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AdvancedAI & MLLive Data

AI-3: Application of Generative AI

Explore cutting-edge generative AI technologies and create innovative applications. Master prompt engineering, AI ethics, and build real-world project...

AdvancedAI & MLLive Data

AI-3: Application of Generative AI

Explore cutting-edge generative AI technologies and create innovative applications. Master prompt engineering, AI ethics, and build real-world project...

Lessons

9

Activities

9

Projects

4

Duration

24 sessions • 6 months

About This Course

Explore cutting-edge generative AI technologies and create innovative applications. Master prompt engineering, AI ethics, and build real-world projects using modern AI tools and platforms.

Prerequisites

Computer with internet access

This course consists of 24 structured sessions over 6 months. Each session includes lessons, activities, projects, and assessments to ensure comprehensive learning.

1

Introduction to Generative AI and Core Concepts

Generative AI fundamentals and applications

Lesson MaterialsActivitySubmission

Course Information

Course CodeAI3

Age Group13+ years old

Class SizeMax 8 students

Teacher Ratio1:8

Learning ModeHYBRID

Last Updated9/14/2025

Data SourceGitHub

Key Benefits

AI
Master AI through practical application

Basic computer skills

Curiosity and willingness to experiment

Skills You'll Learn

AIData

2

Data, Training, and Bias in AI

AI training data and bias mitigation

Lesson MaterialsActivitySubmission

3

Word Representations - Embeddings and Neural Networks

Text processing and neural networks

Lesson MaterialsActivitySubmission

4

Advanced Model Mechanisms: Attention and Output Generation

Attention mechanisms and transformers

Lesson MaterialsActivitySubmission

5

Interacting with Language Models and Prompt Engineering

Prompt engineering techniques

Lesson MaterialsActivitySubmission

6

Project One: Hugging Face Project

AI image and camera applications

Exit Ticket

7

Advanced Prompt Strategies and Retrieval Techniques

Advanced prompting and retrieval methods

Lesson MaterialsActivitySubmission

8

Evaluating Models: Model Cards and Fine-Tuning

Model evaluation and fine-tuning

Lesson MaterialsActivitySubmission

9

Quiz 1 + AI Coding with IDE

Assessment and AI-assisted coding

Lesson MaterialsActivitySubmission

10

Project 2: Spelling Bee (Part 1)

AI-powered spelling game development

Exit Ticket

11

Project 2: Spelling Bee (Part 2)

Enhanced features and adaptive difficulty

Exit Ticket

12

Project 2: Spelling Bee (Part 3)

Final implementation and deployment

Exit Ticket

13

Project 3: Smart Farm Assistant (Part 1)

Agricultural AI assistant development

Exit Ticket

14

Project 3: Smart Farm Assistant (Part 2)

Browser APIs and advanced features

Exit Ticket

15

Project 3: Smart Farm Assistant (Part 3)

Specialization and user experience

Exit Ticket

16

Project 3: Smart Farm Assistant (Part 4)

Deployment and presentation

Exit Ticket

17

Quiz 2

Assessment of applied AI knowledge

Activity

18

Vibe Coding with GitHub

Collaborative AI development

Lesson MaterialsActivitySubmission

19

Final Project (Part 1)

Creative AI application design

Exit Ticket

20

Final Project (Part 2)

Core features implementation

Exit Ticket

21

Final Project (Part 3)

Advanced features and optimization

Exit Ticket

22

Final Project (Part 4)

Testing and refinement

Exit Ticket

23

Final Project (Part 5)

Presentation and submission

Exit Ticket

24

Graduation

Portfolio review and course completion

Lesson MaterialsActivitySubmission

Data

Master Data through practical application

Learning Outcomes

Practical Skills
Build real-world applications and projects
Problem Solving
Develop computational thinking and problem-solving abilities

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