Artificial Intelligence

Course Overview and Objectives:

This course, Artificial Intelligence (IIAI30017), offers students a comprehensive introduction to the fundamental concepts, techniques, and applications of artificial intelligence (AI). Through lectures, programming assignments, literature reviews, and project-based learning, students will gain both theoretical understanding and practical skills in AI.

• Provide a strong foundation in core AI principles, including search, knowledge representation, reasoning, probability, and machine learning.
• Develop proficiency in Python programming for AI applications, reinforcing concepts through practical assignments.
• Enhance students’ ability to critically read, evaluate, and present recent AI research papers.
• Cultivate problem-solving skills through a midterm report and a final project, encouraging creativity, innovation, and technical rigor.
• Equip students with hands-on experience in developing AI solutions that bridge theory and practice, with additional focus on demos and implementations.
• Encourage teamwork, communication, and class participation, preparing students to engage in both academic and industrial AI contexts.

Prerequisites

• Programming Proficiency in Python
  • All assignments will be implemented in Python. Students with extensive programming experience in other languages (e.g., C++, Matlab, or JavaScript) should still be able to adapt.
• Mathematics Foundations
  • Calculus and Linear Algebra: Ability to take derivatives, and familiarity with matrix–vector operations and notation.
  • Probability and Statistics: Understanding of basic probability concepts, Gaussian distributions, mean, standard deviation, and related statistical measures.

Grading

• Assignments (30%): Including programming assignments, literature review reports, etc.
• Midterm Report (20%): Students need to select a AI-related paper from the past three years and write a research report. The report should include Background, Motivation, Proposed Method, Result, and Personal Reflection. Additional points will be awarded for including a demo and technical implementation in the report.
• Final Project (40%): Including project presentation, and final project report. Students are required to select a AI-related topic, develop a proposal, and undertake an implementation project. The evaluation criteria encompass a thorough comprehension of the problem, innovation, practicality of the solution, completeness, and performance of the technical implementation. Additional credit will be awarded for incorporating a demo and technical implementation.
• Class Participation (10%): Class Participation.
• For each absence during roll call:-1 for the final grade.

Office Hours

• Monday 11:00-12:00 am
• Room: Engineering Building-6 (374)

Progress

Textbook

• Artificial Intelligence: A Modern Approach