AI/Robotics specialization

Description

Course Description: The AI/Robotics Specialization is a comprehensive course designed to introduce students to the exciting fields of artificial intelligence and robotics. The course is divided into three levels: basic, intermediate, and advanced, each catering to different skill levels and providing a progressive learning experience. The course is delivered over ten-hour sessions conducted online via Zoom. It is suitable for students interested in preparing for exams such as the AP Computer Science and for kids who want to explore and develop skills in this rapidly advancing field.

Basic Level: In the basic level, students will gain a foundational understanding of AI and robotics. They will explore the following topics:

1. Introduction to AI and Robotics: Overview of key concepts, applications, and the impact of AI and robotics on society.
2. Python Programming: Introduction to programming using Python, including data types, variables, control structures, and functions.
3. Game Development: Introduction to game development using Python, focusing on basic game mechanics and algorithms.
4. Introduction to Machine Learning: Understanding the fundamentals of machine learning, including supervised and unsupervised learning algorithms.

Intermediate Level: The intermediate level builds upon the concepts covered in the basic level and focuses on hands-on projects and real-world applications. Topics covered include:

1. Advanced Python Programming: Exploring more advanced programming concepts, data structures, and libraries for AI and robotics.
2. Data Analysis and Visualization: Introduction to data analysis techniques and visualization using Python libraries such as Pandas and Matplotlib.
3. Machine Learning Projects: Implementation of machine learning algorithms and projects using real-world datasets from platforms like Kaggle.
4. Version Control and Collaboration: Introduction to using Git and GitHub for version control and collaborative coding.

Advanced Level: The advanced level delves deeper into advanced topics and emphasizes practical applications. Students will explore:

1. Cloud Computing: Understanding cloud platforms and services for scalable AI and robotics applications.
2. Advanced Probabilistic Models: Exploring probabilistic models and algorithms, including Bayesian networks and hidden Markov models.
3. Deep Learning: Introduction to deep learning, neural networks, and popular frameworks like TensorFlow and PyTorch.
4. Simulation Platforms: Utilizing simulation platforms such as Gazebo or Unity to practice and test AI and robotics algorithms in virtual environments.

Throughout all levels of the specialization, students will have access to online resources and tools such as Code.org for interactive projects and activities.

Expected Outcomes: By the end of the AI/Robotics Specialization, students can expect to:

1. Understand the foundational concepts and principles of AI and robotics.
2. Be proficient in Python programming and its application in AI and robotics.
3. Develop machine learning skills and implement algorithms on real-world datasets.
4. Gain experience with collaboration and version control using Git and GitHub.
5. Explore cloud computing and its role in scalable AI applications.
6. Familiarize themselves with advanced probabilistic models and deep learning techniques.
7. Gain practical experience through hands-on projects and simulations.
8. Prepare for exams such as the AP Computer Science and develop a strong foundation for further studies in AI and robotics.

This course will enable students to become familiar with AI and robotics at an early age, empowering them to pursue academic and industry opportunities in the field and ultimately become skilled machine learning practitioners.