CertNexus Certified Data Science Practitioner (CDSP)

Price
Net €
VAT €

Price
Price on Request

Duration
5 days

For companies and job seekers:
this course is 100% fundable!
 

Location

Course Language
English

Training Solutions
Online Live

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Data is now at the heart of strategic decisions—modern analysis methods transform large amounts of information into clear patterns and reliable forecasts. The focus is on structured workflows, traceable modeling, and the responsible use of AI-supported processes.

Key topics

  • Data cleansing, transformation, and feature creation.
  • Analysis concepts, statistical tests, and pattern recognition.
  • Machine learning models for various problems.
  • Model evaluation, optimization, and reproducible pipelines.
  • Transparency, fairness, and practical documentation standards.

Prerequisite
Understanding of basic data processes and technical procedures.

Target audience
People from IT, data, business, or technology who want to create structured analyses and support decision-making processes with sound forecasts.

A compact insight into modern data science practice that combines current methods, clear processes, and sustainable AI application.
 

course content
  • Starting a data science project
  • Defining the data science problem
  • Extract information
  • Convert data
  • Integrate data
  • Analysis of data sets
  • Researching the distribution of data
  • Use of diagrams for data analysis
  • Preprocessing of information
  • Recognition of machine learning models
  • Verifying an assumption
  • Model training and optimization
  • Analysis of model performance
  • Developing and optimizing regression models
  • Analysis of regression models
  • Developing and adapting clustering models
  • Analyzing clustering results
  • Inform stakeholders
  • Present models in web applications
  • Implement and test production pipelines

Frequently asked questions

  • CDSP is a vendor-neutral data science certification that teaches practical skills in data analysis, modeling, and machine learning.
  • Topics covered include data preparation, statistical analysis, modeling, machine learning, model evaluation, and ethical aspects of data analysis.
  • Basic knowledge of mathematics, statistics, and programming is helpful but not essential. An interest in technology and logical thinking are often sufficient.
  • Ideal for professionals in IT, analytics, business intelligence, or related fields who want to build or deepen their knowledge of data science.
  • CDSP is practice-oriented, manufacturer-independent, and teaches real skills rather than tool specifics—ideal for application-oriented data projects.
  • The focus is on Python—because of its versatility and prevalence in the data science field. The basics will be explained during the training.
  • Yes, it offers a professional start, especially for positions in the fields of data analysis, AI, business intelligence, or data engineering.
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