Foundations of Artificial Intelligence
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Foundations of Artificial Intelligence

★ Premium · 📖 71 lessons

Foundations of Artificial Intelligence provides a practical, beginner-friendly introduction to the technologies and concepts driving modern AI. The course explores how artificial intelligence works, including machine learning, neural networks, deep learning, natural language processing, generative AI, large language models, and other essential topics. Students will also learn how AI systems are trained, how they generate predictions and content, and how organizations are applying AI to solve real-world problems. Designed for students, developers, and IT professionals, the course combines clear explanations with hands-on learning using Python and open-source AI tools. Students will gain practical experience working with AI while developing a solid foundation for more advanced study in machine learning, generative AI, and AI application development. No previous AI experience is required, making this an excellent starting point for anyone interested in understanding and working with artificial intelligence.

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Course Content

71 lessons
Module 1: Introduction to Artificial Intelligence 6 items
1.1
What Is Artificial Intelligence?
Video
1.2
How AI Systems Actually Work
Video
1.3
The Python AI Toolkit
Video
1.4
Setting Up Your AI Lab Environment
Lab
1.5
Exploring Your First Dataset
Lab
1.6
Introduction to Artificial Intelligence Quiz
Quiz
Module 2: Python Foundations for AI 6 items
2.1
Working with NumPy Arrays
Video
2.2
Data Wrangling with pandas
Video
2.3
Visualizing Data with Matplotlib
Video
2.4
Manipulating Data with NumPy
Lab
2.5
Cleaning a Real-World Dataset with pandas
Lab
2.6
Python Foundations for AI Quiz
Quiz
Module 3: Understanding Data for AI 6 items
3.1
What Makes Good Training Data
Video
3.2
Preparing Data for Machine Learning
Video
3.3
Where AI Gets Its Data
Video
3.4
Preparing a Dataset for Modeling
Lab
3.5
Detecting Bias in a Dataset
Lab
3.6
Understanding Data for AI Quiz
Quiz
Module 4: Machine Learning Fundamentals 6 items
4.1
What Is Machine Learning?
Video
4.2
Your First Model with scikit-learn
Video
4.3
Evaluating Model Performance
Video
4.4
Training Your First Model
Lab
4.5
Evaluating Model Quality
Lab
4.6
Machine Learning Fundamentals Quiz
Quiz
Module 5: Classification with scikit-learn 6 items
5.1
Classification Algorithms Overview
Video
5.2
Building and Tuning Classifiers
Video
5.3
Real-World Classification Problems
Video
5.4
Building a Classifier
Lab
5.5
Tuning a Classification Model
Lab
5.6
Classification with scikit-learn Quiz
Quiz
Module 6: Regression and Model Evaluation 6 items
6.1
What Is Regression?
Video
6.2
Evaluating Regression Models
Video
6.3
Beyond Linear Regression
Video
6.4
Building a Regression Model
Lab
6.5
Improving a Regression Model
Lab
6.6
Regression and Model Evaluation Quiz
Quiz
Module 7: Unsupervised Learning 6 items
7.1
Finding Structure Without Labels
Video
7.2
Clustering with K-Means
Video
7.3
Dimensionality Reduction
Video
7.4
Clustering Data with K-Means
Lab
7.5
Reducing Dimensions with PCA
Lab
7.6
Unsupervised Learning Quiz
Quiz
Module 8: Introduction to Neural Networks 6 items
8.1
How Neural Networks Work
Video
8.2
How Neural Networks Learn
Video
8.3
Building a Simple Neural Network
Video
8.4
Building a Neural Network from Scratch
Lab
8.5
Training a Neural Network with scikit-learn
Lab
8.6
Introduction to Neural Networks Quiz
Quiz
Module 9: Deep Learning and Computer Vision Basics 6 items
9.1
What Makes Learning "Deep"
Video
9.2
How Computers "See" Images
Video
9.3
Computer Vision Applications
Video
9.4
Working with Image Data
Lab
9.5
Classifying Images
Lab
9.6
Deep Learning and Computer Vision Basics Quiz
Quiz
Module 10: Natural Language Processing Basics 6 items
10.1
How Computers Process Language
Video
10.2
Text Classification and Sentiment
Video
10.3
From Word Vectors to Language Models
Video
10.4
Processing Text Data
Lab
10.5
Building a Sentiment Classifier
Lab
10.6
Natural Language Processing Basics Quiz
Quiz
Module 11: Large Language Models and Prompt Engineering 6 items
11.1
What Are Large Language Models?
Video
11.2
Prompt Engineering Fundamentals
Video
11.3
Building with LLM APIs
Video
11.4
Practicing Prompt Engineering
Lab
11.5
Calling an LLM from Python
Lab
11.6
Large Language Models and Prompt Engineering Quiz
Quiz
Module 12: AI Ethics, Limitations, and Final Project 5 items
12.1
Responsible AI
Video
12.2
The Limits of Today's AI
Video
12.3
Final Project and Where to Go Next
Video
12.4
Final AI Project
Lab
12.5
AI Ethics, Limitations, and Final Project Quiz
Quiz