Hello, Habr! Despite this title, I want to start not with life hacks, but with personal pain. I think many Khabrovites will understand me. This pain is a lack of time. It may well be called one of the main problems of modern specialists. Because of her, we abandon pet projects, learning something new, and articles for Habr have been written for years (this one is an exception!). As a result, personal progress is delayed. The Internet is simply full of various life hacks, how to do everything, techniques from Musk, Bezos and others like them, but today I would like to pay attention to the personal experience of much more earthly people. I spoke with online graduate students “Data Science” NUST MISIS and Zavtra.Online about how they manage to combine work and study.
I work in Sochi, in the largest hotel in the south, Velvet Seasons, in an engineering position, closely related to the operation of vertical transport (lifts and platforms, lifting for the disabled); in total there are about 300 pieces of equipment in the park.
In the magistracy, I was attracted by the opportunity to flexibly customize my learning regime. No need to waste time traveling to and from university. Document flow can be carried out by mail. The pace of learning can also be adapted to suit your activity.
Of course, there are periods of lag due to various factors, such as events in the family, at work, but I try to make up for missed material. How can you do everything? On weekdays, after work, it takes about a couple of hours for lectures and practice, I allocate half of each weekend for my family, the other half for intensive work on the platform. It so happens that on weekends you immerse yourself in the study of books, code, libraries.
Probably the most difficult thing is to find the motivation to practice intensively, not to procrastinate, in bad weather or after a long day at work. By the end of the first semester, it seems that burnout will finish you off, but unexpectedly for yourself, a second wind suddenly appears. Perhaps because you more clearly understand the ultimate goal, the features of the project that you will be working on, you start thinking about implementation details, functionality, and possible areas of application. Now more and more time is required to read books and immerse themselves in thematic communities.
In the summer, when it was necessary to intensively prepare for admission, I had the opportunity to participate in the preparations for the Formula 1 Grand Prix in Russia, which took place in September 2020. The period of preparation for the entrance exams was a “training” of study, I had to combine two jobs and preparation for the entrance exams, and in September the educational process began, and the level of stress increased significantly. At such moments, the body is mobilized. The difficulty was that at the very beginning a Python course started, which needed to be given more time than I could. As a result, having prioritized, I preferred to finish what I had begun (work on a Formula 1 project) and had to catch up with the missed course materials. Towards the end of the first semester, we managed to close all debts and even get well-deserved “automatic machines”. How? For 4-5 hours every day after work and all weekend with full immersion, disconnected from external stimuli, only you and the task.
Now it turns out to allocate 2-3 hours daily for lectures and practice; I do not take into account the time for reading specialized publics and books, it is difficult to take into account. On weekends, half of the day is classes on the platform, solving cases, problems. As you move further along the learning path, the intensity of the presentation of the material, of course, increases, and more time will need to be allocated on weekdays. It turns out that on average, the educational process must be given at least 20 hours a week.
A whole range of techniques and techniques helps to assimilate the material. During the preparation for admission, MindMap mind maps helped me (they structure information well). Coursera has a useful free course – Learning How to Learn: Powerful mental tools to help you master tough subjects (University of California San Diego) with Russian subtitles, which greatly helps to improve the quality of assimilation of the material. Practice helps to immerse yourself in the environment, however, while you are immersed, you are drowning in details, attention is scattered, but with each new iteration, the skill of finding the necessary information is developed. Now it all comes down to fighting the ever-increasing entropy.
I work as an electrical engineer for an oil company.
I decided to enter the magistracy because I want to understand Data Science. In general, I like to learn new things, besides, there is an opportunity to change profession after training, this also influenced my choice.
Study can be combined with work, especially if you do not postpone until later, but do at least a little in the evenings. Self-discipline is most likely needed here. I study most often on weekends, but it’s best to complete assignments in my spare time.
I have little experience in programming in general, I studied Python on my own and in free online courses before entering my master’s degree. If I do not have enough materials on the platform for training, then I read forums, articles, library descriptions, usually this is enough to understand.
I entered the master’s program because I decided to change my field of activity, I am a former design engineer, and in the current realities of our country the salary of a good designer is less than that of a junior data scientist. Perhaps I was looking badly …
I began to take SkillFactory courses, and at some point I was offered to enroll in a master’s program at MISiS. I decided to just try and, to my surprise, I entered with a very good passing grade, apparently, the first technical education affected.
At the same time, I managed to get a job at Norilsk Nickel, where a team was recruited to develop ml solutions, I passed the introductory tests and started working as a data scientist, at least that’s what they call me there.
Most of the work of a data scientist is not models (alas), it is collecting information, data mining. A complex process associated with understanding what you collect and how to apply it further.
Learning and working is not easy, especially if you are trying to do both well. No wonder there is a saying: you can’t sit on two chairs. Studying takes up almost all my free time, but this, apparently, is due to my desire to master more skills as quickly as possible. At work, I am the most inexperienced in the team, and in order not to be a ballast, I have to learn a lot myself, although a master’s degree gives me good knowledge. Work helps in truly understanding what is expected of a data scientist in a company.
At the moment I work as a business analyst at Rambler Group, a leading specialist in the project office. I manage to combine work and study thanks to online studies, I can choose a convenient time on weekends and make up for lost time, I also try to study on weekdays, but it does not always work out. For this reason, sometimes you have to sit at home all weekend and complete all the tasks, but I try not to lead to funny situations. Once, postponing everything to Sunday and sitting down to the material, I realized that I would not be able to solve everything in one day and understand what I had gone through).
I had to break the deadline a little, but now I try to do everything on time. I usually study on weekends, there are 5-9 hours a day. In total, it turns out to allocate about 15-20 hours a week for study, taking into account lectures. I thought for a long time whether to go to graduate school, to postpone work or not, but when I saw this option, when during my studies you can even go to work abroad, I stopped doubting and began to collect documents.
I work as a project manager at SKB Kontur. In my case, distance learning is especially important, since I live in the United States, New Jersey.
So far, it has been possible to combine work and study. There are moments of blockage, the main thing here is to clearly plan your work and study meetings in advance. For example, knowing the schedule of your lectures, schedule work meetings early in the morning, then you have time both here and there, in the evening, to allocate some time to complete work and educational affairs. After lunch, I pick up the kids from school and devote this time to family and household chores.
I study in the morning until lunchtime, if I don’t have time to do everything before lunchtime, I try to find time in the evenings. I study every day, including weekends whenever possible. The training includes the time of attending webinars, lectures, laboratory work, team projects, self-study on the SF platform, and so on; everything on average takes 3-5 hours a day, on some days a little more, on some – less. I am a pure team player, and it is important for me to discuss or jointly discuss certain issues with someone, practical study assignments. It helps me to master the material better.
All our students have a different background and rhythm of life, but, as we can see from the examples above, if a person really wants to study and get a new specialty, then he adapts his environment to this goal. Of course, there is a fear that if you allocate about a few hours a day for training after the main job, then there will be no time at all for rest and family. But here it is important to understand that such conditions are a passing phenomenon, after which it will be easier (even though IT and learning go hand in hand).
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