Do not miss our next launches !
35h per week
February 02, 2021
March 02, 2021
April 06, 2021
10h per week
February 02, 2021
March 02, 2021
April 06, 2021
Launches are planned every month
Study the company’s data to determine which data will be extracted and processed
Retrieve and analyze relevant data related to the company’s production process, sales or customer data
Develop predictive models in order to anticipate the evolution of data and trends related to the company’s activities
Model results to make them readable, usable and actionable
Join the Data teams and interact with Data Engineers and Data Analysts
As part of our partnership with the University of Paris 1 Panthéon Sorbonne, our Data Scientist training is now certified by La Sorbonne.
You can now benefit from the recognition of a world-class university.
Our Data Scientist
Price for our course: 5000€*
*Payable in 10 installments
Are you still hesitating on the route to choose closest to your expectations?
A member of our DataScientest team will be happy to help you make the right choice
The Data Scientist job :
Data Scientist is the “sexiest job in the 21st century” according to the Harvard Business Review. Even if there is a consensus on this statement today, the definition of data scientist is hardly universal.
The huge amounts of data available to companies are a fantastic source of information: it’s all about extracting the potential and drawing useful conclusions. The task of the data scientist is to set up data-based algorithms to respond to all types of problems ranging from stock optimization to weather prediction.
In a survey we conducted among 30 CAC 40 groups (Crédit Agricole, BNP Paribas, AXA…), the four most important skills of that a data scientists should have were in order :
- Mastery of machine learning and mathematical statistics
- Programming and computer science
- Fluency in written and oral communication
- Knowledge of the trade
If the data scientist who perfectly masters these four aspects can be difficult to find, specialized training allows to be up to date on these key points in order to meet the expectations of recruiters.
From raw data, a data scientist develops algorithms to address issues such as :
- classification (spam or not spam)
- recommendation (such as for Netflix or Amazon catalogs)
- model detection (without previously known groupings)
- detection of anomalies (fight against fraud)
- image, text, audio recognition…
- automated processes (validation of credit card payments)
- segmentation (marketing based on demographic segments)
- optimization (risk management)
- forecasting (sales and/or revenues)
DataScientest makes you live a day in the skin of a data scientist through this video.
We can almost talk about a scientific process of the data scientist. During this one, the scientific method he applies integrates the following elements:
- Acquisition, collection and storage of data
- Identification of needs (asking the right questions)
- Data digestion and integration
- Checking the validity of the data, deletion if necessary
- Initial data analysis (exploratory statistics)
- Choosing one or more models and algorithms
- Apply data science methods and techniques (machine learning, statistical modeling, AI)
- Measuring and improving results Deliver, format and communicate results
Our course :
All professions with a scientific background can be concerned by our training courses, because the acquired knowledge is often sufficient to develop the skills necessary for data science professions. To understand and know the necessary pre-requisites, discover this article !
To start a training as a data scientist, the minimum requirement is at least a Bachelor’s degree in mathematics or a master’s degree in science. Some notions of communication and marketing are always a plus in view of the work of transmission and communication that this job requires.
These prerequisites exist because although the training is centered on data science, and not mathematics, they are necessary for a good understanding of the logical principles of the concepts addressed. Those who have already studied and approached statistics (variance, algebra…) will go much faster and will be able to tackle new concepts much more easily.
After your registration on the site, we will contact you a first time for a presentation of what DataScientest is, what we can offer but also your background and your wishes. The idea is to align your expectations with our training courses.
Then we will redirect you to a technical positioning test which helps us know with which bases you start. It is essentially a mathematical test of probability/statistics and relatively basic algebra (undergraduate level in mathematics).
Once this test has been taken, a member of the admissions team will contact you to discuss your result, your motivations, and finally the relevance of your project.
During your reflection and until this stage, you are in no way commited with DataScientest and can at any time, if you wish, put an end to the process.
Once your project has been confirmed, you move on to the registration phase with our teams who will take care of initiating your training in data science and implementing it with you in all its aspects.
DataScientest is the only organization to offer hybrid training, i.e. both face-to-face and distance learning. (approximately 15% and 85% respectively). This makes it possible to combine flexibility and rigor without compromising on either one or the other. It is a well thought-out choice that motivates our pedagogy so that the learning process can be carried out to its conclusion with motivation. We have detailed the advantages of this unique combination in an article on the subject.
Moreover, it is possible to follow the training entirely from distance: face-to-face courses are then replaced by videoconference courses. However, the follow-up remains the same: the teachers remain attentive and follow you throughout your course.
- The ability to study the company’s data to determine what data will be extracted and processed in the future.
- The ability to retrieve and analyze relevant data related to the company’s production process, sales or customer data.
- The means to develop predictive models in order to anticipate the evolution of data and trends related to the company’s activity
- The know-how to model data analysis results to make them readable and usable by managers.
The curriculum is built on several blocks, themselves divided into modules. The blocks for our Data Scientist course are the following: Introduction to Python, Dataviz, Statistical Machine Learning, Advanced Machine Learning, Large Dimension, Deep Learning, and finally Complex Systems and AI. Click here to request the complete training syllabus!
All courses have been created by our expert data scientists. DataScientest commits to never use external providers or buy back content. The content is the result of rigorous work carried out in close collaboration with major European groups. The total duration of a course is 400 hours, including 280 hours of training and 120 hours for the Big-Data project. The courses are based on the principle of sprints :
- Firstly a platform objective with the aim of knowing how to handle skills, validated by exercises and certification in fine.
