inputs, and discover awesome tools.

Lesson 7

Introduction to Object-Oriented Python for AI Programming

Learn the basics of object-oriented programming so that you can build your own Python package.

Lesson 8 • Project

Use a Pre-trained Image Classifier to Identify Dog Breeds

In this project, you will use Python code and a created image classifier to identify dog breeds.

Course 3 2 weeks

Numpy, Pandas, Matplotlib

Let's focus on library packages for Python, such as : Numpy (which adds support for large data), Pandas (which is used for data manipulation and analysis) And Matplotlib (which is used for data visualization).

Lesson 1

Anaconda

Anaconda is a package and environment manager built specifically for data. Learn how to use Anaconda to improve your data analysis workflow.

Lesson 2

Jupyter Notebooks

Jupyter Notebooks are a great tool for getting started with writing python code. Though in production you often will write code in scripts, notebooks are wonderful for sharing insights and data viz!

Lesson 3

NumPy

Learn the basics of NumPy and how to use it to create and manipulate arrays.

Lesson 4

Pandas

Learn the basics of Pandas Series and DataFrames and how to use them to load and process data.

Lesson 5

Matplotlib and Seaborn Part 1

Learn how to use matplotlib and seaborn to visualize your data. In this lesson, you will learn how to create visualizations to depict the distributions of single variables.

Lesson 6

Matplotlib and Seaborn Part 2

In this lesson, you will use matplotlib and seaborn to create visualizations to depict the relationships between two variables.

Course 4 2 weeks

Linear Algebra Essentials

Learn the basics of the beautiful world of Linear Algebra and why it is such an important mathematical tool in the world of AI.

Lesson 1

Introduction

Take a sneak peek into the beautiful world of Linear Algebra and learn why it is such an important mathematical tool.

Lesson 2

Vectors

Learn about vectors, the basic building block of Linear Algebra.

Lesson 3

Linear Combination

Learn how to scale and add vectors and how to visualize the process.

Lesson 4

Linear Transformation and Matrices

What is a linear transformation and how is it directly related to matrices? Learn how to apply the math and visualize the concept.

Lesson 5

Vectors Lab

Learn how to graph 2D vectors.

Lesson 6

Linear Combination Lab

Learn how to computationally determine a vector's span and solve a simple system of equations.

Lesson 7

Linear Mapping Lab

Learn how to solve some problems computationally using vectors and matrices.

Lesson 8

Linear Algebra in Neural Networks

Take a peek into the world of Neural Networks and see how it related directly to Linear Algebra!

Course 5 3 hours

Calculus Essentials

Covers foundational topics in CalculusLearn the foundations of calculus to understand how to train a neural network: plotting, derivatives, the chain rule, and more. See how these mathematical skills visually come to life with a neural network example.

Lesson 1

Calculus

Lesson 2

Calculus in Neural Networks

Course 6 3 weeks

Neural Networks - AI Programming with Python

This course on neural networks explains how algorithms inspired by the human brain operate and puts to use those concepts when designing neural networks to solve particular problems.

Lesson 1

Welcome to Neural Networks

Lesson 2

Introduction to Neural Networks

In this lesson, Luis will give you solid foundations on deep learning and neural networks. You'll also implement gradient descent and backpropagation in Python right here in the classroom.

Lesson 3

Implementing Gradient Descent

Mat will introduce you to a different error function and guide you through implementing gradient descent using numpy matrix multiplication.

Lesson 4

Training Neural Networks

Now that you know what neural networks are, in this lesson you will learn several techniques to improve their training.

Lesson 5

Deep Learning with PyTorch

Learn how to use PyTorch for building deep learning models.

Course 7 4 hours

Programming Transformer Neural Networks with PyTorch

This course will guide you through the essential concepts of Transformer Neural Networks and their implementation using PyTorch. Starting with an introduction to Transformers, you will learn to build and train Transformer models from scratch. Additionally, you will explore the advantages of using pre-trained Transformer models and how to leverage them effectively in your projects. By the end of this course, you will have a solid foundation in programming Transformer Neural Networks with PyTorch.

Lesson 1

Introduction to Transformer Neural Networks

Explore Transformer neural networks, their architecture, and applications like ChatGPT. Delve into NLP basics, tokenization, and model training using PyTorch for AI advancements.

Lesson 2

Building Transformer Neural Networks with PyTorch

Learn to build a Transformer model with PyTorch, covering tokenization, embeddings, multi-head attention, training, and text generation for NLP tasks.

Lesson 3

Using Pre-Trained Transformers

Master the use of pre-trained transformers, including their training, fine-tuning, limitations, and applying them to NLP tasks like text generation and QA.

Course 8 4 hours

Create Your Own Image Classifier

In the second and final project for this course, you'll build a state-of-the-art image classification application.

Lesson 1 • Project

Create Your Own Image Classifier

In this project, you'll build a Python application that can train an image classifier on a dataset, then predict new images using the trained model.

Course 9 5 minutes

Next Steps!

Congratulations!!!!! You finished your first nanodegree in the School of AI! What are the next steps?

Lesson 1

How Do I Continue From Here?

(Optional) Course 10 1 week

Git and GitHub

Programmers use version control software to manage changes to software projects large and small. In these lessons you will learn to keep track of changes to your code using the Git version control software, and collaborate with other programmers using GitHub.

Lesson 1

What is Version Control

Version control is an incredibly important part of a professional programmer's life. In this lesson, you'll learn about the benefits of version control and install the version control tool Git!

