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I am a current student in Eastern University’s MS in Data Science program. The program started in August, and is now starting its 6th term. I’m only entering my third term though.
This program provides comprehensive education in all aspects of data science, data visualization and machine learning. I’m really enjoying it! There’s not a lot written about it though, and I’m hoping this will clear some misconceptions up.
Applying to Eastern’s MS in Data Science
First things first: Eastern is a Christian school but you do not need to be Christian to attend. The application, which is free, does ask for your religious affiliation (I chose Agnostic, sorry I didn’t look for Atheist), but it has no bearing on your application.
You’ll need to provide unofficial transcripts at first and then have official transcripts sent. Domestic grads can get admitted and start conditionally with unofficial transcripts, while international students will need their transcripts evaluated by a NACES member like WES.
Since I attended Athabasca University, which is US regionally accredited accredited despite being a Canadian school, I did not need to have my undergrad evaluated (though I did provide an evaluation anyway since I had one.)
You also need to submit a resume. They’ll accept a GPA of 2.5 but prefer a 3.0.
MS in Data Science Curriculum
After getting admitted, I was able to start the first course. There are 10 courses in the program, 3 credits each. At this point I’ve completed DTSC-520 and DTSC-550 and am starting DTSC-650 on Monday. The courses are taken in somewhat of a different order.
- DTSC 520 Fundamentals of Data Science
- DTSC 550 Introduction to Statistical Modeling
- DTSC 575 Principles of Python Programming
- DTSC 650 Data Analytics in R
- DTSC 660 Data and Database Management with SQL
- DTSC 670 Foundations of Machine Learning Models
- DTSC 600 Information Visualization
- DTSC 680 Applied Machine Learning
- DTSC 690 Data Science Capstone: Ethical and Philosophical Issues in Data Science
- DTSC 691 Data Science Capstone: Applied Data Science
DTSC-520 is an introduction to Python and Data Science. DTSC-550 is a statistics course with very basic R. DTSC-575 is an indepth Python programming course. DTSC-650 is an indepth R programming course.
DTSC-660 is a database course using PostgreSQL, while 670 and 680 are deep dives into machine learning, neural networks, and artificial intelligence. DTSC-600 is a data visualization course focusing on Qlik and Tableau.
Finally, DTSC-690 and DTSC-691 are the capstone courses where you build a complete data science project from start to finish to build your portfolio.
It’s a packed program! Each course includes video lessons that are small (2 minutes, 5 minutes, 10 minutes) and you’ll use that to learn the basic material. There are non-credit quizzes throughout, and then exams.
Each course is 7 weeks long, so they are a tight 7 weeks. This is not a cohort program so you can take 1, 2, or 0 courses in each term. You have 5 years to complete the program
The first two courses are 100% exam-based. DTSC-520 includes 4 exams and DTSC-550 includes 5 exams. You can repeat the exams as many times as you need and the highest grade is kept.
You must earn a minimum of 80% in each course to proceed, but again you can repeat the exercises as much as you need.
In the later courses you’ll also have CodeGrade assignments where you submit your code to CodeGrade and it will evaluate it for you. Again, you can resubmit as much as you need.
Learning Management System and Student Support
The degree uses Brightspace as the Learning Management System (LMS), and there are discussion boards throughout the program that help students learn from each other and a Discord server that is student-run is available for instant chats.
Additionally, there is a Graduate Assistant assigned to each course that will answer discussion board posts and provide additional support.
This is perhaps the cheapest MS in Data Science in the United States. Each course is $990 so the total tuition, all in, is $9900! They also accept full financial aid and provide veterans and alumni scholarships/discounts.
I’m really happy with the Eastern MS in Data Science program. I’ve also been a Graduate Assistant for 2 terms and it’s been a wonderful experience. I look forward to moving further in the program.
Are you interested in the Eastern Master of Science in Data Science program? Are you a current student? Let me know!
31 thoughts on “REVIEW: Eastern University Master of Science in Data Science 2021”
I am starting this program on June28, 2021(Summer 2). I will be taking DTSC 520 Fundamentals of Data Science and DTSC 550 Introduction to Statistical Modeling. What are the recommended textbooks for these courses?
I replied to your email as well but just so you know, the first 2 courses have no required textbook but Learning Statistics with R is referenced in 550 and 650 (https://learningstatisticswithr.com/book/).
Hey Dustin I’m considering this program and was wondering what prior experience/degree did you have before and what information would you suggest brushing up on before entering? I’m currently an applied mathematics major with a minor in computer science but took a few more classes then necessary for the minor. At the moment I’m taking a course on R and SAS and I have a few years of programming experience because initially computer science was my major however, I want to make sure I have enough background to succeed if I take this path. Any additional information you could provide would be greatly appreciated!
