In this article, I am going to map out the things you need to do to become a Data Scientist. This article may solely be for beginners, however, there may be a thing or two that current Junior Data Scientists may have missed out on. This is where I am here to help fill in those gaps so that you don’t have to feel imposter syndrome or lack of confidence on your data science journey.

I will be taking you through the steps – it is a roadmap at the end of the day.

 

Python

 

Python is one of the most popular programming languages today and more and more people are adopting it due to its simplicity. So if you’re looking to enter data science and have not chosen a programming language yet – Python is always a good start.

Here are some courses to help you get started:

100 Days of Code: The Complete Python Pro Bootcamp for 2022 – Udemy

Programming for Everybody (Getting Started with Python) – Coursera (University of Michigan)

 

Data Science and Machine Learning

 

Once you understand alphabets and how vowels work, that’s when you can start to construct sentences. That’s how I see programming languages and sectors such as data science and machine learning.

Once you get a hang of the programming language Python, you should then be on a good page to see how you can use that skill and apply it to data science and/or machine learning.

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.