MS in Data Science: self-paced, 10 months, under $10k

Discussion in 'IT and Computer-Related Degrees' started by Seylan, Jun 5, 2020.

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  1. Dustin

    Dustin Active Member

    The first 3 courses require no purchased textbook but provide links to free resources. The first course is made up of 6 modules:
    • Intro to Data Science
    • IPython
    • NumPy
    • Pandas
    • Matplotlib + Seaborn
    They use a series of professor-recorded videos with embedded quizzes and an exam at the end of each module. It's not proctored (yet) but the syllabus provides the option for them to implement proctoring. You must score 80% or higher on the previous quiz(zes) to be eligible to write the next one, and you can repeat them until you get 100. There are assignments required at different points in the course, and you only get one shot at those.

    The video lectures are short (10-20 minutes each) and total about 2 hours per module, I haven't gotten to a quiz yet. You have until the end of the semester to submit (so in this case Feb 28). The content included here looks like most of my DataCamp Data Analyst with Python course I took (with the exception of basic stats which is covered in the next course.) In the first module is an introduction to Google Colab which I'd never heard of, but allows you to offload your processing to Google servers, and otherwise is identical to Jupyter notebooks if you're at all familiar with those.
     
  2. sube

    sube New Member


    Thanks, that's interesting. It sounds similar to taking a course on Coursera or one of the other MOOCs since it's self-paced and exams and quizzes are embedded. Do you have to do any projects with other students or post in discussion boards? I've never heard of Google Colab either but I will check it out. Is there any interaction with the professor or do you only contact him/her if you have a question?
     
  3. Dustin

    Dustin Active Member

    Discussion boards are pervasive. There is a parent MSDS "course" with a discussion board for the whole program. Each module has a discussion board (e.g. NumPy discussion board for questions about that module.) Each course has an overall course discussion board. And there is an Eastern University discord, unsanctioned but promoted by the professors (and run by students.) Discussion posts are optional but if you provide 10 substantive replies to content-related questions, you're eligible for a 2.5% boost to your letter grade.

    There are 2 capstone courses, an Ethics in Data Science project where you develop a proposal and learn about how to do ethical data science projects (this is the second-to-last course) and a capstone where you develop your proposal into an actual project. You can collaborate and study with each other throughout the program but don't have to. The capstone can be done in groups but doesn't have to be.

    There are 2 Graduate Assistants in each course who got an A in the course previously and have strong communication skills. In exchange for being a GA in a course, they get a tuition rebate for another course. They answer questions on the discussion boards, and the Professors make themselves available via email generally. The course materials are all recorded lectures by the professor, so in that way there is some interaction, but generally you contact them if you have questions.

    All in all, they're very flexible.
     
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  4. Dustin

    Dustin Active Member

    Here's what the lectures look like. They're all recorded, and they use Jupyter to show you the code, talk about it and then show you immediately how the output changes. I really like the format.
     

    Attached Files:

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  5. JoshD

    JoshD Active Member

    Jupyter is not bad but I prefer Spyder. Probably because it very much resembles RStudio in appearance and use. Lol
     
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  6. sube

    sube New Member

    I saw your other posts about Quantic. You're a busy guy! I had never heard of that one, so I'm taking the free courses there now. I like their learning model and format. Going through the class is actually fun! Anyway, thanks for posting all this info on Eastern. I'm approaching the end of my career so getting a master's is not something I really need at this point and I'm not sure I can justify spending the money, but I will think about it more before I make a final decision. How would you rate the rigor so far or is it too soon to say? Are they starting you off with the basics?
     
  7. Dustin

    Dustin Active Member

    It does starts with the basics, but it feels like there's a bit of a learning curve for people not familiar with programming. I know basic Python, so it's mostly about getting re-familiarized. Too early to say the rigor. It definitely hits all of the topics for someone with no background in data science: Python, NumPy, matplotlib, seaborn, IPython, how to use Jupyter, R, descriptive statistics, probability, multiple and logistic regression, Qlik, Tableau, other regression and classification techniques, SQL, database management and cleaning data, k-nearest neighbor, SVM, decision trees, PCA, neural networks, deep learning, and two capstone courses.

    But with that many topics covered, I think the bigger issue is that it's hard to get indepth in any of those topics in 7 week courses.
     
  8. Dustin

    Dustin Active Member

    I completed my first "exam" (to differentiate it from the non-credit quizzes.) It's 50 questions, auto-graded and scored immediately. A mix of fill in the blank and multiple choice.

    Very tough. Very little opportunity to guess. You have to really know the material.

    I got a 74 on my first try and an 84 on my second. Someone on the Discord mentioned it took them 10 tries to get 80%+.

    At least one student was actively dropping out. He was in the first conort and doing 2 courses at a time so he was 60% through (January is the 3rd semester they've been offering the program) but decided to switch.

    He had considered WGU, GA Tech, and the other usual suspects but I'm not sure where he decided to move, but he was leaving data science.
     
  9. sube

    sube New Member

    Hmmm, that's interesting. It doesn't seem like this is really for an absolute beginner (as I am) so I'm going to pass. I really only need business analytics, not data science, so I'm going to look into that, but I'm intrigued by the Quantic program. I'll post something in that thread since this one should just be for data science.
     
  10. Dustin

    Dustin Active Member

    I do hope you find a good program for you. I was worried I couldn't find a program that didn't require Calculus and Linear Algebra. I know that those are important to understand what's happening under the hood but data scientists are often using libraries and need to understand how to use a library but not necessarily how to build. It's practitioner vs researcher.
     

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