• Introduction Data Science

  • Group Training

    “The sexiest job of the 21st century”, claims the Harvard Business Review in 2012. With Data Science you try to make predictions and discover patterns from large amounts of data.

    Training code
    CGAIDASCCD
    Spoken Language
    Dutch
    Language Materials
    English
    Dayparts
    2
    Price
    €750,00
    excl. VAT No extra costs.

    Book Introduction Data Science now

    In group training, we use several learning methods to help you obtain the knowledge, give you helpful insights and get you inspired. Check the Spoken language and Language materials on the left for language info.

    • 13-3-2023
      Utrecht
      €750,00
      €750,00
    • 4-7-2023
      Utrecht
      €750,00
      €750,00
     

    What is Introduction Data Science

    “The sexiest job of the 21st century”, claims the Harvard Business Review in 2012. Data Science is an extension of classic data analysis as most know it. With Data Science, you try to make predictions and discover patterns from large amounts of data, which can provide valuable information needed to make decisions.
    In Introduction Data Science you learn to spot opportunities for a potential Data Science project and you take the first steps towards the real Data Science work.
    You will be introduced to terms such as
    Data Science Cycle

    • Supervised learning
    • Unsupervised learning
    • Time Series Forecasting
    • Natural Language Processing
    • Computer Vision

    We will discuss different types of Data Science methodologies and models. We also discuss how the correct formulation of a problem statement and good preparation of the data plays a major role in the validity of your analysis.
    During the training, the question "I have problem X, how do I solve this with the help of data?" central. During the training, participants are challenged to apply the theory to practical cases. The training is given by people who carry out Data Science projects in practice and who know what it is about. They want to pass on that practical knowledge.

     
     

    Who should attend Introduction Data Science

    The training Introduction Data Science is suitable for:
    Starters at the start of their career

    • People making a career switch to Data Driven Working
    • People working in IT, especially in departments such as Data Analytics
    • Data Analysts
    • Data Scientists

    Prerequisites

    Basic skills and general knowledge of data analysis. The 'Introduction to Data Analysis' course addresses these topics and is ideally suited to follow as a training course prior to this.

    Objectives

    After this training, the participant is able to answer the questions:

    • What steps do you take in a typical Data Science project?
    • What is the difference between Supervised and Unsupervised learning and when do you use one or the other?
    • What are common pitfalls and how do you avoid them?
     
    Incompany

    “The sexiest job of the 21st century”, claims the Harvard Business Review in 2012. With Data Science you try to make predictions and discover patterns from large amounts of data.

    Training code
    CGAIDASCCD
    Spoken Language
    Dutch
    Language Materials
    English
    Dayparts
    2
    Price
    €750,00
    excl. VAT No extra costs.

    With an Incompany training you have several advantages:

    - You choose the location
    - You experience the training with your colleagues, so it is always in line with your practice
    - The trainer can tailor explanations, examples and assignments to your organization
    - In consultation exercises can be adapted to organization-specific questions

    Request more information or a quote.

     

    What is Introduction Data Science

    “The sexiest job of the 21st century”, claims the Harvard Business Review in 2012. Data Science is an extension of classic data analysis as most know it. With Data Science, you try to make predictions and discover patterns from large amounts of data, which can provide valuable information needed to make decisions.
    In Introduction Data Science you learn to spot opportunities for a potential Data Science project and you take the first steps towards the real Data Science work.
    You will be introduced to terms such as
    Data Science Cycle

    • Supervised learning
    • Unsupervised learning
    • Time Series Forecasting
    • Natural Language Processing
    • Computer Vision

    We will discuss different types of Data Science methodologies and models. We also discuss how the correct formulation of a problem statement and good preparation of the data plays a major role in the validity of your analysis.
    During the training, the question "I have problem X, how do I solve this with the help of data?" central. During the training, participants are challenged to apply the theory to practical cases. The training is given by people who carry out Data Science projects in practice and who know what it is about. They want to pass on that practical knowledge.

     
     

    Who should attend Introduction Data Science

    The training Introduction Data Science is suitable for:
    Starters at the start of their career

    • People making a career switch to Data Driven Working
    • People working in IT, especially in departments such as Data Analytics
    • Data Analysts
    • Data Scientists

    Prerequisites

    Basic skills and general knowledge of data analysis. The 'Introduction to Data Analysis' course addresses these topics and is ideally suited to follow as a training course prior to this.

    Objectives

    After this training, the participant is able to answer the questions:

    • What steps do you take in a typical Data Science project?
    • What is the difference between Supervised and Unsupervised learning and when do you use one or the other?
    • What are common pitfalls and how do you avoid them?
     
  • Related

    Fields of Expertise
    Data Analytics
     
  • e-CF competences with this course

     

    At Capgemini Academy we believe in transparency and clarity in the training landscape. That is why, in the table below, we show you to which e-CF competence this training or certification contributes. For more information about how to use the e-Competence Framework read more here. If you want to know how you can apply the e-CF within your organization, read more on this page.

    e-Competence Level12345
    A.6.Application Design     
    D.10.Information and Knowledge Management     
    B.1.Application Development     
    E.1.Forecast Development