From the Upcoming Book
All course materials are derived from our comprehensive book Engineering AI Agents, currently in development.
These courses provide hands-on experience with the concepts, algorithms, and techniques that will be covered in depth in the book.
Course Structure
Students typically begin with Introduction to AI, which establishes the fundamental concepts, techniques, and mathematical foundations necessary for advanced study. After completing the introductory course, students can choose to specialize in either Deep Learning for Computer Vision or AI for Robotics, based on their interests and career goals.Prerequisites
Before starting any course, students should have a solid foundation in mathematics and programming. We recommend reviewing the following topics covered in our Prerequisites:Mathematical Foundations
- Linear Algebra - Vectors, matrices, eigenvalues, and matrix operations
- Calculus - Derivatives, gradients, and matrix calculus for optimization
- Probability - Joint, marginal, and conditional distributions
Programming Skills
- Python - Proficiency in Python programming for data science and machine learning
- Libraries - Familiarity with PyTorch or TF/Keras, NumPy, Matplotlib, and other common MLframeworks
If you need to refresh your background knowledge, visit the Prerequisites section for comprehensive reviews of these topics before beginning the coursework.
Spring 2026 Offerings
CS-GY-6613 — Introduction to AI
Foundational concepts in artificial intelligence, machine learning, optimization, and neural networks. NYU Tandon.
CS681 — Deep Learning for Computer Vision
Advanced computer vision techniques including object detection, segmentation, and generative models. NJIT.
CS685 — AI for Robotics
Intelligent robotic systems, ROS integration, perception motion planning, and vision-language-action models. NJIT.
CS670/370 — Introduction to AI
Foundational concepts in artificial intelligence, machine learning, optimization, and neural networks. NJIT.
Learning Path
- Start with Introduction to AI - Build your foundation in machine learning fundamentals, optimization techniques, and neural network architectures
- Choose your specialization - Select either Computer Vision or Robotics based on your interests
- Apply your knowledge - Complete hands-on assignments and projects throughout each course
Course Resources
All courses include:- Comprehensive lecture materials and readings
- Hands-on programming assignments
- Development environment setup guides
- Submission guidelines and best practices