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Thoughts about my MS Data Science Statement of Purpose


ksssh 1 / 3  
Sep 27, 2020   #1

to achieve academic success as a graduate student at the University of California



In a rapidly developing world with an enormously increasing number of data and computational efficiency, data science appears to be a key to solve complex issues the world is facing and improve our society further. I discovered my love for data science through academic training and how I could transform the knowledge I gained from classes to improve modern technology. My goal is to deploy more advanced products or services with data to benefit as many people as possible. Developing models to process with various types and inconsistent data is a challenge that I am determined to undertake. I believe the advancements in Data Science will be revolutionary in how data can be exploited in many different and various industries and how data can be designed to mitigate risk in each industry.

My passion for mathematics started in high school. I always questioned myself "why do we need to learn about concepts of derivatives and integrals?" With this intense curiosity, I decided to major in Applied Mathematics to find the right answer. As I took abstract courses, 'Numerical Analysis' and 'Linear Algebra', I could adequately find the satisfying answer and applications by constantly asking questions about my misinterpretation to professors and classmates until I fully comprehended. In addition, I passionately supported and taught other classmates who had the same question I had by explaining what they misunderstood step by step.

Hence, I could improve my mathematical knowledge more rigorously, such as how Newton's method quickly approximates optimal solutions for different models, Matrix Factorization estimates hidden or latent features in models, and the concept of Separating Hyperplane Theorem is applied in Support Vector Machine. As I found more mathematical applications and grasped the abstract concepts, I successfully transformed mathematical knowledge into Machine Learning theory to optimize the model and communicated effectively.

By choosing Applied Mathematics as my major at the University of California, Berkeley, I had great exposure to the field of statistics and immediately fell in love with it because the application of statistics was more discernible and I could intertwine the two fields to get my hands on the data. As I underwent advanced and project-based statistical coursework, I became competent in Python and R and produced statistically appropriate projects. In my first group programming project, I practiced collaborative programming and project management through Github. I was responsible for building a stratified random permutation test to verify computational answers to scientific questions using Hypothesis Test and building test functions with 99% code coverage in Python. Throughout the project, I improved quantitative storytelling and deeply understood how important it is to produce consistent code and reproducible results. I also learned to design robust statistical data analysis from data collection, data validation using statistical tests, and Poisson regression modeling within a team efficiently.

In addition, after graduating from my university, I participated in a Data Science Certificate program to continuously solve real-world data-driven problems and to keep myself with the latest trends in Data Science and Machine Learning. Through the certificate program, I could thoroughly scrutinize my learnings and construct end-to-end Machine Learning projects alone. As I developed the Artists Recommendation System, I could understand how customer churns hugely affect a company's revenue and how important it is to keep users as many as possible to boost a company's profit. By gathering more artists' information using Spotify API and exploring how Netflix implemented its own recommendation system using Matrix Factorization, I was able to determine an optimal way to retain users for digital streaming platforms as well as the characteristics of the recommendation system that would make it more likely to stand out.

Moreover, to gain basic knowledge of how deep learning is applied in a computer vision and to efficiently apply the advanced Machine Learning, I implemented Pokédex, which classified given Pokémons. First, I experimented to summarize each image with the Histogram of Oriented Gradients and then applied the Support Vector Classifier to summarized images. However, the result was not satisfying due to limited data. So, I ambitiously researched about Convolutional Neural Network and learned to implement it with Keras. As I applied image augmentation on the limited data with Keras and trained the CNN model through a cloud computing system, I could boost my accuracy and reduce the high false-positive rate. These projects not only taught me how to effectively answer business-related problems but also how to consistently research to improve the results significantly.

Apart from my academic and research endeavors, I believe delivering knowledge flexibly to non-technical people is as important as the research behind it. As Data Scientists will work with various departments and agencies, I practice explaining highly technical terms in-detail, but more approachable to non-technical peers by publishing presentations with descriptive statistics and clear visualization. During my graduate studies, I want to gain more publishing experience through cooperation with different departments and students.

I aim to deploy many different types of Machine Learning models not only to solve business-related problems for companies but also to benefit as many as people possible to free from criminal concern and live in a safer environment. Since security cameras tend to have poor resolution, it is very challenging to accuse suspects based on the footage. I want to leverage Machine Learning models to identify unsolved criminal cases to improve scientific investigations and to offer comfort to the bereaved family. To achieve this goal, my next long-term project is improving the quality of low-resolution videos to be clearly visible using Deep Learning. To handle the long-term research with my persistent ambition, I need to have more research experience to deeply understand image/video processing and to efficiently use practical tools required to work with data at scale.

