Lesson List

Welcome to AI Programming with Python

Start using AI techniques and developing skills related to programming, linear algebra, and neural networks.

Why Python Programming

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

Data Types and Operators

Control Flow

Functions

Scripting

Lab Classifying Images

In this project, learners will be testing their newly-acquired Python coding skills by using a trained image classifier. They will need to use the trained neural network to classify images of dogs (by breeds) and compare the output with the known dog breed classification. Learners will have a chance to build their own functions, use command line arguments, test the runtime of the code, create a dictionary of lists, and more.

NumPy

Learn how to use all the key tools for working with data in Python: Jupyter Notebooks, NumPy, Anaconda, Pandas, and Matplotlib.

Pandas

Matplotlib and Seaborn Part 1

Learn how to use Matplotlib to choose appropriate plots for one and two variables based on the types of data you have.

Matplotlib and Seaborn Part 2

Introduction

Learn the foundational math needed for AI success—vectors, linear transformations, and matrices—as well as the linear algebra behind neural networks.

Vectors

Linear Combination

Linear Transformation and Matrices

Vectors Lab

Linear Combination Lab

Linear Mapping Lab

Linear Algebra in Neural Networks

Introduction to Neural Networks

Gain a solid foundation in the latest trends in AI: neural networks, deep learning, and PyTorch.

Implementing Gradient Descent

Training Neural Networks

Deep Learning with PyTorch

Create Your Own Image Classifier

How Do I Continue From Here

Go to course home
06. Lesson Plan

Lesson Plan

We offers the AI Programming with Python Nanodegree to a wide range of students. As such, our students come from various backgrounds. Some of you will have had previous coding experience and some will have had none. For this reason we offer two suggested lesson plans. One lesson plan will apply to those of you with previous coding experience. The other will apply to those of you who feel they need more time to build coding confidence.

These suggested lesson plans will give you an idea of how to partition your time. You are of course encouraged to make your own judgement and enjoy the content at your own specific pace.

 

 

Extracurricular section

Notice that we provided you with an extracurricular section.
In this section you will find additional useful lessons.

for example:

  • If you are completely new to Python, you will find our Intro to Python (Turtles and Code) lesson helpful.
  • If you have extra time and want to learn more about Machine Learning, you will find our Intro to Machine Learning.

Throughout the lessons, we will point you to additional extracurricular material when relevant.

 

 

 

 

Suggested Lesson Plan: Students Without Extensive Coding Experience

Module 1: Introduction to AI Programming with Python

At your leisure

 

 

Module 2: Intro to Python

  • Lessons (Why Python Programming, Data Types and Operators, Control Flow, Functions and Scripting)

    • 1.5 weeks

    • Project_1 (using an Image classifier)

    • 1.5 week

 

 

Module 3: Numpy, Pandas, Matplotlib

  • Anaconda, Jupyter Notebooks

    • 1 week

  • Numpy, Pandas, Matplotib

    • 1.5 weeks
 

 

Module 4: Linear Algebra Essentials

  • Lessons (Introduction, Vectors, Linear Combination, Linear Transformation and Matrices and Linear Algebra in Neural Networks )

    • 0.5 week

  • Labs (Vectors, Linear Combination and Linear Mapping)

    • 0.5 week
 

 

Module 5: Neural Networks

  • Lessons (Introduction to Neural Networks, Implementing Gradient Descent and Training Neural Networks)

    • 1 week

  • Lesson (Deep Learning with PyTorch)

    • 1 week
 

 

Module 6: Image Classifier Project

  • 2.5 weeks
 

 

Notice that in total this sums up to 11.5 weeks. Use the extra time as you please.

 

 

 

 

Suggested Lesson Plan: Students With Extensive Coding Experience

Module 1: Introduction to AI Programming with Python

At your leisure

 

 

Module 2: Intro to Python

  • Lessons (Why Python Programming, Data Types and Operators, Control Flow, Functions and Scripting)

    • 1 weeks

    • Project_1 (using an Image classifier)

    • 1 week

 

 

Module 3: Numpy, Pandas, Matplotlib

  • Anaconda, Jupyter Notebooks

    • 1 week

  • Numpy, Pandas, Matplotlib

    • 1 week
 

 

Module 4: Linear Algebra Essentials

  • Lessons (Introduction, Vectors, Linear Combination, Linear Transformation and Matrices and Linear Algebra in Neural Networks )

    • 0.5 week

  • Labs (Vectors, Linear Combination and Linear Mapping)

    • 0.5 week
 

 

Module 5: Neural Networks

  • Lessons (Introduction to Neural Networks, Implementing Gradient Descent and Training Neural Networks)

    • 1 week

  • Lesson (Deep Learning with PyTorch)

    • 0.5 week
 

 

Module 6: Image Classifier Project

  • 1.5 weeks
 

 

(Notice that you have 3.5 weeks of extra time if you choose to use it).

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