Data Scientist

Bootcamp (3 month)
Part-time (9 month)

Get a recognized diploma, support until you are hired and a flexible job that is in high demand.

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Upcoming Dates
October 01, 2024
November 05, 2024
December 03, 2024
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Certified Courses

Training content (280 hours total)

  • Python for Data Scientist
  • Exploration Statistics
  • Data Quality
  • Object-oriented programming

  • Matplotlib
  • Seaborn
  • Plotly

  • Linux & Bash
  • Git & GitHub
  • Unit testing
  • AWS Cloud Practitioner

  • Classification
  • Regression
  • Clustering

  • Advanced Classification
  • Recommender Systems
  • Pipeline

  • Dimension Reduction
  • Time Series
  • Anomaly Detection
  • Reinforcement Learning

  • Ethics
  • Bias & Interpretability
  • MLflow
  • Text Mining
  • Web Scraping with BeautifulSoup
  • Graph Theory with NetworkX

  • Dense networks
  • Convolution networks
  • Keras - TensorFlow

  • SQL
  • API
  • PySpark

  • Streamlit
  • Docker
  • AWS Solution Architect
target

Throughout your Data Scientist training, you will carry out a 120-hour project.
The objective: apply what you’ve learned to a real project (which you can choose!) and benefit from a first concrete experience to add to your portfolio.

target

This course includes an AWS Cloud Practioner course leading to an official AWS certification.

METHODOLOGY

Hybrid learning format

Combining flexible learning on a platform and Masterclasses led by a Data Engineer. It's the combination that has won over more than 15,000 alumni, giving our courses a completion rate of +98%!

Our teaching method is based on learning by doing:

  • Practical application: All our training modules include online exercises so that you can apply the concepts developed in the course.
  • Masterclass: For each module, 1 or 2 Masterclasses are organised live with a trainer to address current issues in technologies, methods and tools in the field.
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Data scientist’s goals

The Data Scientist develops complex analysis models to extract information from databases.
These can be uses to predict consumer behavior or to identify business or oiperational risks.

Develop

Develop and deploy data processing, management and analysis solutions, including predictive models and algorithms.

Explore

Explore and visualize data to extract insights using advanced statistical and analytical tools.

Conceive

Design and optimize artificial intelligence models to solve specific predictive problems.

Key figures of the training

95,6%
job

Success rate

93,05%
fusée

Completion rate

99%
personne

Satisfaction rate

Alumni feedback