With all these valuable skills demonstrated above, I'm confident that I will continue to achieve academic success as a graduate student at the University of California, Berkeley. With compacted data science and machine learning courses, it will reinforce my knowledge in data science and broaden the perspective of data. Moreover, I will rigorously integrate the skills I learn from the Master of Information and Data Science offered by the University of California, Berkeley to realize my dream.

Obi1 1 / 2  
Sep 27, 2020   #2
Basic Personal Statement includes the following:

1. What are the personal qualities you think you posses that will help you to successfully complete the programme of study

2. Why have you chosen to apply to the preferred University?How does the preferred University aligns with your research goals? How can they help you achieve your goals?

3. How will studying this program help you when you return home(International student) and in your future career?

My candid opinion- I think you went overboard with the experiences, the recruiter might not be a data scientist and eventually don't have a clue about all you are saying, she/he might get bored with it.

The essay is good...Just highlight your highest achievement.
Holt  Educational Consultant - / 10,317 3352  
Sep 28, 2020   #3
For the statement of purpose, you need to go beyond your childhood interests and undergraduate training. Since you are enrolling for a masters course, the first thing you have to prove to the reviewer is that you have the professional experience to assist you as a student. The professional requirement is oftentimes a minimum of 2 years. That is unless you are going into a masters course that does not require work experience as a part of the student qualifications.

You need to convince the reviewer that you have the following foundation in your statement of purpose:
- A professional purpose for your desire to study this course. This could be a desire to improve the current field in your country, a plan to change careers, or part of your training for future promotion

- Explain your relevant educational background based on course requirements of the masters course. Discuss your grades in relation to the subjects you know are relevant to the masters course. Offer an explanation of any low scores you might have and why you believe relevant on the job training has overcome that for you.

- Explain your relevant work experience and how it has prepared you to complete the course. Mention the series of employers you may have had and your work in relation to your time with them.

- If this is a thesis based course, try to explain what your topic will be about and why you believe this research you will be doing shall be of relevance to your course choice, work requirements, and improvement of Data Science in general.

- Discuss why you chose the university and the course. Offer an insight that shows you truly considered the educational possibilities at the university. Cover the course curriculum and training (if any) that will be highly relevant and useful upon your return to work.

Once you focus the essay on the proper requirements for a statement of purpose, the written interview should have information that will work in your favor during the applicant consideration process.
OP ksssh 1 / 3  
Dec 14, 2020   #4
Merged:

SOP for MS in Data Science - passion for mathematics



Statement of purpose
Any comments/thoughts will be helpful!

We're now living in a rapidly developing world with its enormous and increasing amount of data and computational efficiency. In this context, data science appears to be the key to solving complex phenomena the world is facing, such as the current COVID-19 pandemic and thereby can help improve our society still further. I discovered my love for data science during academic training and with the realization that I could transform the knowledge I was gaining from my classes to improving modern technology.

My goal now is to deploy ever more advanced statistical models using data to benefit and explain complex issues clearly as many people as possible. Developing practical models to use to process various types and handle inconsistent data is a challenge that I am both eager and determined to undertake. I believe these advancements in data science will be revolutionary in how data can be exploited in many different and various domain fields, and thus can be better designed and utilized to mitigate risk in the fields.

My passion for mathematics began in high school. I always was asking myself "Why do we need to learn about concepts related to derivatives and integrals?" Given this intense curiosity, I decided to major in Applied Mathematics to find the right answer. I took the abstract courses, such as 'Numerical Analysis' and 'Linear Algebra', to find the answer and the right applications by constantly asking questions about my misinterpretations of my professors and classmate. I wanted to fully comprehend what I was learning. I also passionately supported and taught classmates who had the same questions by trying to explain what they misunderstood step by step.

Based on my academic experience and self-training, I am now convinced to improve my mathematical knowledge in rigorous ways, such as learning how Newton's method quickly approximates optimal solutions for different models, Matrix Factorization estimates hidden or latent features in models, and how the concept of Separating Hyperplane Theorem is applied in a Support Vector Machine. As I learned more mathematical applications and grasped new abstract concepts, I successfully transformed my mathematical knowledge into Machine Learning theory to optimize the model and communicate the theory and its applications more effectively.

By choosing Applied Mathematics as my major at XXX University, I gained remarkable and excellent exposure to the field of statistics. I immediately fell in love with the field because the application of statistics was so discernible, and I could dovetail the two fields to my greater satisfaction and get my hands on data. As I completed my advanced and project-based statistical coursework, I became competent in Python and R and produced statistically robust projects.