- Then, the project comes to confirm the acquired skills, it must be completed, with a progress report and a deliverable to fill-out.
Depending on the type of training chosen (bootcamp or continuing training), each sprint takes place over one or several weeks. If the content remains the same, the number of hours of classes differs depending on the format: 35 hours per week for bootcamps and 6 hours for our continuous format.
Of course! And who better to provide support than our teachers, who also designed the program. They are available and ready to listen to all questions, whether theoretical or practical, and will demonstrate pedagogy in their answers.
In addition, to ensure the completion and commitment of each student, our teachers follow your progress closely. As soon as you stop logging in for an extended period of time, your cohort leader will check in on you: we won’t let you down!
Finally, our papers, exams and papers are also corrected by hand by our panel of qualified teachers: everything is done so that everyone can progress at his or her own pace efficiently. At DataScientest we are convinced that only a personalized follow-up ensures quality learning!
Throughout your training, and as your skills are developed, you will lead a data scientist project.
It will not be a standardized and imposed data science project: it will be up to you (in pairs or trinomials) to determine the subject and to pitch it to our teams who will validate it or not. Obviously this adds difficulty: unclean data, uncleaned models… but our teachers are there to help you every step of the way.
It’s an extremely efficient way to move from theory to practice and make sure you know how to apply the topics covered in class.
It is also a project that is highly appreciated by companies because it ensures the quality of the training and the knowledge acquired at the end of the Data Scientist training. Knowledge that is not only technical, since the soft skills are also highlighted:
- Knowing how to communicate and pitch
- Know how to present and popularize your work
- To know how to enhance data via data visualization (dashboard…)
All in all it is a project that will require a real investment: at least a third of your time spent on training will be spent on this project.
Each major step highlights a new aspect that is being addressed during the course. The project is punctuated with exams and support with your educational director to ensure your progress and understanding throughout your advancement.
According to the data managers of the largest CAC 40 companies, knowing how to communicate both orally and in writing is more important for a data scientist than mastering the company’s core business.
That is why we have taken this into account in our curriculum, which also emphasizes soft-skills with :
The written and oral support of the project, which allows to develop these skills.
Data class around project management or management tools that are now part of the syllabus.
Masterclasses on “best practice in data visualization” that complement the curriculum.
For those who wish, the possibility to participate in CV workshops and career coaching via the career managers and the HR team of DataScientest. Click-here
As part of our partnership with Panthéon Sorbonne, each of our Data Scientist, Data Analyst and Data Engineer training courses is now certified by La Sorbonne. You can now benefit from the recognition of a world-class university. These certifications are a pledge of quality that guarantees a content adapted to each of our learners.
In addition, as a B2B leader in data science training, DataScientest is well known among companies that entrust it with the data science training of their teams. This trust has forged the recognition of its diplomas.
Finally, the data scientist diploma benefits from a level 6 RNCP title (equivalent to master’s level). We are in the process of validation by the RNCP for a level 7 diploma and should be validated in the coming weeks (updated 02/11/20).
If you are registered at Pôle Emploi, you are potentially eligible for the AIF.
You will then be able to benefit from a grant of up to 2000€.
Whatever the case, our teams are there to guide you through the administrative procedures for registering for the various funding programs.
To find all the financing possibilities, nothing could be simpler: we have created a page dedicated to the subject!
A Data Scientist’s career :
The ability to master data is proving to be very valuable in certain professions such as researchers and actuaries.
They benefit enormously from the added value of data sciences, as do most quantitative professions that involve statistics.
Data offers them new doors and opportunities.
To answer this question, we conducted our own survey of some 40 partner companies.
Depending on the sector and the company, the salary of a junior data scientist is between 35 and 50 000 € per year.
After 4 years of experience, this salary increases considerably and varies between 50 and 65 000 euros.
Our post-training support services
Beta-tests are made available for former students to gain knowledge even after the end of the training.
At the same time, newsletters elaborated by our data scientists are regularly sent out and are a reliable source of specialized data science information.
Finally, the DataScientest community continues to grow, and with it all of its alumni. To keep in touch and allow alumni to communicate with each other, DataScientest has set up a group of alumni on LinkedIn who share and exchange on various themes around Data Science.
Initially, DataScientest supported the data transition of companies.
This allowed us to create strong links between the major groups that ensured the growth of our structure.
Subsequently, they were the ones who motivated the launch of our offer to individuals in order to compensate for the lack of competent profiles.
This need for good profiles is reflected in the survey we conducted among 30 of the CAC 40 groups. Even with high budget constraints, only 4% believe they would reduce their data scientist numbers: by comparison, 28% would still seek to increase their numbers by more than 20%.
On the strength of our past with large companies, we then signed partnerships related to the hiring of our alumni. All our partner companies are committed to including all our students at the end of their training in their recruitment process: this, coupled with the help with CVs and interviews, means that you will be in pole position to get the job of your dreams!
Not only can we help you but we are also in an ideal position to do so
Of course, assessments are regularly made with our HR team who will follow you throughout your career.
When you are nearing the end of your training, a point is made during which you inform the sectors you wish to move towards.
Based on your information, we deposit your CV with our partner companies, and you are immediately registered in the recruitment process of these groups.