Coursera has so many courses, it is difficult to keep track. New ones are starting all the time. Here are 2 more that will be beneficial to people interested in learning more about data science.
- Statistics One – Technically, it started yesterday, but you will not miss out on much if you start today. If you are lacking some skills in statistics, this is probably a great place to start.
- Intro to Computational Finance and Financial Econometrics – If you are interested in data science and finance, or if you want to know if you are interested in data science and finance, it is worth checking out this course.
Happy Studying Again!
This is a nice infographic about gamification in education. I am curious to watch how gamification plays a role in the online education scene at places like Udacity and Coursera. I think gamification is going to lead to many new and interesting problems in bigdata.
Created by Knewton and Column Five Media
Recently, I read an article titled, Why Online Education Won’t Replace College–Yet. The article is most likely a response the recent success of Massive Open Online Courses (MOOCs) such as those offered by Udacity and Coursera. The author, David Youngberg an Assistant Professor of Economics, presents 5 reasons why online education won’t replace college. I disagree with his reasons, so I thought I should share more details. I will go through each of his 5 reasons.
- It’s too easy to cheat. Cheating has always been an issue in education, and I think it always will be. Students even manage to cheat in ivory tower institutions. Online Colleges such as University of Phoenix have been very successful and cheating can easily exist in that scenario. I do think online classes make cheating easy, but I don’t really see that stopping the success of online education.
- Star students can’t shine. This is just simply not true. The star students are the ones answering questions in the forums and getting the assignments done first. This is very similar to the star students in a regular college setting. The brightest students have their work done first and are frequently found helping their peers. Udacity has even hired one of the former star students.
- Employers avoid weird people. Just because a person takes an online course does not make him/her weird. Taking an online course means a person is willing to find cheaper and easier ways to solve old problems. It also means the person has the initiative to go out and complete something. All of those traits are attractive to companies. The problem here is credentials. MOOCs have not yet solved the credential problem. MOOCs don’t offer degrees or widely-acknowledged certifications yet. Companies want to hire people with degrees, not people with a piece of paper stating “I completed an online course.” I think MOOCs will quickly figure out this problem. Also, many of the Coursera and Udacity students are former college graduates. Why are they now weird for taking an online course?
- Computers can’t grade everything. Not so fast. Earlier this year, Kaggle and the Hewlett Foundation sponsored a competition to see if technology could be created to automatically grade standardized test essays. Well, the competition was a big success. See the full press release. The competition results will probably not generalize to all essays, but the technology to automatically grades papers is not that far away. Also, Coursera is experimenting with crowd-sourced grading of papers. One student grades the papers of 4 unknown classmates, then a final score is calculated by a computer. See the Peer Assessments section on the Coursera website. This technique may even be more effective than grading by a single highly-trained person.
- Money can substitute for ability. The author argued that students will pay for tutors, buy dishwashers or anything else to help get better grades. I do not think banks are going to start handing out loans for dishwashers, so students can have more time for homework. I think MOOCs will allow students to learn without building massive amounts of debt.
Now, I cannot say with certainty whether or not MOOCs will replace traditional colleges. I just did not believe the above reasons are what will determine the outcome.
On a side note, this blog is focused on material about learning to become a data scientist. I think MOOCs are going to be hugely helpful for people wishing to obtain data science skills.
Thanks to Ed for leaving the comment yesterday. I have reposted the comment here because I thought it was so good.
Looks like Coursera added a new data science course entitled “Web Intelligence and Big Data” while nobody was looking! Plus, it starts at the end of the month, for those who can’t wait until the UW Intro to Data Science course to be scheduled.
Here is a link to the Coursera Web Intelligence and Big Data Course. The course is looking to focus on map-reduce and parallel programming applied to data problems.
If you have the necessary background in math, statistics, and computer science; then it is a good time to learn some data science specific skills. Coursera just recently launched a course specifically devoted to Data Science. It is titled: Introduction to Data Science. The course is being taught by Bill Howe of the University of Washington’s eScience Institute. I believe this course is an excellent place to start. I am very excited about this course.
Other Data Science Learning Resources
Here is a listing of other materials that could be helpful to learning data science.
Many aspects of computer science are fundamental to data science. A good data scientist has to be able to transform/extract/manipulate lots of data. Computer programming is the main technique for such operations. Here are numerous resources to help you learn the fundamentals of computer science.
Online Computer Science Courses: Introductory Level
If you are not familiar with computer programming, this list is a good place to start.
Online Computer Science Courses: More Advanced
Two More Helpful Resources
Stack Overflow is a great site for answering all of your programming questions. It is good for beginners as well as more advanced programmers. Also, if you start writing a lot of code, Github is a great place to store that code.