Campamento de verano de introducción a la IA y al aprendizaje automático | Nivel 1 para adolescentes
Esta es una introducción a la inteligencia artificial y al aprendizaje automático, que presenta a los estudiantes estos campos. Los estudiantes completarán cuatro proyectos de aprendizaje automático en Python utilizando herramientas de aprendizaje automático reales, código Python y datos reales.
David Sofield
Puntuación media:
4.9
Número de reseñas:(822)
Popular
Qué está incluido
10 reuniones en vivo
10 horas presencialesTarea
2-4 horas por semana. 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.Proyectos
3-6 durante toda la claseCertificado de finalización
Students will receive a certificate of completion at the end of the class. Students must attend at least 8 classes to receive the certificate.Experiencia de clase
Nivel de inglés - B2+
Grado de EE. UU. 8 - 11
Nivel Beginner
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.
Metas de aprendizaje
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.
Programa de estudios
10 Lecciones
más de 2 semanasLección 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 minutos de lección en vivo en línea
Lección 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 minutos de lección en vivo en línea
Lección 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 minutos de lección en vivo en línea
Lección 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 minutos de lección en vivo en línea
Otros detalles
Orientación para padres
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.
Requisitos previos
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.
Lista de útiles escolares
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.
Recursos externos
Además del aula de Outschool, esta clase utiliza:
Se unió el April, 2020
4.9
822reseñas
Popular
Experiencia y certificaciones del docente
Licenciatura desde 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. Reseñas
Curso grupal en vivo
165 US$
semanalmente5 x por semana, 2 semanas
60 min
Videoconferencias en vivo
Edades: 12-17
6-14 alumnos por clase
