Home >Courses >AI and Robotics Teaching Certification for Class 9-10 Teachers

NSTC Logo
Home >Courses >AI and Robotics Teaching Certification for Class 9-10 Teachers

Self Paced

AI and Robotics Teaching Certification for Class 9-10 Teachers

Inspire the Next Generation: Teach AI and Robotics with Confidence

Register NowExplore Details

Early access to e-LMS included

  • Mode: Virtual / Online
  • Type: Self Paced
  • Level: Moderate
  • Duration: 3-4 Months

About This Course

This certification empowers teachers to introduce foundational AI and robotics concepts to students in grades 9-10, focusing on engaging, hands-on learning experiences that inspire interest in STEM. The program provides tools, techniques, and curriculum strategies to make complex AI and robotics topics accessible and enjoyable for young learners.

Aim

The AI and Robotics Teaching Certification for Class 9-10 Teachers is designed to equip educators with the skills and resources needed to teach fundamental concepts in AI and robotics effectively. The course includes a mix of theoretical knowledge and practical applications, covering AI basics, robotics components, ethical considerations, and project-based learning tailored to this age group.

Program Objectives

  • Gain confidence in teaching fundamental AI and robotics concepts to young learners.
  • Develop skills to design interactive, project-based learning experiences.
  • Learn techniques to introduce responsible and ethical AI discussions.
  • Enable students to apply AI and robotics to real-world scenarios.
  • Design and evaluate student projects for practical and educational outcomes.

Program Structure

1. Introduction to AI and Robotics

  • Overview: Explore foundational AI concepts and applications across industries, along with the core principles of robotics.
  • History and Evolution: Key milestones in AI and robotics, from early inventions to modern advancements in technology.
  • Hands-On Component: Introductory activity where participants identify common AI applications in everyday life.

2. Programming Basics for AI

  • Python Fundamentals: Introduction to Python syntax, basic data types, loops, and conditional statements.
  • Coding Exercises: Simple exercises to write programs performing basic tasks, laying the foundation for AI applications.
  • Data Handling: Brief introduction to data manipulation in Python, essential for developing AI applications.

3. Fundamentals of AI in Education

  • Problem-Solving with AI: Understanding AI’s role in enhancing problem-solving and pattern recognition, with a focus on critical thinking.
  • Case Studies: Examples of AI in education, such as adaptive learning platforms, feedback systems, and personalized learning experiences.
  • Collaborative Activity: Group activity where participants brainstorm potential applications of AI in educational settings.

4. Integrating AI & Robotics with STEM

  • Curriculum Alignment: Approaches for incorporating AI and robotics within the STEM curriculum.
  • Workshop: Participants design a lesson plan that integrates basic AI or robotics concepts with STEM learning goals.
  • Practical Examples: Review of educational tools and platforms that support AI and robotics learning in STEM.

5. Building a Simple Robot for Classroom Demonstration

  • Introduction to Robotics Kits: Overview of popular educational robotics kits, including sensors, motors, and programmable parts.
  • Hands-On Assembly: Guided assembly and programming of a basic robot, demonstrating functions like following instructions or responding to touch.
  • Classroom Applications: Discussion on ways to engage students with robotics-based activities in a classroom setting.

6. Practical Coding for AI Tools

  • Working with AI Models: Introduction to pre-built AI models, such as chatbots, basic image classifiers, and sentiment analysis tools.
  • Training and Testing: Basic concepts in using training data, evaluating model accuracy, and interpreting AI outputs.
  • Project: Set up a simple chatbot project to illustrate AI in action, allowing participants to customize and interact with AI responses.

7. Classroom Engagement Techniques

  • Pedagogical Approaches: Strategies for teaching complex topics like AI and robotics effectively to various age groups.
  • Interactive Learning: Techniques for fostering hands-on learning, promoting inquiry-based projects, and encouraging collaborative problem-solving.
  • Student Engagement: Tailoring instructional approaches to different learning styles, emphasizing inclusivity and accessibility.

8. Assessment Strategies in AI Education

  • Competency-Based Assessment: Approaches for evaluating practical AI and robotics skills, including problem-solving and critical thinking.
  • Rubric Design: Crafting clear, objective rubrics for project-based assessments, quizzes, and hands-on activities.
  • Feedback Mechanisms: Using AI-enabled tools for continuous formative assessment and constructive feedback.

9. AI Ethics and Responsible Use

  • Ethics in AI: Exploration of key ethical considerations in AI, including bias, privacy, transparency, and accountability.
  • Classroom Discussion: Facilitated discussion on ethical scenarios in AI, encouraging students to think critically about the social impact of AI technologies.
  • Project: Students create a brief presentation on the ethical implications of a chosen AI technology, addressing potential benefits and risks.

10. Project-Based Learning

    • Final Project Design: Structuring a capstone group project where participants develop simple AI or robotics applications.
    • Group Collaboration: Best practices for managing teamwork, assigning roles, and facilitating cooperative learning.
    • Presentation and Review: Group presentations of projects followed by a class discussion, constructive feedback, and a reflection on project experiences.

Who Should Enrol?

Basic knowledge of computers, basic teaching experience in science or STEM subjects. Knowledge of Python programming is an advantage but not mandatory.

Program Outcomes

  • Confidence in teaching AI and robotics fundamentals.
  • Proficiency in creating project-based AI and robotics activities.
  • Ability to introduce ethical AI discussions in classroom settings.
  • Skills in assessing and guiding student progress in STEM subjects.

Fee Structure

Discounted: ₹15000 | $195

We accept 20+ global currencies. View list →

What You’ll Gain

  • Full access to e-LMS
  • Real-world dry lab projects
  • 1:1 project guidance
  • Publication opportunity
  • Self-assessment & final exam
  • e-Certificate & e-Marksheet

Join Our Hall of Fame!

Take your research to the next level with NanoSchool.

Publication Opportunity

Get published in a prestigious open-access journal.

Centre of Excellence

Become part of an elite research community.

Networking & Learning

Connect with global researchers and mentors.

Global Recognition

Worth ₹20,000 / $1,000 in academic value.

Need Help?

We’re here for you!


(+91) 120-4781-217

★★★★★
Green Catalysts 2024: Innovating Sustainable Solutions from Biomass to Biofuels

Very helpful to us.

Amit Das
★★★★★
AI for Federated Learning: Decentralized Data and Privacy-Preserving Models

I need invoice with the following data:
Tera Srl
Via Martin Luther King, 35
70014 Conversano (Ba) - ITA
VAT ID: IT06597060729

Please, send it to leonardo.cici@terasrl.it

Daniel Lotano
★★★★★
Prediction of Protein Structure Using AlphaFold: An Artificial Intelligence (AI) Program

Nice clear presentation.

Liam Cassidy
★★★★★
AI and Ethics: Governance and Regulation

the workshop was very good, thank you very much

Sandra Wingender

View All Feedbacks →

Stay Updated


Join our mailing list for exclusive offers and course announcements

Ai Subscriber