This Grade 4 curriculum is designed to introduce students to STEM (Science, Technology, Engineering, and Mathematics) with a focus on AI, Robotics, Drone Science, Data Analytics, and Machine Learning is engaging, hands-on, and age-appropriate with a focus on labs, creativity and innobvation.

Unit 1: Introduction to STEM
Week 1-2: Overview of STEM Fields
Introduction to the concept of STEM.
Exploration of various STEM careers through stories and guest speakers.
Classroom discussion on the importance of STEM in everyday life.

Unit 2: Basics of Robotics
Week 3-6: Understanding Robots
Definition and examples of robots.
Basic principles of robotics, including sensors and actuators.
Building simple robots using kits and programming basic movements.
Week 7-9: Programming Concepts
Introduction to block-based programming languages.
Coding exercises to control robots' movements and actions.
Problem-solving challenges to apply programming concepts.

Unit 3: AI Fundamentals
Week 10-12: Introduction to Artificial Intelligence
Explanation of AI concepts in a kid-friendly manner.
Examples of AI in daily life, such as voice assistants and recommendation systems.
Simple AI activities, like pattern recognition games.

Unit 4: Drone Science
Week 13-16: Introduction to Drones
Understanding the basic components of drones.
Safety measures and responsible drone usage.
Hands-on activities with small drones, including basic flying skills.
Week 17-18: Drone Programming
Introduction to drone programming using visual programming tools.
Coding exercises to control drone flight paths.
Group projects to plan and execute drone missions.

Unit 5: Data Analytics
Week 19-22: Introduction to Data
Basics of data collection and representation.
Graphs, charts, and other visualizations.
Simple data analysis activities, such as surveys and class polls.
Week 23-24: Data and Everyday Life
How data is used in various fields (e.g., weather predictions, sports).
Real-world examples of the impact of data on decision-making.

Unit 6: Machine Learning Concepts
Week 25-28: Introduction to Machine Learning
Explaining the concept of machines learning from data.
Examples of machine learning applications in daily life.
Basic supervised learning activities, such as image recognition games.

Week 29-30: Ethical Considerations
Discussion on the ethical use of AI and machine learning.
Understanding bias and fairness in algorithms.
Encouraging responsible use of technology.
Culminating Project: STEM Fair
Students work on a project that integrates concepts from all units.
Presentation of projects to parents and the school community.
Throughout the curriculum, the emphasis should be on fostering curiosity, creativity, and critical thinking. Hands-on activities, group projects, and real-world applications will help make STEM subjects engaging and relevant for Grade 4 students.