There are a lot of ways to ruin your statement of purpose. Some of them are “kisses of death.” You mention your tendency for road rage or claim that you want to “save the world with AI” and the admissions committee rejects you without blinking. Then there are more subtle mistakes. These don’t result in immediate rejection — they aren’t kisses of death — but this kind of SOP mistake can have an effect that, in my opinion, isn’t much better: they make you look like someone who doesn’t think.
(Not exactly a winning strategy for grad school admissions.)
One of these mistakes is astonishingly common. Graduates from top universities aren’t immune. I can name at least two dozen Harvard and Stanford graduates who made this mistake in the last few years. In fact, after crunching my 2023 data, I realized that I encountered this mistake in 90% of the SOPs I read this year.
That’s right: if you’re reading this, chances are overwhelming that you made this mistake, or that you soon will…unless we can learn how to write like someone who really thinks.
Let’s do exactly that.
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The Problem
In the SOP Starter Kits (for master’s and PhD applicants), we learn that all great statements of purpose answer a question: how will this graduate program help me reach my specific career goal? We answer this question with a “study plan” — an outline of the courses we’ll take, the professors we’ll work with, and the labs we’ll join, along with a sufficient explanation of why these resources matter to us personally.
Everyone finds the first part easy. It’s not hard to name the classes we want to take, right?
But this is exactly why things can get tricky. It isn’t difficult to name classes. Anyone with an Internet connection can Google Stanford’s MSCS program and copy-paste the titles of their courses. Doing so isn’t a magic bullet for your application essay. It’s a start, yes. But if this is all you do in your SOP — list classes — you haven’t proven that you’re ready for graduate school. All you’ve proven is that you have an Internet connection.
We have to go further.
And this is where things start to get ugly.
Smart Thinking Starts Here
A good friend of mine was…well, let’s call him a “recruiter”…at Harvard for twenty-five years. It was his job to find the most spectacular scholars in the world and make sure Harvard knew about them long before they even applied. I’ve spent untold hours with him discussing college admissions, and he’s very fond of repeating this aphorism:
“Harvard doesn’t care what you want to do,” he’d tell me. “They care about why you want to do it.” That’s how they distinguish the normies from the superstars, the NPCs from the scholars with potential to change the world. Are you or are you not capable of explaining why you want to study in this grad program? That’s the test. Thus, the goal for your SOP’s “study plan” is not just to list courses and faculty, but to explain why they’ll be important for you.
Why do you want to take CS246: Mining Massive Data Sets?
Why do you want to take API-318 Thinking Analytically in an Uncertain World?
The funny thing is, when I ask these questions, no one has a problem coming up with an answer. Literally everyone can provide an answer.
The problem is the answers they give.
Don’t Teach the Teacher
If we visit the course page for Stanford’s CS246: Mining Massive Data Sets, we find the following convenient description:
The course will discuss data mining and machine learning algorithms for analyzing very large amounts of data. The emphasis will be on MapReduce and Spark as tools for creating parallel algorithms that can process very large amounts of data.
Topics include: Frequent itemsets and Association rules, Near Neighbor Search in High Dimensional Data, Locality Sensitive Hashing (LSH), Dimensionality reduction, Recommendation Systems, Clustering, Link Analysis, Large-scale Supervised Machine Learning, Data streams, Mining the Web for Structured Data, Web Advertising.
When I ask an applicant why they want to take this course, most of them — a full 90% in 2023 — will say, “Because…” and then just repeat the course description.
“Why do you want to take CS246: Mining Massive Data Sets?”
“Because it will teach me data mining and machine learning algorithms for analyzing very large amounts of data.”
Woof.
This isn’t an answer. This doesn’t explain why you want to take the course. It explains what the course teaches — which, I assure you, is something Stanford already knows.
Often students will hear me say, “Don’t teach the teacher,” and this is precisely what I mean. If you repeat what a university has written on their own website, you aren’t proving yourself to be some brilliant detective who’s capable of recognizing esoteric patterns in the mathematical architecture of the universe. You’re proving that you have the deductive abilities of a parrot.
