Data scientist Job: Which training to follow ?

Do you enjoy computer data processing and information assurance, and you’re looking for your dream Data scientist Job ? Becoming a data scientist can be a good fit for you. Big data, programming, and algorithm creation will no longer be a mystery to you. This strategic profession necessitates a high level of accuracy as well as analytical and synthesizing abilities. In this article, we’ll provide you with all the information you need to find the best training and find a Data scientist Job.


What are the prerequisites for becoming a data scientist?

A Master’s degree program will prepare you to become and find a Data scientist Job. Your prerequisites are a bachelor’s in one of the following fields: mathematics, engineering, statistics, or computer science. The formation is aimed at those who have programming skills and want to hone them while working on the predictive component of the IA. Isn’t it also a lowering of the bar in all of these areas? As a result, the master’s program lasts two years if you want to find a Data scientist Job.

It is also feasible to combine the bac + 4 course. To do so, you must have completed and passed a master’s degree in data analytics or data science.

What qualifications are required to work as a data scientist?

The training program allows you to gain the skills you’ll need to work and find a Data scientist job. This person’s job entails gathering, analyzing, and translating a large number of data sets. Then, using algorithms, you’ll create predictive models to assist the company in making decisions. As a result, you play a strategic role.

Thousands of data points are logged by businesses, all of which are waiting to be used. As a result, they require big data specialists. The merging of data is complicated, and its use requires the use of a statistical system to model it. In addition, the data scientist will develop predictive models to anticipate data evolution as a part of his/her Data scientist job.

Statistical analysis, computer programming, and marketing are hence his specialties. The person in charge of the Data scientist job has a broad understanding of corporate strategies and can translate them into mathematical models. It is capable of giving meaning to diverse data in order to translate them and make them accessible and meaningful.

You must have a strong mathematical and programming background to succeed in a Data scientist job, as well as an analytical mindset. Also essential is your understanding of business issues from a marketing standpoint.

The Data scientist job is frequently confused with that of a data analyst. While each of these professions makes use of data, their goals are very different. In fact, a data scientist’s job gathers a variety of data in order to create analytical tools. In terms of the data analyst, you’ll be responsible for the extraction and analysis of targeted data used for marketing purposes.

What is the program of the data scientist training?

The training program to become and find a Data scientist job, whether in Master 1 or Master 2, is divided into three areas: applied mathematics, programming, and AI business.

In the first year of the master data scientist program, the objectives are:

  • Optimize and dynamize data on MySQL and MongoDB by creating data tables ;
  • Data extraction with Python ;
  • Data manipulation with Python Pandas;
  • Modeling processed data with Python library;
  • Perform various statistical analyses and program an algorithm to answer an identified problem;
  • Translate the data into tables to make their reading more efficient;
  • Know how to use IT management tools;
  • Evaluate the impact of AI on the company’s performance.

The skills that match are:

  • Create a database with a DBMS;
  • Analyze the data and extract the main KPIs;
  • Choose a machine learning algorithm adapted to a problem and optimize its performance;
  • Translate the analysis into a dashboard.


In the second year of the Master’s program, the program continues and deepens the objectives defined in the first year. The skills developed are the following:

  • Extract the main KPIs from different data and produce a dashboard ;
  • Choose a deep learning algorithm in accordance with a problem and optimize its performance;
  • Create a web application with a predictive part and accompany its deployment;
  • Analyze textual data with NLP techniques;
  • Generate fake faces with generative adversarial network (GAN) technologies.



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