How (in 2023) to Become a Data Scientist with No Experience

So, you want to become a data 
scientist but have no prior experience?  Employers, on the other hand, are only 
interested in candidates with working experience.  Most of us have been there, so don’t worry!
The good news is that you’ve clicked on   this video, and we will now share 
our secret formula for overcoming   this seemingly insurmountable challenge.
Over the years, 365’s team has trained   hundreds of thousands of people.

We’ve heard many 
stories about what has worked for our students   and what hasn’t. And, in this video, 
we’ll gladly share our findings with you.  One of the aspects many individuals underestimate 
is having a clear roadmap in mind. So first,   we’ll talk about the learning journey you need to 
embark on to become a data scientist. Then, we’ll   focus on the things you can do to put the odds in 
your favor and land your first data science job.  Right. Learning journey.

steps do you need to take?  We recommend you start by gaining a broader 
understanding of the data science field   and how it adds value to businesses.
• Study various data science   terms and their application.
• Find out why data plays such an important   role in company management and profitability.
• Determine how a company can be positioned   in order to thrive in a world of data.  Other things you can learn include:
• what types of data   analysis techniques are there,
• as well as how and why do we apply   machine and deep learning algorithms,
• and so on…  You might even want to take a few business 
courses to ensure you understand how a   company creates value and what its current 
strategic positioning is within its industry.   Our courses on Intro to Data Science, Data 
Strategy, Data Literacy, Intro to Business   Analytics, and Data-driven growth can be the 
perfect gateway to obtaining this knowledge.  Once you’re past this initial stage, 
it’s time to learn the fundamentals.  Start with Statistics, Mathematics, and 
Probability to build a solid foundation that   would allow you to understand technical topics 
later on.

In this way, you would not only know   how to apply existing frameworks in blindly, but 
will also recognize how they were constructed and   understand their limitations in each situation. 
This is precisely the reason why our program   covers the fundamentals first and only then 
introduces you to coding with programming   languages such as SQL and the application 
of advanced statistical concepts in Python.  But eventually, you will need to learn how to 
code. SQL and Python are the two most popular   coding languages a data scientist needs. SQL 
allows you to work with structured databases,   while Python is the tool you use to manipulate 
data and perform analysis. Certainly, one of the   best tips we have for you if you are a beginner 
in programming is to learn the basics, then apply   what you’ve learned by working on simple projects. 
Our video on the ‘4 essential Python projects for   beginners’ is a great source of inspiration if 
you’re looking for beginner-friendly projects.  At this point, you will be ready to hone 
advanced topics such as supervised and   unsupervised machine learning algorithms, 
potentially even deep learning… But to be   able to showcase your skills properly, you’ll 
need great data visualization skills too.   So, don’t forget to work on this aspect.

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