DSBA 6156: Applied Machine Learning
University of North Carolina, Charlotte
Practical perspectives and applications of machine learning methods and techniques including: acquisition of declarative knowledge; organization of knowledge into new, more effective representations; development of new skills through instruction and practice; and discovery of new facts and theories through observation and experimentation.�Students are expected to have a functional knowledge of Python programming before enrolling in the�course.�Students are expected to have a functional knowledge of Python programming before enrolling in the�course.�
Average GPA: 3.80
Grade distribution records: 1,042 students across 24 terms.
Grade distribution
| Grade | Students | Percent |
|---|---|---|
| A | 835 | 80.1% |
| B | 162 | 15.5% |
| C | 19 | 1.8% |
| W | 14 | 1.3% |
Based on 1,042 student grade records across 24 terms and 14 professors.
Instructors
- Richard Chakra 232 students, Average GPA 3.72
- Siddharth Krishnan 147 students, Average GPA 3.91
- Robert Abbott 120 students, Average GPA 3.98
- Samira Shaikh 112 students, Average GPA 3.91
- Mirsad Hadzikadic 109 students, Average GPA 3.64
- Greg Michaelson 67 students, Average GPA 3.66
- Depeng Xu 62 students, Average GPA 3.83
- Khalil Khouy 55 students, Average GPA 3.80
- Cory Hefner 39 students, Average GPA 3.90
- Joseph Tenini 37 students, Average GPA 3.63
- Minwoo Lee 37 students, Average GPA 3.78
- Agnieszka Dardzinska 16 students, Average GPA 4.00
- Richard Souvenir 6 students, Average GPA 3.00
- Pamela Thompson 3 students, Average GPA 3.67