Semester.ly

Johns Hopkins University | EN.500.111

Heart: Machine Learning for Medicine

1.0

credits

Average Course Rating

(4.15)

This course gives a peek into the research area of regression and inference, which is engineer-speak for “connecting dots with a line in a principled way.” Alternating between theory and practice, students will explore both foundational and modern techniques for finding patterns in data. Through hands-on coding activities and classroom discussions, students will experience for themselves the deep intersection between real world data, mathematical statistics, and computing, pushing them to seek out even more new and interesting knowledge during their remaining semesters at JHU. The course will emphasize key paradigms that appear often in applied mathematics, allowing students to apply their knowledge beyond medical applications and to areas such as economics, biology, and computer science.

Fall 2014

(3.94)

Fall 2014

(4.28)

Fall 2014

(4.0)

Fall 2014

(4.11)

Fall 2014

(4.16)

Fall 2014

(3.85)

Fall 2014

(4.28)

Fall 2014

(4.17)

Fall 2014

(4.58)

Fall 2014

Professor: Andrew Gaynor

(3.94)

Students’ favorite aspects of this class were the hands-on 3D printing activity and off-site field trip experience. Students thought the course’s biggest drawback was the length of class periods. They believed that the course could be improved with greater interactivity during class times. Students thought it was valuable for prospective participants to know that this course provided a useful introduction to a current field of research.

Fall 2014

Professor: Gregory Wiedman

(4.28)

Students thought this course’s best aspect was the opportunity to learn from an engaging instructor who provided insight into current research in drug engineering. Some students thought the weakest aspect of the course was that the class was not taught effectively to those with little knowledge or experience in the subject matter. They also thought the class would benefit from greater discussion during class time. Students thought it would be useful for prospective participants to know that this class had a light workload.

Fall 2014

Professor: Robert Ireland

(4.0)

Students in this course thought that it was a useful introduction to materials science taught by an engaging instructor. Students found that the course’s biggest drawback was that it covered a great deal of material in a short time. They also believed that the course could be improved by incorporating more interactivity or hands on activities into class time. Students thought it was important for people considering this class to know that the class required little work outside of class.

Fall 2014

Professor: Nuala Del Piccolo

(4.11)

Students especial y enjoyed the opportunity in this course to learn about a subject new to them. They also appreciated the off-site field trip incorporated into the class. Students believed that the biggest drawback of the course was the short duration. They also thought that background knowledge in the subject area was sometimes assumed making it difficult to understand some of the material being taught. They thought that the course could benefit from the addition of hands on activities exploring the techniques being discussed in lectures. Students thought that it would be useful for students thinking about taking the class that it had a small workload and provided a low pressure opportunity to explore the subject matter.

Fall 2014

Professor: Amir Pourmorteza

(4.16)

In this course, students especially appreciated the opportunity to learn from an engaging instructor who shared their personal experience with medical imaging. Students thought the class’ biggest weakness was the long timespan of the class periods. Students believed the course could have benefitted from additional materials to show some of the equipment and concepts being described, as well as additional interactivity in class periods. Participants thought people thinking about taking the course should know that little background knowledge was necessary for the course and that the instructor helped to make concepts understandable.

Fall 2014

Professor: Anindya Roy

(3.85)

152Students said they enjoyed the engaging topics and opportunities for discussion in this course. Students felt that one of the weaker aspects of this section was an over-emphasis on energy studies. The class could have benefitted from additional discussion or interactivity, students said. They also felt it would be useful for people considering taking this class to know that the course required a light workload outside of class.

Fall 2014

Professor: Kristie Wrasman

(4.28)

Students liked that this course provided an engaging introduction to genetics taught by an instructor who was passionate about the subject of the class. Students believed that the class’s biggest drawback was the extended length of class sessions. They thought the course could be improved with greater discussion and interactivity. People considering taking this class should know that it did not require a background in genetics or biology to be comprehensible, students said.

Fall 2014

Professor: Ehsan Variani

(4.17)

Students’ favorite aspects of this class were the hands-on 3D printing activity and off-site field trip experience. Students thought the course’s biggest drawback was the length of class periods. They believed that the course could be improved with greater interactivity during class times. Students thought it was valuable for prospective participants to know that this course provided a useful introduction to a current field of research.

Fall 2014

Professor: Robert Yaffe

(4.58)

Students particularly enjoyed the interesting subject matter and incorporation of real world examples into this course. Students also appreciated the variety of activities they engaged in. Students thought the class’s biggest drawback for this class was the long class sessions. Some students believed that the course could have been improved by exploring fewer topics, and looking into each in greater depth. 154Participants thought it was useful for people thinking about taking this course to know that there was a light workload outside of class.

Lecture Sections

(01)

No location info
J. Lim
13:30 - 14:45

(02)

No location info
M. Jain
16:30 - 17:45

(04)

No location info
I. Saha
13:30 - 14:45

(05)

No location info
E. Ariail
18:00 - 19:15

(03)

No location info
C. Hallinan
10:30 - 11:45