Outschool
検索

$32

weekly
or $319 for 10 classes
クラス
再生

AI と機械学習入門 | AI & Python コーディング クラス レベル 1

48 人が学習を完了しました
年齢 11 歳-16 歳
ライブグループコース
これは人工知能と機械学習の入門であり、学習者にこれらの分野を紹介します。学生は実際の機械学習ツール、Python コード、実際のデータを使用して、4 つの機械学習 Python プロジェクトを完了します。
平均評価:
4.9
レビュー数:
(815 レビュー)
Popular
Rising Star

オンラインライブ授業
週に1回、 10 週間
6 人-14 人 1クラスあたりの学習者
60 分

含まれるもの

10 ライブミーティング
10 授業時間
宿題:
週あたり 1-2 時間. There will be review questions and practice assignments each week, taking approx. 1 to 2 hours. Learners are also strongly encouraged to learn on their own outside of class time. Students will also have an optional final project introduced in week 7 of the class and presented during a optional 3 to 5-minute presentation.
テスト
All the learners in the last 3 weeks can work on their own machine learning project and complete a optional 3 to 5-minute presentation to the class. Learners will receive feedback from the instructor and other learners for project.
修了証書
Students will receive a certificate of completion at the end of the class that is fully verifiable online. Students must attend at least 8 classes to receive the certificate.
この文章は自動翻訳されています

このクラスで学べること

英語レベル - B2+
米国の学年 6 - 9
Beginner レベル向け
This introduction to artificial intelligence and machine learning allows learners to start exploring the foundations of these exciting fields. Learners will complete 4 projects using Python code and the same machine learning tools used by professionals in the field.  Students will complete real 4 machine learning projects utilizing a decision tree, linear regression, nearest neighbors, and a neural network. Learners will learn the steps of successful machine learning projects. These steps include data collection, data preparation, model training, accuracy determination, and model improvement. All students in the last 3 weeks are encouraged to work on their own machine learning project and complete an optional 5-minute presentation to the class. 

**** Please, review the coding prerequisites listed at the end of this description or in the parental guidance section. This is a coding-class using real code and the same tools used by professional AI and Machine Learning engineers. ****

What Learners will Create

Jump into four hands-on projects where you'll:
Train an AI to distinguish between cats and dogs
Analyze real scientific data from the famous Iris dataset
Build a neural network that can read handwritten numbers
Design and code your own unique AI project based on what interests you most

Class Syllabus

Week 1
What is Intelligence?
What is AI? 
AI in Our World
What is Machine Learning?
Artificial Intelligence vs. Machine Learning vs. Data Science
Introduction to Google Colab

Week 2
Types of Machine Learning Part 1
Google Colab Introduction
Python NumPy and Pandas Introduction
Working with Panda Data Frames
Machine Learning Project Introduction #1 - Cat or Dog Classification

Week 3
Machine Learning Project  #1 - Cat or Dog Classification
What Problems can AI Solve?
Supervised vs. Unsupervised Learning
Types of Supervised Learning 
The Machine Learning Process

Week 4
Working with Data Python
Project 
Data Science and People
NumPy Introduction
Pandas Introduction
Matplotlib Introduction

Week 5
Data and AI
Collecting and Preparing Data
Ethical Issues in Data
Potential problems with AI
Coding Skills: A Good Coder is a Good Searcher

Week 6
What is Scikit-learn?
Supervised Learning Algorithm - Nearest Neighbor 
Machine Learning Project #2 Introduction -  Iris Data Set

Week 7
Machine Learning Project #2 Introduction -  Iris Data Set
Supervised Learning Algorithm - Decision Trees
Introduction to Final Project
Test and Training Data

Week 8
Introduction to Neural Networks
Neural Network Concepts
Supervised Learning Project #3 - Classification: Handwriting Classification
Using Scikit-learn with images
Loss and Determining Accuracy 
Test and Training Data

Week 9
Supervised Learning Project #3 - Classification: Handwriting Classification
Loss and Determining Accuracy 
Review Final Project

Week 10
Final Project and Presentations
Student Presentation
Careers in Machine Learning and AI


Interactive Groups Build the Foundation of Code Skills

Every learner is strongly encouraged to post questions, sample code, and their projects every step of the way. This gives students the chance to learn from each other and start practicing reading code. The instructor will also be providing feedback and guidance regularly throughout the course. 

****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.

学習到達目標

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.

シラバス

10 レッスン
10 週間以上
レッスン 1:
Introduction to AI and Machine Learning
 Students will explore the concepts of intelligence and AI, discovering how AI is integrated into our daily lives. They'll learn the distinction between AI, Machine Learning, and Data Science, and get hands-on experience with Google Colab, a powerful tool for coding and analysis. 
60 分のオンラインライブレッスン
レッスン 2:
Fundamentals of Machine Learning and Python
 This session introduces different types of Machine Learning and dives into essential Python libraries like NumPy and Pandas. Students will begin their first ML project, predicting favorite music, which will give them a practical understanding of ML applications. 
60 分のオンラインライブレッスン
レッスン 3:
Machine Learning Concepts and Data Visualization
 Students will complete their first ML project and explore the problems AI can solve. They'll learn about supervised and unsupervised learning, key ML terminology, and the overall ML process. The day concludes with an introduction to data visualization using Matplotlib. 
60 分のオンラインライブレッスン
レッスン 4:
Working with Data and Python
 This day focuses on handling data in Python. Students will work with Pandas DataFrames and synthetic data, preparing them for their second ML project comparing height and weight data. 
60 分のオンラインライブレッスン

その他の情報

保護者へのお知らせ
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 and Kaggle datasets will be used for practice datasets throughout the class. Teachable Machine and ML Playground are low code platforms for machine learning projects. Python.org will be used as Python reference sources throughout the class. ***Intro to AI and ML Class Prerequisites **** To succeed in this class, learners should have a strong grasp of coding fundamentals including conditional statements, functions, loops, and arrays/lists. Learners should have completed comprehensive multi-week beginner level coding classes before starting this course. Any programming language is fine, such as Python, Java, JavaScript, C / C++, or Swift. There will be a brief review during the first few classes using Python. There are many excellent beginner Python courses available through Outschool.
受講の前提条件
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.
受講に必要なもの
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. 