Lesson 2

Create a Git Repo

Now that you've learned the benefits of Version Control and gotten Git installed, it's time you learn how to create a repository.

Lesson 3

Commits, Tags, Conflicts

Knowing how to review an existing Git repository's history of commits is extremely important. You'll learn how to do just that in this lesson.

Lesson 4

Remotes and Developer Repos

In this lesson, you'll learn how to fork another developer's project. Collaborating with other developers can be a tricky process, so you'll learn how to contribute to a public project.

Lesson 5

Writing READMEs for Repos

Learn the importance of well documented code and see how to craft meaningful READMEs.

(Optional) Course 11 12 minutes

Intro to Machine Learning

Lesson 1

Intro

An introduction to what you'll learn in this course!

Lesson 2

Linear Regression

Learn how effective linear regression algorithms are in predicting numerical data

Lesson 3

Logistic Regression

Learn about one of the most basic forms of regression modeling - logistic regression

Lesson 4

Decision Trees

Learn how decision trees are a structure for decision-making where each decision leads to a set of consequences or additional decisions.

Lesson 5

Naive Bayes

Learn how powerful Naive Bayesian Algorithms are for creating classifiers for incoming labeled data.

Lesson 6

Support Vector Machines

Learn about how support vector machines can be effective models for classification.

Lesson 7

Ensemble Methods

Learn about bagging and boosting, two common ensemble methods for improving the accuracy of supervised learning approaches.

Lesson 8

Outro

Let's recap and wrap up what we've learned.

(Optional) Course 12 15 minutes

Learning Rate

Still curious about the learning rate, how sensitive it is and what role it plays in the accuracy of the training process?

Lesson 1

Visualizing The Importance Of The Learning Rate

Visualizing the importance of the learning rate.

Taught By The Best

Photo of Mat Leonard

Mat Leonard

Content Developer

Mat is a former physicist, research neuroscientist, and data scientist. He did his PhD and Postdoctoral Fellowship at the University of California, Berkeley.

Photo of Andrew Paster

Andrew Paster

Instructor

Andrew has an engineering degree from Yale, and has used his data science skills to build a jewelry business from the ground up. He has additionally created courses for Udacity's Self-Driving Car Engineer Nanodegree program.

Photo of Jennifer Staab

Jennifer Staab

Instructor

Jennifer has a PhD in Computer Science and a Masters in Biostatistics; she was a professor at Florida Polytechnic University. She previously worked at RTI International and United Therapeutics as a statistician and computer scientist.

Photo of Luis Serrano

Luis Serrano

Instructor

Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.

Photo of Juan Delgado

Juan Delgado

Content Developer

Juan is a computational physicist with a Masters in Astronomy. He is finishing his PhD in Biophysics. He previously worked at NASA developing space instruments and writing software to analyze large amounts of scientific data using machine learning techniques.

Photo of Juno Lee

Juno Lee

Instructor

As a data scientist at Looplist, Juno built neural networks to analyze and categorize product images, a recommendation system to personalize shopping experiences for each user, and tools to generate insight into user behavior.

Photo of Mike Yi

Mike Yi

Data Analyst Instructor

Mike is a content developer with a multidisciplinary academic background, including math, statistics, physics, and psychology. Previously, he worked on Udacity's Data Analyst Nanodegree program as a support lead.

Photo of Grant Sanderson

Grant Sanderson

Instructor

Grant Sanderson is the creator of the YouTube channel 3Blue1Brown, which is devoted to teaching math visually, using a custom-built animation tool. He was previously a content creator for Khan Academy.

Photo of Ortal Arel

Ortal Arel

Curriculum Lead

Ortal Arel has a PhD in Computer Engineering, and has been a professor and researcher in the field of applied cryptography. She has worked on design and analysis of intelligent algorithms for high-speed custom digital architectures.

Photo of Ivan Mushketyk

Ivan Mushketyk

Software Engineer

Experienced software engineer with over ten years in the field. Worked at at AWS and Stripe, as well as several start-ups. An experienced online instructor, creating courses on AI, data engineering, and AWS. Passionate about leveraging technology to solve complex problems and sharing knowledge with others.

Student Reviews

Average Rating: 4.7 Stars

624 Reviews

Saif A.

February 27, 2023

That project is more than excellent; it provides a solid foundation for deep learning. But the content is so large that you need to take care of each part to get the maximum benefit. And the Udacity team is extremely helpful. 

Xavier A.

November 7, 2022

good review

VIVEK B.

October 29, 2022

Excellent program.

Muhammad Z.

October 9, 2022

It was a wonderful experience working in a real-time environment. The course plan was perfectly aligned with my study and future goals.

Abdul R.

September 23, 2022

very helpful program

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About AI Programming with Python

Our AI Programming with Python Nanodegree program offers a beginner-friendly exploration into Python AI programming. This course covers Python, NumPy, Pandas, Matplotlib, PyTorch, and Linear Algebra, laying a solid foundation for building neural networks. You'll engage in practical projects like vector visualization and Python data types, gaining real-world experience. Taught by experts like Mat Leonard and Luis Serrano, this Python AI course combines hands-on learning with industry insights, making it ideal for those starting in AI. At Udacity, we're dedicated to your success. With our approach, you don't just learn – you apply. Our practical projects, based on real-world scenarios, ensure that you gain experience and retain knowledge, enabling you to immediately apply your new skills. Embrace this opportunity to kickstart your career in AI with Udacity, where innovation and success are part of our DNA.

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