All you need is the knowledge on the lay of the land and to focus your efforts on the right goal...
Let's get started!you want to switch to a data science career
but the field is a mystery to you
because it looks like the amount of things to learn is endless
you feel overwhelmed in a sea of information
and you're not sure which direction will be worth your time
you have trouble bringing everything you learned together
even though you study hard you don't feel solid progress
you feel intimidated by the insane data science job descriptions
you need a way to guide your efforts and stay in focus
you want to know that you are doing the right things
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This is a start-to-finish guided project course.
As you go through the course, you build a data science project and at the end of the course, you will have a portfolio-worthy project to share with the world, already on your GitHub account, all ready to present!
This course is prepared to act as a guide to aspiring data scientists during the first steps of their journey.
The goal of the course is to help you identify clear goals and stay focused when learning data science. There are three modules in the course:
“Straight to the point and short but very meaningful. It definitely guides me in a better direction.”
“It gave me an insight of what a data scientist is. You have inspired me with the data science knowledge...thanks a lot!”
“The whole course covers the proper guideline for a data scientist. Each and everything was important to me.”
“Organized info about getting into data science in a way I have not seen before!”
By now you have probably heard this explanation: ML algorithms learn like humans. You give it examples and it recognizes and remembers the patterns in them. You need to give it a lot of examples, though, so that it can learn accurately. Okay, that’s clear. But HOW does it learn?
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It is pretty much a stereotype that data scientists can’t write clean and understandable code. This doesn't have to be the case for you. By learning a few principles of how to write code properly, you can use the stereotype to your advantage and set yourself apart from the competition.
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When changing careers into data science, if you have years of work experience, it's only fair to expect a higher position than junior data scientist. In order to achieve it, you need to approach your job hunt differently than newly grads. Here are some tips for signalling to your future employer that you will bring value.
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It's not easy to choose courses. There are many courses offering different sets of knowledge and nearly all claiming that they are the best course. In this article, I will share my opinions on the popular data science courses and books and recommend ways of studying data science using these resources.
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There is a group of people who seem to give off only negative messages about becoming a data scientist. I call them the data science elitists. In this article, I want to show you how you can have your shield up against negativity on your way to becoming a data scientist.
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It is hard to give a comprehensive list of all the skills that will be in-demand in the future but I will share three most likely candidates that, in my opinion, companies will be looking for in the coming 5 years.
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