Class record · ENGR · MCAS

ENGR 3105

Introduction to Statistical Data Analysis and Machine Learning · 1 instructor on record · 11 sections

What the course score is made of

86BC evaluations11 records · weight ×1.0 · Spring 2024 – Spring 2026

—Student reviewsno reviews — does not contribute

—RateMyProfessorsno ratings — does not contribute

That is the class itself, averaged across everyone who taught it. Who taught it, and how each of them scored, is the board below — that is what a student picking a section is actually choosing between.

What the challenge rank is made of

49thMore challenging than 49% of BC classesranked against every one we hold

90BC — “Intellectually Challenging”11 records · raw score out of 100

Boston College's own “intellectually challenging” question for this class only — students answer it positively about courses that stretched them, so it measures intellectual challenge and NOT grading, workload or quality. Almost every BC class scores high on it, which is why it is shown as a rank rather than a score.

What the workload rank is made of

25thMore work than 25% of BC classesranked against every one we hold

40BC — “Workload”11 records · raw score out of 100

Boston College reports workload for this class only as one of five bands, not as a number of hours, and it does not publish what the bands mean — so this site will not translate it into hours. Higher means more work, which is not the same as worse.

This course integrates mathematical foundations with engineering applications to provide an understanding of machine learning. Students will apply fundamental mathematical conceptssuch as probability, linear algebra, and optimizationto formulate and solve machine learning problems. Through hands-on MATLAB exercises, students will preprocess, explore, and analyze data, implement classification and regression models, and evaluate their performance using mathematical metrics. The course also explores the theoretical and practical aspects of deep learning, including backpropagation, convolutional neural networks (CNNs), and transfer learning, while emphasizing optimization techniques for improved model accuracy. By interweaving mathematical theory with engineering applications, this course ensures a well-rounded approach to machine learning, preparing students to tackle real-world challenges with both analytical and computational skills.

The only instructor on record

11 sections · nobody else has taught itFull record

Instructor	Overall	Workload	Challenge
Amin MohebbiProfessor of the Practice · Engineering	9111 records	25th	49th

There is no ranking to read here: Amin Mohebbi is the only instructor with evaluation records for ENGR 3105, so the number is a record, not a position.

Also taught by Amin Mohebbi

5 other classes

Class	Instructors	Course score
ENGR 2104Engineering Foundations Studio IV	314 records	73
ENGR 2101Engineering Foundations Studio I	34 records	78
ENGR 3103Advanced Math for Engineers	22 records	85
ENGR 4330Green Building Design	22 records	90
ENGR 4430Design of Hydraulic Structures	11 record	94

Other ENGR classes

All of them

Class	Instructors	Course score
ENGR 1801Making the Modern World: Design, Ethics & Engineering	830 records	81
ENGR 3100Collaborative Service Engineering Project	515 records	85
ENGR 2104Engineering Foundations Studio IV	314 records	73
ENGR 1703First-year Human-Centered Engineering Reflection 2	112 records	79
ENGR 2103Engineering Foundations Studio III	312 records	71
ENGR 1101Introduction to Human-Centered Engineering	310 records	74

The line

All 13 items · means across 11 records

The Professor4 items

Clearly Explains MaterialThe instructor was effective at creating an understanding of difficult subject matter.

9453rd pctl

Available Outside of ClassThe instructor was available for help outside of class.

9134th pctl

Brings Out Your Best WorkThe instructor motivated me to do my best work.

9347th pctl

Sparked My InterestThe course stimulated my interest in the subject matter.

9557th pctl

The Course3 items

Well-Organized CourseThe course was well organized.

9148th pctl

Clear Learning GoalsThe learning objectives for the course were clear.

9145th pctl

Useful Beyond the CourseWhat I learned is applicable beyond this course.

9141st pctl

Assignments & Feedback3 items

Assignments Help You LearnAssignments and exams contributed to my learning.

9047th pctl

Gives Feedback PromptlyI received feedback on my work in a timely manner.

9148th pctl

Meaningful FeedbackThe feedback I received on my work was meaningful.

9250th pctl

Workload, difficulty & attendanceNot ratings

WorkloadHow much work the course took outside class, on Boston College's five-band scale — the band boundaries are not published, so this is not a number of hours.

4025th pctl

Intellectually ChallengingThe course was intellectually challenging.

9049th pctl

Attendance MattersAttending class was necessary to do well in this course.

8521st pctl

Bar length is the rank against every comparable record we hold, not the raw score: BC's questions all have a median around 4.5, so a raw-scale bar would be nearly full on every row and would tell you nothing. Every bar is one ink colour — nothing here is graded green or red. The hatched bars are not ratings at all: a higher number on either describes a different course, not a better one.

Game log

11 sections · newest first

Instructor	Term	Sec	Instr	Course	Work
Amin Mohebbi	Spring 2026	01	92	87	40
Amin Mohebbi	Spring 2026	02	94	89	40
Amin Mohebbi	Fall 2025	01	94	91	40
Amin Mohebbi	Fall 2025	02	93	87	40
Amin Mohebbi	Spring 2025	01	93	84	40
Amin Mohebbi	Spring 2025	02	96	88	40
Amin Mohebbi	Fall 2024	01	86	80	40
Amin Mohebbi	Fall 2024	02	87	84	40
Amin Mohebbi	Spring 2024	01	88	83	40
Amin Mohebbi	Spring 2024	02	90	83	40
Amin Mohebbi	Spring 2024	03	90	90	40

How to read this boardInstructors are ranked on their record in this class only, never on their average across everything they teach. Scores are out of 100 — Boston College's 1–5 agreement scale, ×20, the way these numbers were printed for years. Workload is BC's own five-band figure, not a number of hours, and is shown as a rank. A dash means the question was not reported, and is never a zero.