The format is fully adapted to quickly become operational in data science: lots of practice, with a well-established pedagogy on learning the code.
What motivated you to follow the data science training?
I studied in a general engineering school, but did not follow a data science course during my studies. After a few years of strategy consulting, I wanted to bring a more technical dimension to my work by turning to this discipline. I joined ClaraVista, a consulting firm that mixes profiles of data scientists and strategy / marketing consultants. My company gave me the opportunity to become fully operational in data science by following this training, in order to intervene on missions with double competence.
What do you think of the training?
The format is fully adapted to quickly become operational in data science: a lot of practice, with a well-honed pedagogy on learning the code, repeated case studies to understand the main models used on business applications, and expert teachers in the field, available to deepen the mathematical concepts behind the models studied.
I have more of a maths profile than developer: working in pairs allowed me to progress much faster on dev than if I was alone.
How do you find the atmosphere?
The training is based on teamwork with pairs that change daily. The idea is to help each other by taking advantage of everyone's skills, and the diversity of profiles is the strength of this training. I have a maths profile rather than dev: working in pairs allowed me to progress much faster on dev than if I was alone, and conversely, I was more comfortable to help my pairs on math-oriented questions.
Can you tell us more about the project you are developing at Le Wagon?
First, we want to predict sales of short-lived products (bread and fresh products for example) for a large supermarket chain to allow it to adjust its supply to demand in each store. We wanted to study past sales, seasonality on certain products and the impact of external events on sales. We then wanted to try to optimize the logistics around the supply of these supermarkets and are still exploring the avenues allowed by the data we have available. It will also surely depend on the results obtained in the first phase of the project!
What are your tips for people who want to train in data science?
Get totally stuck in! Test models in Python to see how they work and what they produce (no need to master the language, many examples are available on the Internet with detailed explanations), and deepen your knowledge by reading books or technical articles on the important mathematical concepts behind the models to really understand what's going on.
How will this training help you develop in your current profession?
The core business of ClaraVista is to explore the data of our customers to create added business value. The training will allow me to explore additional algorithmic approaches on the missions that we already practice, but also to contribute to developing the scope of intervention of ClaraVista on new customer issues.