My Bachelor’s is in Human Services. I have a bit of understanding of statistics but no math past pre-calc. On the programming side I’d done a bit of Python but no R. I think you’re more than prepared. The program really starts gentle. Python is covered in the first course, basic stats in the second, and R in the third (which is the course I just completed.)
Since you probably don’t need to work on your R or your programming, I would brush up on linear algebra if you have a math background since it will come up in the machine learning courses and otherwise you’re more than ready.
I too am starting this program on June 28. I just signed up for the DTSC 520 only. I was not sure the amount of work it takes to complete each course. Thought it was best to ease into it.
I also started the program with just 520. I’d estimate it took me 5 hours per week and I finished in 4 weeks (out of 7.) It’s a gentle course to get started in.
Are there any stats on job placement after completing this degree?
No job placement data is available yet, mostly because the first class only graduates at the end of this term. Once they’ve been out in the workforce for a while they’ll be surveyed as part of data collection for graduate programs mandated by the US Department of Education and then we’ll know.
Hope this helps,
Thank you for your review, this is very helpful. If you could help answer the following, this would help
* What is the total hours of lectures for a course ?
* If I take 3 courses, that means in tight the total duration would be 21 weeks + 7 weeks for the
last 10th course ?
You can only take 2 courses at a time maximum. If you do this, for each term, you will finish in about 10 months. It’s impossible to estimate the time required, because each person comes into the program with a different level of knowledge. I would say that 520 and 550 (the first two courses) have 10-15 hours of video content. You are assessed with a mix of repeatable quizzes and coding assignments and single-submission assignments.
Hope this helps,
Any job placement help?
Graduates have access to Career Services (https://www.eastern.edu/student-life/center-career-development) including the Handbrake job board. An Academic Advising Manager has also joined the MS in DS program and provides information on internships and other resources. There is not an internship as part of the program.
I am exploring the online program and would like to know the following:
1. I am working full time with a young family, how much time each week do I need to spend on completing the course in 10 months?
2. I am based out of Australia, would that impact my participation in discussion boards etc?
3. Do they provide all tools, software, environments etc required to complete the course?
4. Do you think the content covered gives you enough depth to be able to work in a corporate environment/land a job or they are providing the basics and anything advanced is left upto the students?
5. Other universities offer the same course with minimum duration of 18 months, is there any logical reasoning with 10 months course?
1. To do the program in 10 months you will need to take 2 courses at a time. I spent 5-10 hours a week on the first 4 courses and would estimate you’ll need 10-15 hours for the remaining 6 courses. It starts slow and picks up difficulty as you go. There is a suggested course outline that ensures a mix of easier and more difficult (or lighter and heavier) courses.
2. No problem at all being in Australia. The program is fully self-paced and uses virtual proctoring (Respondus LockDown). Different timezones don’t affect anything and we have students in Africa, Australia and other continents enrolled now.
3. The course uses free and open source software, including RStudio and Anaconda Distribution (which installs Python, Jupyter Notebook, and all the libraries you’ll need.) The only recommended expense is buying a few textbooks but the first 3 courses (520, 550, 650) have no textbook needed. The 4th course (575) has a recommended textbook but I just finished that course today, and didn’t need it. I recommend buying the textbook for the database course (660) and the two machine learning courses use the same textbook (670, 680) which I also recommend you purchase, though it’s available online as a PDF.
4. I haven’t gotten to the machine learning courses but I’ve been pretty satisfied with the content so far. Because it is a 30 credit program (where others are 36), and it takes a “Data Science for All” approach where it starts from 0 with regard to statistics and programming, other degrees do provide more specialization which Eastern’s program does not. So, while you will easily be able to learn how to do natural language processing (NLP) or work with Big Data, for example, Eastern’s program does not have courses in these skills where other programs do. I don’t think that affects your employment prospects as long as you understand your limitations.
5. The program is shorter than others for two reasons: One that I already mentioned, the program is 30 credits so it is 2 credits shorter than some other, 36 credit programs. Secondly, Eastern uses accelerated 7 week terms, so that you complete 2 courses in the time it takes to do 1 course in those other programs. That means you can progress a lot faster. I started with 1 course for 520, 550, 650 and then doubled up (650 + 575) and plan to double up again (600 + 670) before going back to single for 680, 690 and 691.
Hope this helps, good luck!
Hi! I would like to know if the program is accredited. Thank you.
Yes, Eastern University is fully regionally accredited. This is the same accreditation the major universities in Pennsylvania have including UPenn (the Ivy League school.)
I was wondering how the name /reputation of Eastern University is regarded by hiring managers if you have applied for any jobs? Are you still able to land interviews? Thanks.