*** Intro to AI and ML Class Prerequisites ****

To succeed in this class, learners should have a strong grasp of coding fundamentals.
This includes conditional statements, functions, loops, and arrays/lists. Learners should have completed comprehensive multi-week beginner level coding classes before starting this course. Any programming language is fine, such as Python, Java, JavaScript, C / C++, or Swift. There will be a brief review during the first few classes using Python. There are many excellent beginner Python courses available through Outschool.
外部リソース
このクラスでは、Outschool内のクラスルームに加えて、以下を使用します。

先生について

参加しました April, 2020
4.9
815レビュー
Popular
Rising Star
プロフィール
教師の専門知識と資格
学士号 Mount St. Mary's University から
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. I am the author of the soon-to-be released book All About Python for Kids.  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. 

レビュー

他のクラス by David Sofield
他のクラス by David Sofield


その他の人気クラス
人工知能によるデジタルアートとクリエイティブライティング
Miss Haley
5.0
(45)
$60 セッションごと
1対1レッスン
オンデマンド
9 歳-18 歳
子どものためのAI: 人工知能の基礎を学ぶ
Create n Learn: English, Coding, AI, Music, Math
4.9
(206)
$20 クラスごと
次のセッションは明日の 6 PM です
グループクラス
4 週間、 2/週、 55 分
7 歳-12 歳
AI 探索: 仮想ロボットのトレーニング | 人工知能を学ぶ
Create n Learn: English, Coding, AI, Music, Math
4.9
(206)
$12 クラスごと
次回のセッションは Monday の2 AM です
グループクラス
1 週間、 1/週、 55 分
7 歳-12 歳
101 プライベート - 初級レベル 1 - 人工知能 (AI) - 毎週 30 分
StudentScholars
3.9
(86)
$33 セッションごと
1対1レッスン
オンデマンド
8 歳-18 歳
2日間の人工知能101 - コンピュータ科学者が教えるCHATGPTのようなAI
Explosive Learning Jo Reynolds Life Skill Teachers
4.8
(1,288)
$43 クラスごと
次回のセッションは Thursday の2 PM です
グループクラス
1 週間、 2/週、 50 分
9 歳-14 歳
AI アート - 創造性ワークショップ - AI を使用して素晴らしい絵を描く
Mark Richard Mazzu a.ka. "Mister Mark"
4.8
(473)
$28 クラスごと
次回のセッションは Fri 3/7 の4 PM です
グループクラス
1 週間、 1/週、 40 分
7 歳-11 歳
Scratch コーディングによる人工知能プロジェクト (レベル 1)
AI Code Academy
4.7
(1,767)
$22 クラスごと
次のセッションは明日の 12:30 AM です
グループクラス
10 週間、 1/週、 1 時間
11 歳-16 歳
AI ソフトウェア: 子供向けガイド
Daniel Solomon Kaplan
4.9
(396)
$9 クラスごと
グループクラス
4 週間、 1/週、 30 分
8 歳-12 歳
初心者のための Python と AI: AI プロジェクトを学習、構築、探索する
Faruk Hasan
4.8
(145)
$12 クラスごと
次回のセッションは Tue 3/25 の11:35 PM です
グループクラス
24 週間、 1/週、 35 分
12 歳-15 歳
AI ソフトウェア: ティーンエイジャー向けガイド
Daniel Solomon Kaplan
4.9
(396)
$13 クラスごと
次回のセッションは Fri 2/28 の8 PM です
グループクラス
4 週間、 1/週、 50 分
13 歳-18 歳
AI クラブ: ChatGPT やその他の AI ツールを効果的かつ責任を持って使用する
Dr. Nathan
5.0
(23)
$50 クラスごと
次のセッションは明日の 5 PM です
グループクラス
1/週、 45 分
8 歳-13 歳
* 高校生のためのAI
Brandy Dahlen Yun and BE Education
4.9
(634)
$25 クラスごと
次回のセッションは Sat 5/31 の3 PM です
グループクラス
4 週間、 1/週、 45 分
13 歳-18 歳
AIチャットボットを構築しよう
Guido
5.0
(9)
$20 クラスごと
次回のセッションは Sunday の10 PM です
グループクラス
1 週間、 1/週、 1.50 時間
13 歳-18 歳
AI と機械学習入門 | AI & Python コーディング クラス レベル 1
David Sofield
4.9
(815)
$32 クラスごと
次回のセッションは Fri 3/21 の4:15 PM です
グループクラス
10 週間、 1/週、 1 時間
11 歳-16 歳
エイプリルフールの AI エスケープ大イベント、ESL 対応
Teacher Sharon, M.Ed., TEFL
4.9
(925)
$13 クラスごと
次回のセッションは Mon 3/10 の6 PM です
グループクラス
1 週間、 1/週、 35 分
5 歳-9 歳
1対1の宿題サポート: AIを使って概念を理解する
Mrs. B
$57 セッションごと
1対1レッスン
オンデマンド
11 歳-18 歳
もっとクラスを見る
アプリを入手 
App StoreでダウンロードGoogle Playで入手する
Home
検索
ギフトカードを贈る
通貨、タイムゾーン、言語の設定を開く
言語と地域
ログイン