George Leland Bach Teaching Award, 2026
Evaluations
What students say
Every Carnegie Mellon course I have taught since Fall 2023, rated by the students who took it: 727 responses across 24 sections of 8 courses, with 76% of students responding. The numbers are the official faculty course evaluations. The quotes are theirs.
By the numbers
The short version
Every section, in order
Term by term
One dot per section. Bigger dots had more respondents. The line is the average across the sections taught that term. I started as an adjunct in Fall 2023 with two sections of Data Mining; the rest followed as a full-time faculty member.
| Term | Course | Program | Responses | Rate | Teaching | Course | Respect |
|---|---|---|---|---|---|---|---|
| Fall 2023 | Data Mining (A2) | MBA | 24 / 48 | 50% | 3.88 | 3.88 | 4.42 |
| Fall 2023 | Data Mining (B2) | MBA | 5 / 11 | 46% | 3.60 | 3.20 | 4.20 |
| Spring 2024 | Data Mining (M4) | MBA | 32 / 46 | 70% | 4.41 | 4.34 | 4.88 |
| Spring 2024 | Data Visualization (E4) | MBA | 11 / 14 | 79% | 4.55 | 4.45 | 5.00 |
| Fall 2024 | Data Mining (A2) | MBA | 21 / 24 | 88% | 4.62 | 4.52 | 4.76 |
| Fall 2024 | Data Mining (B2) | MBA | 5 / 8 | 62% | 4.40 | 4.60 | 4.60 |
| Fall 2024 | Introduction to Probability and Statistics (A1) | MSBA | 58 / 61 | 95% | 4.14 | 4.14 | 4.91 |
| Fall 2024 | Introduction to Probability and Statistics (B1) | MSBA | 62 / 62 | 100% | 4.06 | 4.03 | 4.74 |
| Spring 2025 | Data Mining (M4) | MBA | 34 / 41 | 83% | 4.65 | 4.59 | 4.91 |
| Spring 2025 | Data Visualization (A3) | MBA | 35 / 55 | 64% | 4.60 | 4.63 | 4.91 |
| Spring 2025 | Data Visualization (M3) | MBA | 40 / 46 | 87% | 4.75 | 4.70 | 4.93 |
| Spring 2025 | Data Exploration and Visualization (M3) | MSBA | 21 / 27 | 78% | 4.86 | 4.62 | 4.95 |
| Fall 2025 | Data Mining (A2) | MBA | 35 / 46 | 76% | 4.74 | 4.77 | 4.89 |
| Fall 2025 | Data Mining (M2) | MBA | 20 / 26 | 77% | 4.90 | 4.90 | 4.95 |
| Fall 2025 | AI Methods for Social and Visual Data (A1) | MBA | 26 / 29 | 90% | 4.73 | 4.77 | 5.00 |
| Fall 2025 | Data Visualization (A2) | MBA | 40 / 51 | 78% | 4.85 | 4.88 | 4.95 |
| Fall 2025 | Managing and Assessing Tech Talent (W2) | Undergraduate | 8 / 13 | 62% | 4.75 | 4.75 | 5.00 |
| Spring 2026 | Data Visualization (A3) | MBA | 33 / 48 | 69% | 4.88 | 4.91 | 5.00 |
| Spring 2026 | Data Visualization (M3) | MBA | 33 / 49 | 67% | 4.88 | 4.94 | 4.94 |
| Spring 2026 | Data Exploration and Visualization (M3) | MSBA | 24 / 34 | 71% | 4.96 | 4.92 | 5.00 |
| Spring 2026 | Machine Learning for Business Applications (A4) | MSBA | 47 / 58 | 81% | 4.45 | 4.43 | 4.70 |
| Spring 2026 | Machine Learning for Business Applications (B4) | MSBA | 54 / 66 | 82% | 4.78 | 4.80 | 4.89 |
| Spring 2026 | Machine Learning Foundations with Python (B) | Heinz | 40 / 47 | 85% | 4.80 | 4.80 | 4.90 |
| Summer 2026 | AI Methods for Social and Visual Data (M5) | MBA | 19 / 46 | 41% | 4.16 | 4.16 | 4.63 |
By course
Course by course
Each course on its own line: every section as a dot, and the response-weighted average circled in pen. The program filter above applies here too.
Taught again, rated higher
The second time around
The courses I have taught three times or more. Each one got better as I rebuilt it: Data Mining moved from R to Python and a lab-first format, Data Visualization narrowed to one tool, Tableau, taught properly.
fig. 3 · the line is the term average; dots are sections; the axis starts at zero
Item by item
Where the change came from
The evaluation asks nine questions. Gray is my first year, Fall 2023 to Spring 2024. Blue is the latest, Fall 2025 to Summer 2026. Every item moved the same direction.
Rated excellent
How many picked the top box
For the Data Visualization sections I have the full distribution, not just the mean. In Spring 2026, nine in ten students rated the teaching excellent, and nobody rated it below average.
316 written comments
What comes up
I tagged every written comment, the critical ones included. Practical and useful at work comes up most. Pace comes up too: the minis are seven weeks, and that is the main thing students ask me to change. The red bars are the asks.
In their words
What they wrote
Comments from the evaluations, by course. They are anonymous and unedited apart from trimming for length. The full set, suggestions included, is what I read at the end of every mini.
Data Mining
4.51 average teaching rating · 8 sections · 176 responses
How to teach a very technical course like data mining to most students who have never touched coding? Just ask Prof Collier. He was outstanding. The structure of the course was spectacular.
This is definitely one of the top 3 best courses I have taken at CMU.