I’m only half way through the program – I actually start my first machine learning course August 30. So unfortunately I’m not sure yet of the program’s reputation in the marketplace.
Thanks for taking the time to craft this review. I’m heading into the program in the Fall1 semester at the end of August and you really have put my mind at ease!
I do have a question regarding the Graduate Assistant role you described. Is that something that students are able to apply for? Or is it something that is assigned to you as part of a later class?
Also, regarding the post degree employment prospects. I’ve found that there are several commercial, industry based certifications that line up with (at least superficially) the course content as you’ve described it. Specifically the Data Science certification from IBM (or Google), and Tensorflow certification from Google. Thus, I wonder if resume padding certifications combined with the resultant portfolio of projects from this degree, and the degree itself, would boost employability as a Data Scientist.
If you have the time, would you take a look and give us your opinion on this?
Thanks again for all the great info and work here!
Looking forward to joining you on this journey.
I apologize for the delay – it’s been a while since I’d checked my comments and I had about 1800 spam ones to remove.
Regarding the GA role – that is something you apply for at the end of each term. You can specify what classes you would like to GA for and they try to play matchmaker, but there are usually more applicants than their are positions available.
I don’t know that certifications on DS-related topics would be that valuable when stacked with the Masters because as you noted there’s overlap between the coursework and the certifications. The main thing I would say would be valuable as far as upskilling is learning machine learning deployment. You’ll learn in the program how to build and evaluate models so you’ll know they’ll work locally, but not necessarily how to wire them up online, or deploy them onto Amazon Web Services (AWS) or other cloud products. This type of training may be more valuable than retreading the course material.
We do learn how to use Git and Github, which is helping for networking and providing code examples to employers. Because I’m now half way through the program (officially my 4th and 5th course will be completed Aug 30 but I’m done the material early), I’ll be writing another article soon that goes more in-depth with each course I’ve done so far.
Thanks for this review, I’m considering the program and have been trying to find someone’s actual experience of it. I’ve taken online programs before and there is always a massive amount of writing and papers. I was hoping this would not be the case with this program. It doesn’t seem like there should be with a more technical subject like this. Can you tell me if there is much writing involved? Thanks!
This program is mostly programming, there is very little writing. There is some writing involved in DTSC-670 and DTSC-680 (very minimal comprehension questions as part of the assignments.) The one exception to this is DTSC-690, the ethics course that is the 9th course in the program. This course is 50% discussion board posts, because you’re reading academic articles on ethics/philosophy of data science, and responding to others. The longest writing assignment in the program is 750 words.
Hope this helps!
Thank you for this helpful review. It looks like you posted this review about 9 months ago. Have you since completed the program? Do you have any insights about the final courses of the program? And more importantly, has the program helped you land a job yet? Thanks one again!
Thanks for writing! I’m actually in my final course and expecting to finish in a few weeks. I’m going to be writing a final article going over my full impressions this month. There are some big changes already in progress that are going to improve the program and make it different than my experience but I do think it’s a great program and the skills I gained are very valuable. I did get a job as a Data Analyst after about a year in the program and have been using my DS skills but I haven’t made the leap to a full Data Scientist position yet.
Thank you for the substantial overview of the MS DS program. I am planning to enroll beginning of 2023 and so I am curious on what would you say the program specializes if you were to describe in general terms?
Hey Dustin, were you able to complete the program? Would love to hear about your final project you did and what that experience was like. How was it graded and how did you “turn it in”?
I’m enrolled in this program and about to take my 3rd course. It’s a very strong program. For those wondering about how Eastern is perceived by hiring managers, I’ll just say any hiring manager is extremely keen on any candidate with an M.S. degree in Data Science. Do the extra work, practice on some personal projects, and build your portfolio in GitHub & you’ll get hired in no time. But you do have to practice & learn the skills. In 7 weeks you get a basic understanding, but it’s up to you to apply what you learn in creative ways.
Like many others here, I am really interested to hear about your experience at Eastern University since you have already graduated by now. I don’t have a background in IT but I am trying to break into the data analyst industry and wonder if this is the right course to take?
I’m comparing the Masters Degree Program with other bootcamps to find the best option considering I do have a MBA already and have been self-learning SQL ?
Thanks for all your help Dustin!
It was a great experience. I feel like I’m ready to tackle end-to-end data science projects. Although I was already working full time and not looking to move, I’m well prepared to talk about and use data science in my current job should the need arise (e.g. occasionally I need to do batch data updates and I write a Python script to do so.) The advantage over a bootcamp is that when you’ve paid your $10K and finished this program you have an accredited Master’s degree. That means more than a bootcamp to a lot of employers.