Because parrots don’t think.
They just repeat.
What’s worse, copy-pasting a course description doesn’t tell the admissions reader anything about you individually. Even if you copy-paste a fancy sub-topic like “Locality Sensitive Hashing” or “Dimensionality Reduction,” you aren’t helping the admissions committee understand you because every student who takes the class will learn the same things.
Perhaps you assume that by mentioning these subtopics, you’re giving the reader insight into the academic problems that interest you. But that’s not true, because you’ve still failed the test my friend from Harvard described above:
It’s not about the what, but the why.
How to Fix This SOP Mistake
Imagine you and I are engaging in some nifty Socratic dialectic. Our conversation goes like this:
“Why do you want to take CS246: Mining Massive Data Sets?”
“Because it will teach me data mining and machine learning algorithms for analyzing very large amounts of data.”
“Why do you want to learn about data mining and ML algorithms for large amounts of data?”
“Because I want to learn how to use Locality Sensitive Hashing and Dimensionality Reduction.”
“Why do you want to learn to use Locality Sensitive Hashing and Dimensionality Reduction?”
“Because I want to work in Computational Advertising.”
“Why are Locality Sensitive Hashing and Dimensionality Reduction important for working in Computational Advertising?”
“I’m not really sure, but Google lists them on their job descriptions for Google Ads Machine Learning Software Engineers.”
Ah ha! Now, we’re getting somewhere. Now, we’ve actually conveyed some information that’s uniquely about you: your career goals. We understand what you aim to achieve and how this course will prepare you to achieve it. But since an SOP isn’t a long, awkward conversation but a test to see how well you can write, let’s condense this thought process.
“Why do you want to take CS246: Mining Massive Data Sets?”
“Because I want to work as an ML engineer for online advertising, and to do so, I need expertise in topics like Locality Sensitive Hashing and Dimensionality Reduction.”
Boom! Wonderful! That’s how you explain why. You aren’t telling the reader what the course teaches, but how it relates to your unique goals. Now, let’s condense this even further.
“In courses like CS246: Mining Massive Data Sets, I hope to gain expertise in topics like Locality Sensitive Hashing and Dimensionality Reduction, which are essential for ML engineering in online advertising.”
Congratulations. With one sentence, you’ve leaped beyond 90% of applicants. You’ve proven that you’re not a parrot nor a copy-paste wizard, but someone with goals, someone who actually thinks. Now, go repeat that process for every other course you want to mention in your SOP.
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Learn the “4 Questions” every SOP must answer to earn admission at competitive schools. This guide will tell you what to write, and leave you feeling super confident and ready to hit “submit.”
Examples
In our SOP guide for course-based, non-thesis, professional track master’s programs, we can find an absolutely brilliant example of a student who actually thinks. Let’s take a look at Sherry’s “why this program” section once again:
The Master of Science in Artificial Intelligence program will provide both the technical and business-management skills I need to achieve my goal. Through courses like Intro to Computer Vision (MSAI 329) and Deep Learning (MSAI 407), I hope to gain a comprehensive understanding of computer vision, its current limitations, and how it can be advanced. This will provide the foundation I need to contribute to the development of accurate and robust machine-learning models for image classification in medical diagnosis. Furthermore, Innovate: Medical (MBUS 450) will guide me toward creating business plans that turn medical innovations into achievable ventures, while Financial Foundations for Entrepreneurs (MBUS 382) will provide hands-on experience with the financial accounting necessary for startup businesses — a crucial aspect of my long-term goals. I am also interested in Professor Lucius Fox’s work on self-supervised fine-tuning algorithms, as correcting super-resolution convolutional neural networks could greatly enhance medical-imaging processes. If possible, I would like to explore this or similar topics in my capstone, with Professor Fox as my advisor, and thus gain vital experience applying these technical skills that will be directly relevant for my future career.
