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US$175

weekly
or US$350 for 10 classes
班級

人工智慧與機器學習夏令營簡介 |面向青少年的 AI、ML 和 Python

新班級
年齡 12-17
現場團體課程
這是人工智慧和機器學習的介紹,向學習者介紹這些領域。學生將使用真實的機器學習工具、Python 程式碼和真實資料完成四個真實的機器學習 Python 專案。
平均評分:
4.9
評論數量:
(830 評論)
明星教育家
熱門課程

即時視訊會議
每週5次,共 2 週
6-14 名學習者(每班)
60 分鐘

包含什麼

10 現場會議
10 上課時間
作業
每週 2-4 小時. There will be review questions and practice assignments each day, taking approx. 1 to 2 hours. Learners are also strongly encouraged to learn on their own outside of class time. Possible solutions are posted to the Outschool classroom for students to check their work.
項目
3-6 整堂課
完成證書
Students will receive a certificate of completion at the end of the class. Students must attend at least 8 classes to receive the certificate.
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課堂經歷

英語程度 - B2+
美國 8 - 11 年級
Beginner 等級
This comprehensive course introduces high school students to the fundamentals of artificial intelligence and machine learning through hands-on Python coding. Students will work with professional-grade tools like NumPy, Pandas, and Scikit-learn to complete four real-world machine learning projects, including image classification, data analysis, and neural networks. The curriculum balances theoretical concepts with practical application, guiding students through the complete machine learning workflow from data collection to model improvement.

This course is designed for students who already have basic programming experience in any language. Throughout the 2-week summer program, students will build increasingly sophisticated AI models while developing critical thinking skills. The collaborative learning environment encourages peer feedback and code sharing.

Projects Included

Cat vs. Dog Decision Tree Classification
Height vs. Weight Data Science Exploration
Hours Studied Linear Regression
Iris Dataset Analysis Nearest Neighbor Algorithm
Handwritten Digit Recognition with Neural Networks

What's Included

2 weeks of comprehensive instruction
Professional-grade tools (Google Colab, NumPy, Pandas, Matplotlib, Scikit-learn)
Hands-on coding experience with real datasets
Daily Practice Questions and Coding Challenges
Introduction to supervised and unsupervised learning techniques
Collaborative learning environment with instructor feedback
Foundation for AI/ML career exploration

Ready to build the future with AI?

Join us for this hands-on course where you'll create real machine learning projects using professional tools. Perfect for high school students with basic programming knowledge who want to explore one of today's most exciting and in-demand fields!

****Important Note for Adults*****

This isn't a beginner coding course. Learners should already be comfortable with basic programming concepts in any language (Python, Java, JavaScript, C/C++, or Swift). If you're new to coding, check out our beginner Python courses first - they'll give you the foundation you need to succeed here.

學習目標

Students will develop proficiency in essential Python libraries for machine learning, including scikit-learn, NumPy, and Pandas. They will demonstrate their understanding by building and evaluating machine learning models through hands-on coding.
Students will master core types of machine learning including supervised and unsupervised learning, along with key algorithms like decision trees and neural networks. They will demonstrate this knowledge by choosing appropriate algorithms.

教學大綱

10 課程
超過 2 週
課 1:
Foundations of AI
 Dive into the fascinating world of artificial intelligence! Today, we'll explore what makes something "intelligent," discover how AI is already transforming our daily lives, and distinguish between related fields like machine learning and data science. You'll set up your Google Colab environment and take your first steps toward building real AI systems. 
60 分鐘線上直播課
課 2:
Machine Learning Basics & First Project
 Get hands-on with machine learning fundamentals as we begin our first exciting project—teaching an AI to distinguish between cats and dogs! You'll learn essential Python libraries like NumPy and Pandas that data scientists use daily, while setting up the foundation for your image classification project. 
60 分鐘線上直播課
課 3:
Project Implementation & ML Process
 Complete your first AI project as you train a model to classify images! We'll dive deeper into supervised and unsupervised learning approaches, explore the end-to-end machine learning process, and celebrate your first functioning AI model. You'll understand not just how to build it, but why each step matters. 
60 分鐘線上直播課
課 4:
Python for Data Science
 Sharpen your data science toolkit with powerful Python libraries! Today focuses on practical coding skills that will elevate your machine learning projects. You'll learn to manipulate data with NumPy, organize information with Pandas, and create compelling visualizations with Matplotlib—essential skills for any aspiring AI engineer. 
60 分鐘線上直播課

其他詳情

父母的引導和規範
Learners will use Google Colab during this class and will need a Google Account to access Colab. Students will also utilize the following Python libraries, including Scikit-learn, NumPy, Matplotlib, Seaborn, and Pandas throughout the class. The documentation (instructions) for these libraries will be used as a reference throughout the course. UC Irvine ML Repository will be used for practice datasets throughout the class. Python.org will be used as Python reference sources throughout the class. ***Intro to AI and ML Class Prerequisites **** This isn't a beginner coding course. Learners should already be comfortable with basic programming concepts in any language (Python, Java, JavaScript, C/C++, or Swift). If you're new to coding, check out our beginner Python courses first - they'll give you the foundation you need to succeed here.
先決條件
This isn't a beginner coding course. Learners should already be comfortable with basic programming concepts in any language (Python, Java, JavaScript, C/C++, or Swift). If students new to coding, check out our beginner Python courses first.
供應清單
Students will use Google Colab during this class and will need a Google Account to access Colab. Colab is a browser-based code editor and there are no minimum hardware requirements for student computers. Students will need a reliable Windows, Mac, or Linux laptop or desktop for this class.
外部資源

認識老師

已加入 April, 2020
4.9
830評論
明星教育家
熱門課程
教師檔案
教師專業知識和證書
學士學位 由 Mount St. Mary's University
Over 5,000 students from nearly 100 countries across a variety of platforms have started coding in one of my classes. I offer classes covering the foundations of Python and AI.  Before teaching, I worked as a software developer for nearly 10 years. I've worked for organizations including Apple, Dell, and Best Buy. I believe the best way to learn is by doing and all my classes are based around hands-on projects that progressively build in difficulty.  I'm a graduate of Mount St. Mary's University in Emmitsburg, Maryland. I can't wait to meet your learner in the class and get started soon. 

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