Data Scientist

 Part-time (9 month) 
OUR NEXT ENTRIES ARE:
Inter-company Cohorts
April 01, 2025
May 06, 2025
June 03, 2025
Price: 5000€
sorbonne
Schedule a meeting

Training content (400 hours, including 120 hours of project)

  • 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
  • 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.

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.
Download program

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

Alumni feedback

Apply