I had a conversation with someone recently and mentioned my interest in data analysis and who I intended to learn the necessary skills and tools. They suggested to me that while it is great to learn the tools and build the skills there is little point in doing so unless i have specialized knowledge in a specific field. They basically summed it to that I'd just be like a builder with a pile of tools who could build a few …

I was looking at a statistics course (undergraduate degree), and I thought I probably would find doing only statistics a bit dry, and I thought about if doing an Applied Mathematics major (I am better with applied math than purely statistics, however, I'm still good with stats.), with perhaps a couple more electives in statistics, as opposed to a statistics major. E.g. on top of the applied math course (Real/Complex analysis, ODE's, PDE's, vector analysis, fluid flow, calculus), also do …

I'm going to do an undergraduate degree next year. Data Science major is there but I was wondering if a statistics major with a minor in data science would be more valuable? Which degree would be more in demand? I am also planning on doing as many internships as possible to gain practical skills and experience. I am also contemplating the value of a masters degree, and whether it is worth the time and money, or if an undergrad+internships will …

I am a chief data scientist at one of the largest corporations in the world. I am constantly approached by employees to teach them more about data science and help them on their learning path. The problem is that no one really seems to stick with it over the long term, everyone just wants the "shortcut" to the sexy data scientist job without realizing the work needed. So, in effect, how can I get more of my "students" to stick …

I've now seen two data science certification programs - the John Hopkins one available at Coursera and the Cloudera one. I'm sure there are others out there. The John Hopkins set of classes is focused on R as a toolset, but covers a range of topics: R Programming cleaning and obtaining data Data Analysis Reproducible Research Statistical Inference Regression Models Machine Learning Developing Data Products And what looks to be a Project based completion task similar to Cloudera's Data Science …

My problem is that at our masters program we have already been taught R, Statistics, Neural nets, Python (pandas, sklearn, etc). Also my master thesis is directly related to Deep Learning and Computer Vision (PyTorch, Tensorflow). Thus, i avoided entering MOOC on this topics. Now i have free time to pass all the MOOCs. But how much more important is the record about the MOOCs passed than just master program for job appliance in Data Science?

I am looking to get my Masters in Science in Data Science or Analytics. I will continue working during the program so it needs to be part-time. I would prefer to do an online course, but if in-person is much better, I could be open to it. So far, I found Georgia Tech and Johns Hopkins for online, part-time programs. For in-person, I could attend Georgetown part-time. Any insight you can provide regarding which of these programs would be best, …

I would like to know how many people can use a single Hadoop cluster at one time? I am asking because I need to figure out whether or not a single 5 or 10 node cluster would be sufficient to host a class of 12 to 24 students. Also, I am wondering if anyone could recommend whether the specifications each for the nodes on a high-end educational-level cluster should be the same as for any other production-level cluster ( ie. …

My dream occupation is to work as a Data Scientist. I'm soon going to be completing my first semester as a physics student, as part of an incredibly prestigious physics program. We get to run an experiment at CERN in our third year! I'm currently ranked highly in this program (top 25%), and I could push myself to top 10% if needed. Thing is, I'm not really interested in working as a physicist. Should I switch to Math & CS? …

I am looking for a challenge that is suitable for a group of novices who want to learn the basics of data science and machine learning. The challenge should match the following criteria: is based on a real application or is at least realistic has a clearly defined goal and partial progress is measurable includes a machine learning component, but also other aspects of data science should be doable within 3 to 6 weeks is suitable for novices it should …

I am a Python developer but I want to become a data scientist. My Question: At its core what is the bare minimum I need to have to make this transition? I know it cannot simply be that I need to learn Numpy and Pandas. My Thoughts: I am hoping to frame my question with the following three perspectives in mind and am trying to answer what is essentially needed for each category: Technical: Analytics Technical: Computer Science Non-Technical: Soft …

So I'm hoping to ask professionals for their advice here. My university doesn't offer a "data science" major and I'm cobbling one together from different departments. So far I have a math major with stat emphasis but I'm having trouble finding technology use in this program so I was thinking computer science for science credits. I also have a choice of an Information Management minor or a Business Analytics minor, both from the business college. So basically, I'm wondering: Which …

I am reading the programme outline of this two-year MSc in Data Science and I found that it has no deep learning content (as in many other european ones). I am no expert but as far as I've seen I think that DL is going to be a heavy weight of ML algorithms for a long time. Do you think it is a bad idea to take a strong focus on classical models (e.g. bayesian) instead of teaching DL in …

If I understand the Databricks philosophy correctly, Spark will soon be heavily moving toward dataframes, i.e. away from the usual map/reduce on RDDs. I was wondering if there are any good suggestions for online courses or books that introduce Spark from the dataframe point of view? I know Databricks has a good number of resources on dataframes but I would really like to see some more detailed courses.

I had a question regarding about a career as a data scientist. Im pursuing a degree in business analytics with a minor computer science. Could i still become a data scientist with a bachelors degree in business analytics. Or would i have to pursue a masters degree in data science in order to become a data scientist. (I have a good programming background in data structures and algorithm in java, plus web development, python)

I'm currently pursuing a bachelor's degree in physics from a university in the UK. Most data science jobs here have a strong preference for people with PhDs in numerate degrees like physics and maths. I don't understand the point of spending 5 years of my life doing research in something I don't want to pursue a career in. I'm confused about what master's degree I should choose if I want to apply for a job straight after graduating. A physics …

I am looking for domain-specific data science programs (as a major, not a minor or specialization). I found programs in bio-statistics (and other disciplines in public health), MS in marketing analytics, MS in learning analytics and MS in urban informatics. Does anyone know any other domain-specific data science field of study?

Many Universities now offer Masters Degrees in data science; I'm curious as to people's opinions on whether a traditional master of statistics is a better to fit for working in the field of in data science.

What are the benefits of establishing data science programs as an independent discipline rather than creating data scientists in different fields? (for students, universities and the society as a whole) I am authoring a book on data science and I have mentioned some university programs as models for establishing data science programs in bachelor's, master's and doctorate level. I am thinking of some reasons to compare this model with enriching well-established programs and adding data science skills.

I am studying data science education curriculum design and guidelines. All resources I have up to now is about data science in statistics education and library and information science education. Is there any work on data science in computer science/software engineering education (adding data science courses to a traditional software engineering curriculum) ,management and other disciplines? An example of including the curriculum for statistics is this paper