Semester.ly

Johns Hopkins University | EN.600.435

Artificial Intelligence

3.0

credits

Average Course Rating

(4.19)

The course situates the study of Artificial Intelligence (AI) first in the broader context of Philosophy of Mind and Cognitive Psychology and then treats in-depth methods for automated reasoning, automatic problem solvers and planners, knowledge representation mechanisms, game playing, machine learning, and statistical pattern recognition. The class is a recommended for all scientists and engineers with a genuine curiosity about the fundamental obstacles to getting machines to perform tasks such as deduction, learning, and planning and navigation. Strong programming skills and a good grasp of the English language are expected; students will be asked to complete both programming assignments and writing assignments. The course will include a brief introduction to scientific writing and experimental design, including assignments to apply these concepts. [Applications] Prereq: 600.226; Recommended: linear algebra, prob/stat. Students can only receive credit for 600.335 or 600.435, not both.

Spring 2013

(3.83)

Spring 2014

(4.75)

Spring 2015

(4.0)

Spring 2013

Professor: COMPUTER SCIENCE

(3.83)

The best aspects of this course included the broad range of topics covered and the engaging, fun homework that was assigned. One student felt the course lacked innovation. Another student felt the grading scale was far too strict. One suggestion was for the instructor to focus more on the relevant topics. Prospective students should have a good understanding of calculus, and probability theory and statistics in order to understand the material.

Spring 2014

Professor: Benjamin Mitchel

(4.75)

The best aspects of this course were the interesting topics covered, the very cool software, and the introduction to kinematics. The class is about robotics, which is pretty cool regardless of the format. The worst aspects of the course was the disconnect between the theoretical lectures and the practical homework. Many students thought this led to overly complicated homework. Some suggestions for improvement included more exam review sessions, more interaction in class, and more instruction in RoS. Prospective students should have a strong programming and linear algebra background. The class is interesting and fun, but a good deal of work.

Spring 2015

Professor: Benjamin Mitchel

(4.0)

The best aspects of the course included the exposure to useful topics in robotics, the constant references to real-world applications of the concepts, and the enjoyable assignments. Some students suggested that the lectures and presentation of the material occasionally seemed jumbled, and that better organization would have al owed for more clarity. Further, some students suggested that probing concepts with greater depth and using concrete examples would have led to a more confident understanding of the material and its applications. Prospective students may benefit from prior familiarity with robotics and C++.