Course Info

Length: 1 Week

City: Paris

Type: In Classroom

Available Dates

  • Dec-30-2024

    Paris

  • Feb-03-2025

    Paris

  • May-05-2025

    Paris

  • Aug-04-2025

    Paris

  • Nov-03-2025

    Paris

Dates in Other Venues

  • Dec-30-2024

    Dubai

  • Jan-06-2025

    Dubai

  • Feb-03-2025

    Kuala Lumpur

  • Feb-03-2025

    Istanbul

  • Feb-03-2025

    Barcelona

  • Feb-03-2025

    Amsterdam

  • Feb-03-2025

    London

  • Feb-03-2025

    Singapore

  • Feb-10-2025

    London

  • Mar-10-2025

    Dubai

  • Apr-07-2025

    London

  • May-05-2025

    Dubai

  • May-05-2025

    Barcelona

  • May-05-2025

    Istanbul

  • May-05-2025

    Kuala Lumpur

  • May-05-2025

    Singapore

  • May-05-2025

    Amsterdam

  • June-09-2025

    London

  • July-07-2025

    Dubai

  • Aug-04-2025

    London

  • Aug-04-2025

    Amsterdam

  • Aug-04-2025

    Istanbul

  • Aug-04-2025

    Barcelona

  • Aug-04-2025

    Singapore

  • Aug-04-2025

    Kuala Lumpur

  • Sep-08-2025

    Dubai

  • Oct-06-2025

    London

  • Nov-03-2025

    Kuala Lumpur

  • Nov-03-2025

    Barcelona

  • Nov-03-2025

    Singapore

  • Nov-03-2025

    Dubai

  • Nov-03-2025

    Amsterdam

  • Nov-03-2025

    Istanbul

  • Dec-08-2025

    London

Course Details

Course Outline

5 days course

Understanding Data Science

  • Overview of data science: definition, importance, and applications.
  • Key roles and responsibilities in a data science team.
  • Introduction to data types and data structures.
  • Basic principles of data management.

Data Analysis Basics

  • Introduction to statistics for data science: Descriptive & inferential statistics.
  • Exploratory data analysis and data cleaning.
  • Data wrangling and transformation.
  • Introduction to regression analysis.

Introduction to Machine Learning

  • Defining machine learning and its importance in data science.
  • Overview of supervised, unsupervised, and reinforcement learning.
  • Basic machine learning algorithms: Regression, classification, and clustering.
  • Training and validation of machine learning models.

Data Visualisation

  • The importance of data visualisation in data science.
  • Understanding different data visualisation tools.
  • Creating impactful visualisations: charts, graphs, heat maps.
  • Effective storytelling with data.

Ethics and Future Trends in Data Science

  • Discussion on ethical considerations in data science: privacy, bias, and fairness.
  • The role of data governance in data science.
  • Emerging trends in data science: AI, Big Data, IoT.
  • The future of data science: skills for success.

Course Video