Loved this class and the acceptance and encouragement to use AI as it is a tool and not a mode of cheating.
His class has been one of my favorites throughout my MBA. I wish I had taken it earlier, and it truly feels like I'll be using these skills for a long time in my future career.
His insights are sharp and highly practical, and his classes are well-organized and efficient.
Professor Collier has a very deep understanding of the material, but more importantly, he has the ability to explain it so anyone can understand.
THE GOAT OF ANALYTICS AT TEPPER!!!
Data Visualization
4.78 average teaching rating · 6 sections · 192 responses
One of the most practical classes I've taken at Tepper, I actually learned something I could take to work today and use.
This was truly the best class I have had at Tepper. No other class has been as good as this.
It feels like you're discovering together what are good and bad practices. The format forces you to think and judge before learning best practices.
He made everything idiot proof and really met people where they were at. He is so knowledgeable & cool. 10/10
He is a great teacher, very patient, helpful and understanding of different perspectives.
Introduction to Probability and Statistics
4.10 average teaching rating · 2 sections · 120 responses
He has listened to the midpoint feedback of students and adjusted the teaching style based from that.
He shows respect and care to every single student, and he uses real interview questions as brain teasers at the beginning of every class.
He takes the time after class to answer everyone's doubts, not only limited to course but also extended to professional development.
Data Exploration and Visualization
4.91 average teaching rating · 2 sections · 45 responses
Have already convinced my work to purchase the software for me and I am using it at work now.
Professor Collier is one of the most passionate professors I've come across!
The professor's undeniable enthusiasm for the topics he was sharing, whether it was experiments or fonts!
AI Methods for Social and Visual Data
4.49 average teaching rating · 2 sections · 45 responses
This was one of the best courses I've taken at Tepper, which is especially impressive since this is the first time Prof Collier is teaching it.
Some instructors go years without changing a course, but I can tell he is laser focused on making sure this is accurate and up-to-date.
This course belongs in the core curriculum. Collier is equipping us with a set of tools to get far more out of AI than peers and colleagues.
Professor Collier did an excellent job of making complex technical concepts accessible and engaging.
Machine Learning for Business Applications
4.63 average teaching rating · 2 sections · 101 responses
He showed many examples of how academic ideas connect to real work, and encourages hands-on tasks with real tools like AWS.
Probably the most relevant class I took.
Ben is my favorite professor of all time, please keep up the great work!
Machine Learning Foundations with Python
4.80 average teaching rating · 1 section · 40 responses
Dr. Collier made me actually care about this course. I was not excited about it and felt like it was going to be massively over my head.
One of the best courses I have taken at Heinz. He does a wonderful job of explaining ML topics to technical and non-technical students alike.
Thank you for making this class project based, which helps me prove to my future employer that I can actually use these skills.
I LOVE THIS COURSE, PLEASE STAY IN THIS COURSE
Notes that arrived unasked
In the inbox
Evaluations are asked for. These were not: 86 emails and notes from students, alumni, executive education participants and colleagues, saved since 2013. A few of them, with names left off.
Storytelling through data has come up in so many of my conversations with hiring managers! Several have remarked in their feedback that it's helped distinguish me from other candidates.
I've talked to many students at Tepper and they all rave about your data visualization class.
It has been my favorite so far in the program and I have already convinced my employer to let me purchase a Tableau license at work.
This is the first time in my three years at Tepper that data has actually felt "fun" for me, especially as someone who leans more toward soft skills.
You made the 8 AMs bearable and I had a good time with a subject I used to be uncomfortable with.
I work in finance and have no real experience in this area, but have wanted to get into Python for some time. You made it both approachable and interesting.
Before starting I had heard so many of the ML terms we learned in class tossed around without understanding them. I can now talk the talk.
I don't think I've ever had a professor take this much initiative in our learning, so that is much appreciated.
My performance was all thanks to your excellent teaching style and your ability to break down complex problems into smaller, more manageable sections.
The course content was clear and useful, and I appreciated how everything was relevant without any unnecessary information. You're honestly the most considerate professor I've ever had.
Data Mining was by far my favorite MBA course. That course emphasized exactly the type of technical skills I hoped to learn when coming to Tepper.
I just received an offer of an Analyst position. I wanted to express my sincere gratitude for your guidance and support throughout the process!
I actually used some of what we learned at work! I also just appreciated how laid out everything was and easy to follow for someone without a coding background!
I learnt a lot from this course, and I loved your teaching style. Until now, this has been the best course I've taken at CMU.
As a trainer myself, I need to tell you that you were very strong in terms of handling a relatively tough highly diversified audience.
Across all three courses, I found the structure and progression of the material especially impactful. These courses have been among the most formative of my time at Tepper.
Before Tepper
Carnegie Mellon Qatar, 2012 to 2016
My first faculty job was at Carnegie Mellon's campus in Doha, teaching undergraduates organizational behavior, negotiation, research methods, digital marketing and consulting: 19 sections, 428 responses, an average teaching rating of 4.43.
Read with care
How to read these numbers
Carnegie Mellon asks every student to rate ten items at the end of a course, from 1 (poor) to 5 (excellent). The two that matter most are the overall rating of the teaching and the overall rating of the course. I show the teaching rating unless you pick another item.
Small sections swing more. A section with five respondents can move half a point on one person's view, so the dots are sized by responses and the lines are weighted by them. Response rates matter too: mine average above 75 percent, so these are most of the students, not the loudest.
What is not here: the school's comparison averages, which are internal, and the critical comments in full. Those I keep and act on, and the biggest change they produced was recording every class and posting the videos.