In my first group programming project, I practiced collaborative programming and project management using Github. I was responsible for building a stratified random permutation test to verify computational answers to different scientific questions using Hypothesis Test and building test functions with 99% code coverage in Python. Throughout the project, I improved my quantitative storytelling and deeply understood how important it is to produce consistent code and reproducible results. I also learned to design robust statistical data analysis from data acquisition, undertake data validation using statistical tests, and undertake statistical modeling efficiently within a team. The results of the project exceeded all expectations and each member gained a competitive grade.

After graduation from XXX University, I participated in an online Data Science Certificate program from XXX to continue to solve real-world data-driven problems, which provide a great opportunity for me to keep up with the latest trends in data science and machine learning. In this certificate program, I thoroughly scrutinized my learning process and solely constructed end-to-end machine learning projects. I constructed the recommendation system that expanded users' listening behaviors based on their past favorite artists and songs. By exploring how Netflix implements its own recommendation system and reading its research paper deeply, I was able to develop a more optimal way to build my recommendation system users on digital streaming platforms. I also determined the characteristics of the recommendation system that can make that system more likely to stand out.

Moreover, to gain a deeper knowledge of how Deep Learning is applied in a computer vision and to efficiently apply advanced Machine Learning, I participated in research a project related to the Ride-Hailing System at the Department of Transportation and Civil Engineering at XXX University. I implemented and constructed Convolutional Neural Network (CNN) to predict how ride-hailing demand changes temporal-spatially and thus later to apply Dynamic Pricing for mobility services. This ongoing experience has not only taught me how to effectively solve social issues with consumers, but also how to consistently research in order to improve my outcomes significantly.

Apart from my intriguing academic and research endeavors, I believe delivering knowledge flexibly to non-technical people is as important as the research behind that knowledge. Since data scientists work with various departments and agencies, I practiced explaining highly technical terms in-detail, but in a more approachable way to non-technical peers by publishing my presentations with descriptive statistics and clear visualization. During my graduate studies, I plan to gain more publishing experience through cooperation with different departments and personnel with diverse backgrounds. The term "team science" applies equally well to data science, and I embrace all that it means for my future successful career, working effectively with others from different viewpoints and perspectives.

-(Included to explain what I would want to gain from MS program) I also plan to deploy many different types of machine learning models not only to solve business-related (want to change it more academically way) problems, but also to benefit as many as people as possible to help free them from criminal concerns and live in a safer environment. For example, many crimes are observed on surveillance video and surveillance video footage can offer very significant support for solving criminal cases. However, this strong evidence can lose its effect because the footage captured from security cameras tends to have low resolution and poor visuality. Hence, it is challenging to identify suspects with that kind of footage and could fail in court and legal cases. I want to leverage machine learning models to retrieve additional evidence by developing a super resolution reconstruction method to solve historical unsolved criminal cases and improve scientific investigations and thus offer comfort to bereaved families. To achieve this goal, my next long-term project is to improve the quality of low-resolution videos, so they are clearly visible using Deep Learning. To handle such long-term research with my persistency and ambition, I need more research experience, so that I can deeply understand image/video processing and to efficiently use practical tools required to work with data on that scale.

(Should I include the paragraph above?)

Given all my valuable skills, as demonstrated above, I am confident that I will continue to achieve academic success as a graduate student at XXX Unviersity. My academia experience and educational training have prepared me for success in classes such as "Applied Machine Learning", "Statistics for Data Science and Research Design" and "Application for Data and Analysis". In compacted data science and machine learning courses, I will reinforce my knowledge and broaden my perspectives in these important scientific areas. Moreover, I plan to rigorously integrate the skills that I learn from "Deep Learning in the Cloud and at the Edge" to realize my dream career and life objectives. I look forward getting involved in your vibrant and diverse student community with my unique culture and passion. I am ready and determined to complete my MIDS program at XXX to strengthen my career to benefit as many people as possible with data-driven approach. Thank you for your kind consideration.
Holt  Educational Consultant - / 10,317 3352  
Dec 14, 2020   #5
Remove paragraph 3 and 4. There is no need to go all the way back to high school. The discussion should focus only on your college and professional interests in relation to the masters course. Your presentation will be stronger and more focused without it.

Include the discussion about what you want to gain from the program, but frame it in a study plan / thesis proposal presentation. The SOP usually requires that discussion because your main purpose should indicate how you plan to gain the skills necessary to help you realize your purpose. Revise the full paragraph that you presented as I indicated.

Your last paragraph should be less about your skills, as that is no longer a part of this discussion, but more of the reasons why you chose to study at the university. This has to show that you are familiar with the university course offerings, potential training programs you can participate in, professors of note, or any similar references that will inform the reviewer about how familiar you are with the university requirements and that you chose their university for a specific reason or for specific reasons.


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