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Data science is the most technical step in the world of data, and that’s exactly why, when pursuing a data scientist training program with an education voucher, the first question isn’t „Which provider?“ but rather two others: Do you have what it takes to get started? And does the training go deep enough to truly turn you into a data scientist—rather than just someone who’s run a model once? This article addresses both of these questions before getting into the providers: first, an honest self-assessment; then, the question of technical depth; followed by the two typical entry paths; and finally, an overview of five AZAV-certified training programs.
Are You Ready for Data Science? A Quick Self-Assessment
A college degree isn't a formal requirement, but data science is technical, and honest providers will tell you that upfront instead of making it seem like every path into the field is equally easy. Consider these four points:
- Basic quantitative interest. Do you enjoy working with numbers, logic, and probabilities? Statistics is at the heart of data science—it's not just a nice-to-have.
- First experience with data. Have you worked with data before—for example, with SQL, Excel, or in an analyst role? It's not a requirement, but it makes getting started much easier.
- Time and perseverance. You can't learn data science in just a few weeks. Expect several months of focused work, regardless of the format.
- The joy of problem-solving. Building models means experimenting, failing, and making adjustments. If you find that exciting, you've come to the right place.
If you agree with most of these points, you're ready. If, on the other hand, you're just starting out in the world of data and have never worked with SQL or Excel, the most honest advice is: Start with a Data Analyst Training and switch to data science later. This saves you frustration and lays the very foundation on which data science is built. You can read about how the two roles differ in the article Data Scientist or Data Analyst?.
How to Tell If a Data Science Course Goes Deep Enough
Almost all established providers are AZAV-certified, so it is not accreditation that determines quality, but rather the depth of expertise. A good data science training program covers three interrelated levels.
The tool: Python instead of click-based tools. Data science is done using Python, supplemented by the appropriate libraries. A program that lets you set up machine learning simply by clicking through a user interface won't prepare you for the real world.
The Foundation: Statistics and Probability. Without a solid understanding of distributions, relationships, and uncertainty, no model can be meaningfully evaluated. Make sure that statistics is an integral part of the course and not just a side note.
The goal: to build and evaluate models. This is where the difference between a good course and a superficial one becomes apparent. It’s not enough to just run a model. You have to understand why it works, when it fails, and whether its results are even valid. A good program teaches you exactly how to make this kind of assessment on real projects—ideally resulting in a portfolio you can showcase in job applications.
Be skeptical of any provider that promises to turn anyone into a data scientist in just a few weeks. Equally important is the formal foundation: a AZAV certification of the provider and an entry in my NOW, the continuing education portal of the Federal Employment Agency, with its own program number. Asking for this number is the quickest way to verify its authenticity.
Two Paths to Data Science
It's rare to become a data scientist starting from scratch. In practice, there are two paths to the profession, and this will help you figure out which type of provider is right for you.
The academic path. You have a degree with a quantitative component—such as in the natural sciences, business, or engineering—and want to apply that knowledge to a career in data. In that case, you can enroll directly in an in-depth data science program that builds on your existing foundational knowledge.
The path through data analysis. You come from a different field and have some initial experience with data, perhaps as a data analyst. In that case, the most solid approach is to build your skills step by step: starting with applied data work and moving on to statistics and machine learning. Many successful data scientists started out exactly that way.
Both approaches are valid. The key is that the continuing education program meets you where you are and doesn't overwhelm or underchallenge you.
An Overview of 5 Subsidized Data Scientist Training Programs
The following list is organized by entry level and depth—ranging from academically oriented to highly technical—and is explicitly not a ranking. All providers are AZAV-certified and generally eligible for funding through the education voucher. We deliberately describe each course only in general terms; please check the specific duration, prerequisites, and prices directly with the provider and via mein NOW. We only provide specific figures for StackFuel because we stand behind them.
1. educx, Data Science for Academics. Tailors data science and AI training programs specifically to people with an academic background and builds on existing quantitative knowledge. A good fit if you want to build on what you’ve learned in college.
2. IfaDW, structured data scientist training program. Das Institut für angewandte Datenwissenschaft bietet eine AZAV-zertifizierte Data-Scientist-Weiterbildung mit klarem Curriculum und angewandtem Schwerpunkt. Passt, wenn Du einen geordneten, fachlich geführten Weg suchst.
3. StackFuel, applied data scientist continuing education, flexible online. Practical continuing education program to become a data scientist, covering Python, statistics, and machine learning—100 percent online, available full-time or part-time, and culminating in a portfolio project. We’re upfront about the fact that data science builds on foundational data literacy, and we often recommend that beginners with no prior experience start with our Data Analyst training program. AZAV-certified since 2020, with over 8,000 graduates and a 93 percent completion rate. This is a great fit if you want to dive deeper into the technical aspects while still learning flexibly.
4. Newcomers: An intensive introduction through a boot camp. Data Science and AI Bootcamp for a targeted career change, in German or English, online or in person, with extensive career coaching. A good fit if you’re studying full-time and want to make a quick career change.
5. WBS CODING SCHOOL, in-depth technical data science and AI development. Part of the WBS GROUP, offering programs that delve deeply into technical subjects and run over extended periods of time. A good fit if you’re pursuing the most technical path and have the time to dedicate to it.
This is just a selection of reputable providers. Read reviews with a critical eye, and pay less attention to the star rating and more to what is specifically said about support, the depth of expertise, and what comes after the training program.
Here's How the Education Voucher Program Works
All of the continuing education programs listed are generally available through the Education Voucher under Section 81 of SGB III You may be eligible if you are registered as a job seeker or at risk of unemployment. In that case, the Employment Agency will generally cover the full cost of the course; you won’t have to pay anything up front. There is no legal entitlement—it’s decided on a case-by-case basis—but with good preparation, your chances are good.
You can read about how the funding works in detail in Eligibility Requirements for Education Vouchers and Getting an Education Voucher Made Easy. If you're still wondering whether this career is right for you, here are some tips to help you decide What does a Data Scientist do? and How to become a Data Scientist continue.
Frequently asked questions
Do I need a college degree to become a data scientist? No, a college degree is not a formal requirement. However, data science is a technical field, so a basic interest in quantitative topics and some initial experience with data are very helpful. If you're just starting out, it's often better to begin with a data analyst training program and transition into data science later.
How does a data scientist differ from a data analyst? A data analyst analyzes existing data and answers business questions, typically using SQL, Excel, and a BI tool. A data scientist goes deeper, building models that make predictions using Python and statistics, and works with machine learning. Data science is therefore the more technical path and, for many, the second step.
Is a data scientist training program really free (0 euros) with the education voucher? Yes. If the provider is AZAV-certified, the Employment Agency generally covers the full cost of the course through the education voucher; you don’t have to pay upfront. There is no legal entitlement; it’s always decided on a case-by-case basis.
Get free advice
The quickest way to find out whether data science is the right path for you, whether you might be better off starting as a data analyst, and how you can finance your continuing education with an education voucher is to talk to us. In a free consultation Let's take a look together at your background, your goal, and the next concrete step. With absolutely no sales pressure.
StackFuel has been AZAV-certified since 2020. More than 8,000 graduates have completed continuing education programs in data and AI with us, with a completion rate of 93 percent.
