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2022-09-26 09:52:10 How to Become a Full Stack Developer?

Here is my definition of the skills required to be able to call yourself a full-stack data scientist.

Minimum requirements, i.e. you should have at least some experience with all of these:

Python

SQL

Data wrangling

Exploratory data analysis

Feature engineering

Basic statistics

Cross-validation

Regression and classification

At least one deep learning framework

API development

At least one cloud platform

Version control (git)

Preferred qualifications, i.e. you should have familiarity with all of these and some experience with most of them:

NoSQL

NLP

Image recognition

Object-oriented programming

Test-driven development

Distributed systems

Containerization (Docker)

DevOps

Microservices

Streaming analytics

As you can see, this is quite a lot. Data scientist isn’t an entry-level job in my opinion, and when you add «full-stack» it certainly isn’t.

It’s unlikely that you’ll pick up all of these skills as part of education and self-study. Some on-the-job training is necessary.

A full-stack data scientist should have the software engineering skills of a backend developer with at least a couple of years of experience.

So the answer is that you become one by doing the following three:

Complete a STEM degree or at least a degree with a decent number of quantitative subjects.

Self-study obsessively. Hobby projects, MOOCs, papers, books and so on.

Take an entry-level job like junior data scientist, software engineer or similar and gain some experience. It should have a heavy focus on programming.

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