1-855-NGTLearning (1-855-648-5327)  ||  (925) 659-8000  || admin@ngtlearning.com

 Course Syllabus


Level 1 class: Students will begin by learning Generative AI Programming, gaining a foundational understanding of how large-scale AI models can create text, images, and code. They will explore how models like ChatGPT and DALL·E function, with a focus on core concepts such as prompt engineering and natural language interaction. Through hands-on projects, students will practice writing and refining prompts, working with APIs, and building simple applications that generate creative content using language models. This level emphasizes the development of practical skills in using generative AI tools responsibly and effectively, laying a strong foundation for more advanced AI topics.​

Level 2 class: In this level, students will explore Computer Vision, a dynamic field of AI that enables machines to interpret and understand visual data. They will learn how computers analyze images and videos to perform tasks such as object detection, image classification, facial recognition, and scene analysis. Through hands-on exercises using libraries like OpenCV, students will build applications that can “see” and respond to their environment. This module balances foundational theory with practical implementation, helping learners understand how vision-based AI powers real-world technologies such as self-driving cars, medical diagnostics, and augmented reality.

In Level 3 class, In the third level, students will focus on the core principles of Machine Learning (ML), using industry-standard libraries such as TensorFlow, Keras, NumPy, and essential visualization tools. They will learn how machines identify patterns and make data-driven decisions through both supervised and unsupervised learning techniques. Key topics include model training, optimization, and performance evaluation. Students will build and experiment with neural networks for tasks like classification and prediction, gaining hands-on experience in developing and refining ML models. This level emphasizes a practical and intuitive approach to machine learning, preparing learners to confidently apply these techniques in real-world AI applications.

** Each class will include hands-on activities, and the student will work on the project based on the topics covered in the class.​​​​​​

Artificial Intelligence, Machine Learning and LLM Programming 

Senior Tech Class ​​Curriculum

​

This hands-on, project-based course provides a comprehensive introduction to the evolving field of Artificial Intelligence (AI), equipping students with both foundational knowledge and practical skills. It begins with essential AI concepts such as intelligent agents, decision-making, and problem-solving strategies. Students explore how machines can simulate human intelligence to perform tasks like planning, learning, reasoning, and perception. Through real-world examples and engaging activities, learners will gain a deeper understanding of how AI is transforming industries ranging from healthcare to finance.​​


About this Course

  • Grade:  ​​7th-11th
  • Course Structure:  This course has three levels. Each Level is 12 classes (2 hr/week for fast track class and 1 hr class/week for regular class)
  • Prerequisite: Recommended to have some programming experience in python.
  • Course Certificate: After successfully completing the course, students will receive the course completion certificate
  • Usage Area: This class equips students with versatile AI skills applicable across a wide range of domain; including Generative AI, Machine Learning, Computer Vision, and LLM Programming and with real-world use cases spanning industries such as healthcare, finance, education, retail, and more. 
  • Format Available: In-person and Online Class
  • In-Person Class Requirements: All the required material will be provided in the class, including laptops (students do not need to bring anything)
  • Online Class Requirements: A computer (Windows or Apple Mac), headphones, and a webcam is required to join the Zoom class from home. 
  • Fee, Schedule, and Class Details: Visit the Online class registration page​ or In-Person class registration page​​​​​