This Grade 12 STEM curriculum, focuses on advanced and specialized knowledge in Mathematics, AI, Robotics, Drone Science, Data Analytics, and Machine Learning. The curriculum is designed to prepare students for higher education and careers in cutting-edge technological fields.

Unit 1: Advanced Mathematics for STEM
Week 1-4: Mathematical Modeling and Simulation
Advanced techniques in mathematical modeling.
Simulation projects applying mathematical models to real-world STEM scenarios.
Exploration of the role of mathematics in predicting system behavior.

Week 5-8: Advanced Statistics and Probability
Advanced statistical analysis techniques.
Probability distributions in machine learning and data analytics.
Projects involving statistical modeling of complex phenomena.
Unit 2: Advanced Artificial Intelligence and Machine Learning

Week 9-12: Deep Learning and Neural Networks
In-depth study of deep learning architectures.
Advanced neural network design and optimization.
Real-world applications and case studies.

Week 13-16: Reinforcement Learning and Advanced AI Applications
Advanced concepts in reinforcement learning.
Applications of AI in diverse fields such as healthcare, finance, and autonomous systems.
Group projects addressing complex problems with advanced AI techniques.
Unit 3: Advanced Robotics and Control Systems

Week 17-20: Advanced Robotic Control
Nonlinear control systems in robotics.
Adaptive and optimal control algorithms.
Simulation projects for advanced robotic control.

Week 21-24: Bio-inspired Robotics
Exploration of bio-inspired robotics.
Application of biological principles to the design of robotic systems.
Collaborative projects on designing and simulating bio-inspired robots.
Unit 4: Advanced Drone Science and Autonomous Systems

Week 25-28: Swarm Intelligence and Drone Swarms
In-depth study of swarm intelligence.
Design and programming of drone swarms for complex tasks.
Real-world simulations and collaborative projects with drone swarms.

Week 29-30: Autonomous Systems in Research and Exploration
Applications of autonomous systems in research and exploration.
Guest speakers from research institutions.
Collaborative projects involving autonomous systems in specific research scenarios.
Unit 5: Advanced Data Analytics and Big Data Technologies

Week 31-34: Advanced Data Processing and Analysis
Advanced data processing techniques for large datasets.
Collaborative projects analyzing complex and massive datasets.
Real-world applications in big data analytics.

Week 35-38: Artificial Intelligence in Data Analytics
Integration of AI with advanced data analytics.
Machine learning applications in data analytics.
Capstone projects applying AI techniques to complex data analytics challenges.
Culminating Project: STEM Innovation Symposium
Independent or group research projects combining advanced mathematics with AI, robotics, drone technology, and data analytics.
Presentation of research findings at a STEM Innovation Symposium.
Peer review and feedback sessions.
Throughout the curriculum, there should be a strong emphasis on independent research, critical thinking, and collaborative problem-solving. Students should have opportunities to engage with industry professionals, participate in real-world applications, and explore the ethical implications of emerging technologies. The curriculum should prepare students for advanced studies in STEM fields or entry into industries that require expertise in AI, robotics, drone technology, data analytics, and machine learning at a high level of proficiency.