Machine Learning & AI with Python

Learn how to create AI with machine learning using Python.

Course Overview Start First Lesson

Course Overview

Machine-Learning/AI with Python is the second course of a two weeks series that introduces high school and adult students to machine-learning programming with Python. This course assumes students have a solid grasp of intermediate-to-advanced Python, as dataset analysis and machine-learning projects are introduced in the first two days. As all machine-learning models must be trained, trimmed, and corrected using clean and complete datasets, so this course begins with an introduction to data science, data classification, data analytics, and dataset compilation. A series of machine-learning/AI algorithms and techniques such as Random Forest, SVM, SVP, Naïve Bayes, nearest neighbor variants, and TensorFlow will be presented through discussions and projects. Moreover, a description and related projects will be assigned using a series of related open-source modules and libraries, such as Scikit-learn, NumPy, Matplotlib, Pandas, Pygame, Keras, NLTK, BeautifulSoup, and VADER. This course culminates in a capstone project to build and customize a neural-network machine-learning powered arcade space shooter.

Day 1

Morning

In the exploring data session, you will:

Afternoon

In the data preparation session, you will:

Day 2

Morning

In the Random Forest model session, you will:

Afternoon

In the Support Vector Machines session, you will:

Day 3

Morning

In the Natual Language Processing session, you will:

Afternoon

In the Advanced NLP session, you will:

Day 4

Morning

In the Snake Game Setup session, you will:

Afternoon

In the Snake Game AI session, you will:

Day 5

Morning

In the Neuroblast Game Setup session, you will:

Afternoon

In the Neuroblast Game AI session, you will:

Start First Lesson