人工智慧的基本數學和編碼基礎
高中生加速人工智慧基礎：基本概念，無需繁瑣的數學和程式設計。學生將學習核心人工智慧概念、實用編碼和實際應用，為未來打下堅實的基礎。
包含什麼
10 現場會議
10 上課時間作業
每週 1-2 小時. - Three comprehensive assignments integrating mathematics and computer science concepts - Designed to offer hands-on experience and reinforce understanding of key ideas - Students are encouraged to document their problem-solving process完成證書
Upon finishing the course, students will receive a certificate acknowledging their acquisition of foundational AI knowledge and their readiness for further study in the field.我們無法翻譯此文，請刷新頁面並再試一次。
課堂經歷
英語程度 - A1
美國 6 - 9 年級
Beginner 等級
Class Description As an experienced leader in silicon valley and instructors at universities, my course design is to provide a comprehensive AI foundation covering mathematics and computer science for young students. We aim to spark students' interest in AI, preparing them to be either users or designers of AI in the near future. This course is designed to provide long-term benefits, whether students choose to use AI or study it further. We hope this course will help students develop a strong foundation and lasting interest in AI, benefiting them in their future endeavors, whether as AI users or designers. Content: In this course, we will teach students important technical knowledge about AI, including: - Calculus and Linear Algebra (8th to 9th grade level) - Programming (8th to 9th grade level) - Probability and Statistics (9th to 10th grade level) - Data-related concepts Course Philosophy: - Focus on essential AI knowledge - Skip extensive math and computer science courses - Teach only the most crucial content for AI understanding Course structure: - 5 weeks, 10 sessions total - Each session focuses on one topic (10 topics in total) - Topics are relatively independent, allowing flexibility if a student needs more time to review for one class Teaching approach: - Encourage students to consider relationships between topics - Assign homework and offer a Final Certificate - Provide personalized plans and supplementary materials - Offer additional guidance for students interested in deeper learning Classroom interaction: - Encourage questions during class - Share class slides after each session - Promote independent thinking through homework assignments
學習目標
Students will learn the essential AI algorithms with up-to-date examples.Students will learn core concepts in mathematics and computer science for understanding AI.
教學大綱
4 單位
10 課程
超過 5 週單位 1: Overview of AI
課 1:
Current Key AI Models
Description: Introduction to the most influential AI models, their applications, and impact on various industries.
Learning objectives:
- Understand the basic architecture of popular AI models
- Identify key applications of these models in real-world scenarios
- Discuss the ethical implications of advanced AI models 60 分鐘線上直播課
課 2:
Roadmap - Learning Foundations of AI
Description: Overview of the essential skills and knowledge required to understand and work with AI.
Learning objectives:
- Identify the key areas of study in AI (math, programming, data science)
- Understand the interconnections between different AI foundations 60 分鐘線上直播課
單位 2: Programming Fundamentals
課 3:
Introduction to Python
Description: Basic Python programming concepts and syntax.
Learning objectives:
- Understand Python's basic data types and structures
- Write simple Python programs using control structures
- Use Python's built-in functions and create custom functions 60 分鐘線上直播課
課 4:
Advanced Programming Concepts
Description: More complex Python concepts relevant to AI and data analysis.
Learning objectives:
- Understand object-oriented programming principles
- Work with Python libraries commonly used in AI (e.g., NumPy)
- Implement basic algorithms in Python 60 分鐘線上直播課
其他詳情
父母的引導和規範
Parental or guardian supervision is required for any use of AI tools (e.g., ChatGPT, Claude, Midjourney, DALL-E) during this class. Students must adhere to the age restrictions and terms of service for each AI platform and for Outschool. It is important for students to understand the potential biases and limitations of AI-generated content, and they should avoid sharing any personal information with these tools. Additionally, all AI-assisted work must be properly attributed in assignments to maintain transparency and academic integrity.
先決條件
A basic understanding of algebra, along with a curious, creative, and engaged mindset. We want students who are eager to explore how AI and new technologies work. Throughout the course, we will share real examples!
教學語言
英語 （等級： A1）
已加入 December, 2023
教師專業知識和證書
3 個學位
碩士 在 科學 從 University of Washington
學士學位 在 數學 從 University of Minnesota
學士學位 在 科學 從 University of Minnesota
I have 11 years of teaching experience in various subjects related to data science, analytics, and statistics, as well as experience guiding students through strategic decision-making processes. My teaching background includes but not limit to:
- Data Streaming (MSDS 682) - Fall 2023, University of San Francisco Format: In-Person, Graduate level Role: Lead/Primary Instructor Class size: 9 students
- Connecting Data Analytics with Managerial Success (BUS 36) - Summer 2024, Stanford Continuing Studies Format: In-Person, Extension Studies Role: Lead/Primary Instructor Class size: 25 students
- Non-parametric Modeling (STAT 527) - Spring 2014, University of Washington Format: In-Person, Graduate level Role: Teaching Assistant Class size: 50 students
- Categorical Data Analysis (STAT 536) - Spring 2013, University of Washington Format: In-Person, Graduate level Role: Teaching Assistant Class size: 50 students
評論
現場團體課程
US$30
每週或US$150 用於 10 課程每週2次，共 5 週
60 分鐘
即時視訊會議
年齡: 13-18
6-12 每班學員人數
