Artificial Intelligence: Methods and Applications

Artificial Intelligence: Methods and Applications

Explore real-world AI applications, learn Deep Learning, and build AI projects using PyTorch, scikit-learn, and NumPy with hands-on, practical experiences.

  • Duration: 70 hours

  • Grades: 9-12

  • Level: Intermediate

About this course

Prepare to journey into the realm of Artificial Intelligence. In this course, you’ll explore the AI applications that shape our society. Dive into a select set of AI algorithms focusing on Deep Learning and get tons of hands-on experience building and training AI models using PyTorch, SciKit, and NumPy. Holistically learn about the AI application development process and build your own AI applications to share with friends and family.

What you'll learn

  • Identify a range of AI applications both in development and in use today

  • Discuss the broader societal impact of AI, including its ethical implications

  • Describe how AI algorithms are built

  • Build and train AI models using PyTorch, SciKit, and NumPy

How this course is structured

The course is divided into 6 units. Each unit has several lessons and a project. Within each lesson are instructional videos and practice activities. It will take no more than 60 minutes to complete each lesson.

Course Syllabus

Unit 1: The State of Artificial Intelligence Today
  • Lesson 1: How AI Looks Today

  • Lesson 2: Making Your First AI Application

  • Lesson 3: How AI is Used in Real Life

  • Lesson 4: Different AI Systems

  • Lesson 5: What AI Is and Is Not

Unit 2: Data: Food for Artificial Intelligence
  • Lesson 1: Exploratory Data Analysis

  • Lesson 2: Data Cleaning

  • Lesson 3: Prediction Expedition Part 1: Fitting a Model to Our Data

  • Lesson 4: Prediction Expedition Part 2: Evaluating Our Model

  • Lesson 5: The World of Data

Unit 3: Fantastic World of Neural Networks
  • Lesson 1: Fantastic World of Neural Networks

  • Lesson 2: Neural Networks Building Blocks

  • Lesson 3: Training 1

  • Lesson 4: Training 2

  • Lesson 5: Activation Functions and Hidden Layers

  • Lesson 6: Activation Functions and Hidden Layers: Coding

Unit 4: Computer Vision
  • Lesson 1: Exploring a Pictionary AI

  • Lesson 2: Different Methods to Build a Pictionary App using AI

  • Lesson 3: A Closer Look: Convolutions and Pooling

  • Lesson 4: Building Apps for Different Computer Vision Tasks

Unit 5: Natural Language Processing
  • Lesson 1: Building a Text-Based AI Game

  • Lesson 2: Representing Words

  • Lesson 3: Case Study on GPT-3

  • Lesson 4: Building Apps for Different Natural Language Processing Tasks

Unit 6: AI in Practice
  • Lesson 1: What Happens in the Lifetime of an AI Application?

  • Lesson 2: How Can Your AI Knowledge Be Useful?

  • Lesson 3: The World of Open Source Software

  • Lesson 4: Continuing Your AI Journey