data science specialization john hopkins reddit

The five courses in this specialization are the very same courses that make up the first half of the Data Science Specialization. Looking forward to it as a supplement to my ongoing undergrad. Check with your institution to learn more. I'm signed up. csharp jupyter … Wrong! If you only want to read and view the course content, you can audit the course for free. P.S. Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. This track should definitely not be considered "data science training" but more of an introduction to what data science can kind of be like. Filled out the rest of my R education through the help options and on Google. The courses are tougher than I thought they would be, but I've learned WAY more than I thought I would! This course is completely online, so there’s no need to show up to a classroom in person. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Don't wait until the last minute. I am interested in learning some things, but I don't care about final grade, formal certification or proving that I really took these classes. I just completed the Data Science Specialization from the Johns Hopkins University (JHU) and here are some of the things learned along the way. If none of that stuff matters, then I would tell you that it's a great place to actually learn good stuff in an environment where you don't necessarily need to concern yourself with externally discernible results. This course will cover the basic ways that data can be obtained. Asking for help - As you might expect, it is practically impossible to provide 1:1 attention to thousands of people signed up for a course. Books, Stack Overflow, YouTube videos, etc.). Personally it doesn't matter to me, and I can't image that it would matter to any employer or potential employer I'd be interested in. How long does it take to complete the Specialization? Last month I took Data Scientist Toolbox and R Programming. Note to JHU: You should seriously consider adding a Natural Language Processing (NLP) module as part of the specialization. People with the necessary skills are scarce, primarily because the discipline is so relatively new. While others will find themselves struggling a lot with the content, delivery pace, quizzes and projects. One of the problems here is that many of your peers are not native English speakers. Made a first step in the right direction and gained some foundational knowledge. Possibly the best class I've taken. If you really want to cheat, it's really, really easy to do so. New comments cannot be posted and votes cannot be cast, More posts from the datascience community. Thankfully, the specialization has a Capstone project that should work just fine if you've been doing the coursework diligently. Start instantly and learn at your own schedule. Currently 4 courses in. © 2020 Coursera Inc. All rights reserved. If you only want to read and view the course content, you can audit the course for free. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The amount of time I dedicated to each course varied. Why the JHU Data Science Specialization? Ive heard the UW specialization is really good and better than the Hopkins course. This Specialization covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research. I'm paying the $49 a course because I really like the MOOC concept and want to help these people to find a business model that works. Note to potential students: Start working on the final project as soon as you can. A ten-course introduction to data science, developed and taught by leading professors. Solution: Discussion Forum. Press J to jump to the feed. Learn how to ask the right questions, obtain data, and perform reproducible research. Topics in statistical data analysis will provide working examples. What do you think of the Coursera John Hopkins Data Science specialization? Use R to clean, analyze, and visualize data. I would say Coursera and JHU are doing a decent job at it. As I mentioned in my comments on Coursera’s Executive Data Science specialisation, I have looked at a lot of online data science and statistics courses to find useful training material, understand the skills of people who have done these online courses, plus learn a bit myself.. One of the best known sets of courses is Coursera’s Data Science Specialisation, created by John Hopkins University. I'm coming from a liberal arts BA, and I was strong in high-school level math up to Calc, and I just got very little out of the Statistical Inference and Regression Models courses. More questions? This course covers the essential exploratory techniques for summarizing data. I feel like having a portfolio to point to, as well as code on a site like GitHub, should be a good basis for a conversation with a potential employer. This could be useful: https://www.quora.com/What-is-your-review-of-Coursera-Data-Science-Specialization-Track. To be eligible to earn a certificate, you must either pay for enrollment or qualify for financial aid. Use GitHub to manage data science projects. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. You'll be prompted to complete an application and will be notified if you are approved. I would love to see a class on design of experiments or manufacturing focus using R. I have found a few packages (qcc and SixSigma in R) but there don't seem to be many R users in mfg. If the only thing you have to show for is the completion of this Specialization, probably not.

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