best mooc courses for data science

valuesIs.na () is used to test whether the object is Na,is.nan () to test whether the object is Nan. Na is Nan, but Nan is not na,nan much deeper than NA.10. Data frameThe data frame is used to store tabular data and is created with Data.frame (). You can treat a data frame as a special list collection, with the same

TRUEFALSE TRUEFALSE TRUE> x[good][11245Complete.cases () can also handle matrix data> airquality[1:6,] Ozone SOLAR.R Wind TempMonth Day1 A the 7.4 the 5 12 $ 118 8.0 the 5 23 A 149 12.6 About 5 34 - 313 11.5 + 5 45Na Na14.3 About 5 56 -NA14.9 the 5 6> Airquality[good, [1:6,] Ozone SOLAR.R Wind TempMonth Day1 A the 7.4 the 5 12 $

learning methods of C language are not simply learning the language itself, but using C as a tool to learn operating systems, compilers, and embedded systems, in the study of specific fields, we constantly practice the ability to use C programming and enhance the understanding of C. First, who are learning MOOC? The number of students completed in most courses is less than the percentage of students selec

courses is less than the percentage of students selected. Coursera data science certificate sold tens of thousands (by impression, data may be incorrect), and only over 500 people finally completed the capstone project. In addition, most of the people who have completed the work have already had a background in comput

to recommend MIT python on The EDX platform. Data analysis: What I know is: 1. JHU's data science is a bit confusing! 2. The R language is required! Therefore, Duke statistics and analysis are strongly promoted. Note: There is a mooc navigation website under the fruit shell network flag, which is doing well. Many

basis (such as me) to learn, still remember the first class, because the Python2 and Python3 confused, Leng toss for 3 hours ... The course of data science is now charged and is a series of courses, and I went to two of them, of course, for free, and it was all about analytics, but not in Python but in the R language. I like the teacher in Python more than I do

What is http://www.quora.com/What-is-data-science data science?Http://www.quora.com/How-do-I-become-a-data-scientist how can I become a data scientist?Http://www.quora.com/Data-

queue are the previous ideas (Kemin: is a good case where data can be structured and adjusted based on specific problems) and applied to new problems. Finally, Part IV: the limits of computer science takes students through material that might normally be reserved for later theory courses, using the insights that students have developed for both algorithms and

separately and recommend some resources that will help us better understand machine learning and improve related skills. This classification of the learning phase is only my personal advice, and perhaps there are some resources in the pre-and post-classification phases that are appropriate for the current phase. I think it is very helpful to have a holistic understanding of machine learning, and I would like to hear your thoughts and tell me through the comments below! Beginner Stage Beginners

http://blog.csdn.net/pipisorry/article/details/44245575A very good article on how to learn python and use Python for data science, data analysis, machine learning Comprehensive learning Path–data Science in PythonDeep learning paths-da