Journey In Learning: Data Scientist
In my journey to become a data scientist, I was able to learn from various introduction courses using MOOCs or Massive Open Online Courses. I started with Coursera’s offering from the John Hopkins’ Data Science Specialization: link to the Data Science course in coursera.org
They provide certifications that you can attach to your Linkedin’s profile. I learned a lot from the courses regarding the application of Data Science in various scientific fields. We learned how to input datasets of various forms: CSV, JSON’s, HDFS, and also from different API’s. Here is one example of a project I had finished from the courses:
We learned the R programming language, which is often preferred by most data scientists as a language to learn. However, this is not the only programming language to learn. A lot of Data Scientists uses Microsoft’s Excel, especially if you will be involved in business. Data scientists use programming and presentation skills to tell a story about how important a certain study of data is to finding business opportunities, and/or creating real-time decisions to create an advantage over competition: A MOOC that I would suggest in addition to the above data science specialization is offered by Duke University: link here.
In this class, the professor provides a thorough study on what it takes to be a data science, and even provide enough information on how his students got their jobs within the data science industry. He would have guest speakers from former students that are currently working as data scientists, business analysts, and business data analysts. There is even enough information to distinguish a data scientist’s job from a software engineer’s, or how a data scientist works along side the other three jobs. Here are sample screenshots from this course:
Below are some infographics that compare some various Data Science related careers:
