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CertNexus Certified Data Science Practitioner (CDSP)
Data is the raw material of modern decisions – this training shows you how to systematically prepare, analyze, and transform it into reliable forecasts using machine learning methods.
Key topics
- Prepare raw data: cleaning, transformation, and targeted feature engineering.
- Apply statistical tests and analysis methods to recognize patterns.
- Build and compare machine learning models for different problem types.
- Evaluate model quality, optimize pipelines, and make results reproducible.
- Work transparently, fairly, and according to clear documentation standards for AI applications.
Prerequisite
You should have a basic understanding of data processes and an interest in technical workflows – deep programming experience is not required.
Target group
Designed for professionals in IT, analytics, business intelligence, or adjacent fields who want to apply data science methods independently and support decisions with data-driven insights.
Structured, methodical, and focused on real data projects – this training prepares you for the full data science cycle.
course content
Launching data science projects strategically
- Identifying and formulating relevant business questions
- Defining the scope and objective of a data science initiative
Building and managing data pipelines
- Extracting data from various sources
- Transforming raw data into usable formats
- Integrating and making prepared data available
Conducting exploratory data analysis
- Systematically examining and understanding datasets
- Recognizing distributions and patterns in the data
- Using visualizations purposefully for analysis
- Preprocessing data and preparing it for modeling
Understanding and applying machine learning
- Getting to know fundamental ML models and their use cases
- Formulating hypotheses and testing them systematically
Training and evaluating classification models
- Developing, training, and fine-tuning classifiers
- Analyzing model performance and identifying areas for improvement
Developing and evaluating regression models
- Selecting and implementing suitable regression approaches
- Assessing model quality and improving predictions
Applying and interpreting clustering methods
- Building and adapting clustering models to your dataset
- Analyzing group structures and interpreting results
Completing and handing over data science projects
- Presenting results clearly for stakeholders
- Embedding and visualizing models in web applications
- Implementing, testing, and securing production pipelines
Up to 100% funding for your continuing education
Attractive funding opportunities are available for numerous continuing education programs – depending on the funding program, up to 100% funding is possible.
The requirement is that you live or work in Germany. Our funding opportunities are not available outside of Germany.
Funding opportunities are available for career starters, job seekers, career changers, startups, experienced professionals, those seeking career advancement, and specialists.
What does the CDSP certification stand for?
- The CertNexus CDSP is a vendor-neutral qualification that validates practical skills in data analysis, modeling, and machine learning – for real data projects, not just theory.
What exactly do I learn in CDSP training?
- You’ll work through data preparation, statistical analysis, modeling, machine learning, model evaluation, and ethical aspects – hands-on and step by step.
What prior knowledge do I need for CDSP?
- Basic knowledge of mathematics, statistics, or programming is helpful but not required. Logical thinking and an interest in data matter more than deep technical expertise.
Who benefits most from CDSP training?
- The training is aimed at professionals in IT, analytics, business intelligence, or related fields who want to build or deepen their data science knowledge systematically.
What makes CDSP stand out from other certifications?
- CDSP is vendor-neutral and practice-oriented – you learn applicable methods instead of tool-specific workflows, making it especially valuable for real-world data projects.
What languages and tools are used in the training?
- The focus is on Python, as it is widely used and versatile in the data science field. The necessary fundamentals are covered during the training.
How does the CDSP certificate help my career?
- CDSP opens doors to roles in data analysis, AI, business intelligence, and data engineering – as a recognized credential for practical, real-world data science skills.
