Data Scientist

 Part-time (9 month) 
sorbonne
Get a recognized diploma, support until you are hired and a flexible job that is in high demand.
OUR NEXT ENTRIES ARE:
Inter-company Cohorts
October 01, 2024
November 05, 2024
December 03, 2024
Intra-company Cohorts
October 28th 2024
February 11th 2025
June 10th 2025
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Training content (280 hours total)

  • Python fundamentals
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Bokeh
  • Classification
  • Regression
  • Clustering with scikit-learn
  • Time Series
  • Text Mining
  • Dimension Reduction
  • SQL
  • PySpark
  • Data bases
  • Neural Networks
  • CNN and RNN with Keras
  • Tensorflow and PyTorch
  • Reinforcement Learning
  • Deep RL
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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.

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

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.

Studying

Study the company’s data to define which data will be extracted and processed.

Elaborate

Retrieve and analyse relevant ddata related to the company’s production process, sales or customer datasets.

Predict

Develop predictive models in order to anticipate evolutions or determine an future business trend.

Model

Exploit the results of data analysis and modeling to make them readable, usable and actionable by other departments in the company.

95,6%
job

Success rate

93,05%
fusée

Completion rate

99%
personne

Satisfaction rate

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Alumni feedback

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