It is a learning activity by redoing what I have learned, and logging all the progress. It is not just reading, but doing it myself once again. The effective learning is not happening when I read and understand the material. That is mostly happening when I do it myself, and sometimes when I struggle because of many unexpected failures while doing it.
I heard this name quite a time ago, but never had a chance to evaluate. I’ll do it now with the Django Tutorial. It seems django has some different approach to the web service backend, with the MVT (Model-View-Template).
I’ve used C/C++, Shell, PHP, Perl, Java, Python, and some other computer languages as well. But I am not a computer science major, so my understanding is a bit limited in algorithms. Maybe that is why I feel difficulties in coding tests during the interview process, as they normally ask to implement some quick algorithm. I don’t think knowledge of algorithms is really necessary for the work, but it is demanded during the interview process.
I am checking the python basics to answer the interview questions. I have used python for more than 7 years by now, but still there’s many features I have never visited. I’ll take this chance to cover the general basic concepts and features of the Python language. To start I have searched for frequent python interview questions, and tackle them one by one.
I was an analyst for the last 6 years or so, and barely did some C++ work. What I remember is only the Onload OOO Sending feature in R1, and IP Frag Verification done in early 2025. In other times, I was mostly Python/Pandas/Matplotlib developer and Performance Engineer, who was following the performance issues. During the interview process, however, I found people still want me to have some level of C++ skills. So I’ll reclaim my C++ skill with this Detour project.
As a part of the preparation for the python job interview, I decided to take an audit course for the “Introduction to Data Science with Python” in Harvard edX, CS109x. It is in audit mode, so it is a free course. I just need to know some details about what I am still missing in data science, after spending over 6 years of data processing and analysis.