Understanding AI Principles: Students will grasp the foundational principles of Artificial Intelligence, including the history and significance of AI in our modern world.

AI Fundamentals: They will develop a solid understanding of key AI concepts, such as machine learning, neural networks, and data analysis.

Hands-On AI Skills: Through practical projects, students will gain hands-on experience in AI, including creating image recognition systems, chatbots, and AI-driven games.

Ethical Considerations: Students will explore the ethical aspects of AI, learning to identify and address issues like bias, privacy concerns, and the responsible development of AI technologies.

Real-World Applications: They will discover how AI is employed in various industries, from healthcare to finance and transportation.

Problem-Solving with AI: Students will develop critical thinking and problem-solving skills by applying AI tools to real-world challenges.

By the end of the class, students will be equipped with the knowledge and practical skills needed to understand, engage with, and make informed decisions about Artificial Intelligence.

Meet Teacher Andi, a seasoned Art Teacher hailing from the vibrant arts scene of Puerto Rico. With a rich background in art education and a profound understanding of digital art tools, Andi is your guide on a transformative artistic journey.

Education and Expertise:
Hold on tight as Andi's expertise unfolds—holding a Bachelor's degree in Fine Arts with a specialization in Digital Arts. With several years of experience, Andi has honed the craft of teaching art and design to students across various age groups.

Digital Art Proficiency:
Andi navigates the digital canvas with finesse, wielding the power of Affinity, Procreate, and Blender. Their proficiency in these digital art tools ensures a comprehensive exploration of the digital realm.

Inclusive Learning Environment:
Andi's teaching approach is a blend of encouragement, creativity, and support. Step into an inclusive classroom atmosphere that fosters individual expression and creativity.

Whether you're a budding artist or have some experience under your belt, Teacher Andi is ready to nurture your artistic skills, guiding you through the world of digital art with expertise and enthusiasm. Join in and unleash your creative potential!

Homework Offered
Type of Homework:

Students will have a mix of individual and group projects to complete as homework.
Individual assignments may include coding tasks or research on AI-related topics.
Group projects will encourage collaboration, allowing students to work together on more extensive AI-related tasks.
Time Commitment:

Homework time can vary, but on average, students can expect to spend approximately 1 to 2 hours on homework per week. This allows for a manageable workload while ensuring they have time to absorb the class material.
Reading Assignments:

Reading assignments may include articles, case studies, or research papers related to AI. These readings will be carefully selected to be age-appropriate and relevant to the class topics.
On average, learners may be expected to read around 5-10 pages of material independently per week.
The homework assignments are thoughtfully designed to complement the class content and provide students with opportunities to apply what they've learned in both individual and collaborative settings.




Assessments Offered
In this AI class, learner progress is assessed through a combination of methods to provide a well-rounded evaluation:

Informal Assessment: Regular discussions and Q&A sessions during class help gauge students' understanding and engagement. Questions, polls, and open dialogues are used to assess comprehension.

Hands-On Projects: The completion of hands-on AI projects serves as a practical assessment of their ability to apply what they've learned.

Group Assignments: Group projects and collaborative assignments allow students to demonstrate teamwork and communication skills while working on AI-related tasks.

Participation and Engagement: Active participation in class activities, discussions, and group work is a significant part of the assessment. Engaged learners often have a deeper understanding of the material.

Quizzes or Tests: Periodic quizzes or tests may be used to evaluate their grasp of essential AI concepts and principles.

Homework Evaluation: Homework assignments, whether individual or group-based, are assessed for completeness and quality.

Final Project: A culminating AI project at the end of the course allows students to showcase their comprehensive understanding and practical skills.

Feedback and Reflection: Learners may be encouraged to provide self-assessments and reflections on their progress, fostering self-awareness and metacognition.

The goal is to assess students' AI knowledge and skills holistically, taking into account their engagement, practical abilities, and understanding of AI concepts. Assessment methods are designed to be constructive, supportive, and focused on facilitating growth and learning.
Grades Offered

Textbooks and Online Resources:

"Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig.
Online resources like the MIT OpenCourseWare on AI, which offers lecture notes and materials.
Articles and Research Papers:

Research papers from reputable AI conferences such as NeurIPS, ICLR, and ICML, which provide insights into the latest AI developments.
Articles from AI-related journals and magazines like "AI Magazine" or "Communications of the ACM."
Websites and Online Platforms:

Online AI courses from platforms like Coursera, edX, and Udacity can be a valuable resource for supplementary materials and practical exercises.
Open Source AI Tools and Libraries:

OpenAI's documentation and GitHub repositories for AI-related projects can be referenced for practical coding and development activities.
AI Ethics and Responsible AI Guidelines:

Documents from organizations like the Partnership on AI, which provide guidelines on ethical AI development, fairness, and transparency.