Amazing. Four total courses (or five if we include the capstone) and each one is accompanied by a beautifully clear motivation. Sherry is a young woman who thinks.
Here’s another brilliant example from my man, Bennett, who was admitted to six of the top MSDS programs in the U.S.:
Through Gotham University’s Master’s program in Data Science, I hope to further explore how to enhance representation of data minorities in ML models, and thus ensure inclusive healthcare access for the customers I serve. Earning my MBA at Metropolis University taught me how to coordinate the need for quantitative reasoning and human intuition through A/B testing, and I believe the MSDS program will build on that foundation. Mathematical Foundations in Computer Science, for example, will help me build real-time analytics dashboards that account for insurance claim data-entry errors through discrete probabilistic models. In the same vein, elective offerings such as Big Data Analytics and Artificial Intelligence will enable me to choose predictive models and evaluate their accuracy when applied to large data sets — particularly useful when predicting whether an insurance claim will necessitate revisions.
Bravo! There isn’t a single sentence in that entire paragraph that doesn’t work hard to explain how this courswork will prepare Bennett to achieve his career goals.
In fact, this issue of What versus Why pertains to more than just the coursework in our study plans. Consider the following example from Yuxuan, a brilliant graphic designer and painter (and non-native English speaker) who earned admission to 5 fully funded MFA programs. He didn’t mention any courses at all — he focused entirely on the professors with whom he wanted to work:
I am particularly inspired by the work of Professor Karl Banksy. His work often deals with underserved public interest issues, echoing my own pursuit of barrier-free visual experiences. As I create designs for people with achromatopsia, color disorders, and others with visual impairment who are often overlooked in social services, I believe Professor Banksy will be a great mentor. I also feel inspired by Professor Wang Lu, whose research focuses on historical and cultural influence in graphic design. As a Chinese-diaspora artist, I often explore design themes idiosyncratic to Asian culture in my work. I experimented with this in my contribution to “Seeking Plural Narratives,” a recent anthology which sought to examine Eurocentric design and typographic cultures. My pieced discussed Cuban graphic design and its similarities to communist iconography from China. Therefore, I think Professor Lu will be a reliable mentor as I grow my international, multicultural vision for design.
Are Some People Just Not Capable?
Last year, on the r/AskAcademia subreddit, one user asked a painful question: are some people just “incapable” of research? Of course, we’re not talking about research today, but the question hinted at the same problem 90% of students have when writing about their future coursework. They can follow instructions — they can accomplish the what — but they can’t articulate the why. One of the responses was particularly sharp. (You can tell it’s terrifyingly true because everyone was scared to respond.)
See, even PhD applicants have this problem: they can talk about the what, but not the why. Personally, I don’t think there’s anything wrong with these students. They just haven’t taken the time to ask themselves why? Then again, why? And then again, why? …just as you and I and Socrates did above. It certainly takes effort, and it certainly takes time. Luckily, the more you do it, the better you get at skipping the intermediate steps. But working through this mental process is necessary if you want to write an SOP that proves you’re someone who really thinks.
After all, that’s the test, and it’s how you pass it.
To look like someone who really thinks…you have to take the time to really think.
Conclusion on This Too-Common SOP Mistake
Parroting course descriptions is easily the most pernicious problem I see in grad school SOPs. It’s not a kiss of death, and your committee reader may not even be able to articulate why the writing seems lackluster. But make no mistake: if you don’t explain why you want to take a course, or how it’s related to your future goals, you’ll seem like a copy-paste pirate.
Parrot? Pirate?
You get the idea. It’s not a good boat to be on.
Just remember: it’s not about the what, but the why. If you want to learn how to avoid these mistakes in every part of your SOP (just like the brilliant and charming applicants above), consider enrolling in The SOP Formula courses for master’s or PhD applicants. It’s where you’ll find all of my best advice, as well as step-by-step instructions that walk you through the process of really thinking about your dream schools, and how you can leverage them to achieve awesome things.
