Data Scientist with Python

This online course offers you a particularly practice-oriented learning concept with comprehensive self-study units and a team of mentors who are available to you at all times. A new chapter is activated for you every week. With a time budget of around 6 hours per week, you are sure to reach your goal in 17 weeks. This is how you learn in the course:

Placement test: In an onboarding meeting at the beginning of the course, you and the mentoring team will determine what knowledge you already have and which parts of the course you should pay particular attention to. This will prepare you optimally for learning in the self-study units.

Data Lab: In the course's learning environment, you can expect videos, interactive graphics, text and, above all, many practical exercises with comprehensive datasets and coding tasks. You carry these out directly in the browser - without installation or configuration effort and with direct success control.

Mentor team: Your learning coaches are available to answer any questions you may have. They are experienced data analysts who will be happy to help you - via chat, audio or video call.

Webinars: Once a week, you have the opportunity to take part in webinars and immerse yourself in selected special topics of data analysis.

Career coaching: What professional goals are you pursuing with your further training and how can you achieve them? A team of mentors is available to help you achieve your career goals.

Final project: In your own data project, you will work independently through the entire data pipeline and answer typical questions. At the end, you will present your project in a 1-to-1 feedback session with your mentoring team.

Certificate: After the final project, you will receive your official certificate as a Data Analyst with Python.

This online training is provided by our partner StackFuel GmbH. StackFuel specializes in training courses on data literacy, data science and AI.

In this practice-oriented training course, you will learn how to carry out data analyses with large data sets independently.

You will learn how to use Python competently, how to use the programming language for data evaluation and how to create effective visualizations.

You will learn how to connect a wide variety of data sources, filter data in them and merge them.

You will learn comprehensive methods, algorithms and technologies of machine learning and how to use them with Python packages.

You will learn everything you need to know about the use of deep learning and create an artificial neural network with several layers.

After the training, you will be able to examine company data, visualize it in a meaningful way and make it interactively accessible in dynamic dashboards.

The technical entry hurdles are minimized by the use of Jupyter notebooks, with which you can carry out the programming exercises directly in the browser.