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Monday to Friday from 9:00 am to 6:00 pm
Independently implement a data science project for future applications.
The aim of the portfolio project module is to help you build up a portfolio. Career changers in particular are better able to convince potential employers with a convincing work sample than with their CV alone.
You will learn what employers look for in work samples in the field of data analytics and data science and which focus areas are suitable for you. Together with the mentors, you will select suitable data sets and questions. You will then develop projects for your application portfolio, either individually or in small groups, work on them independently with feedback from the mentors and present them online to an audience of participants and StackFuel employees.
In week 1 you will get to know your fellow module participants, be informed about the course of the module and gain initial insights into the components and building blocks of project work.
Learn more about the building blocks of a meaningful portfolio project and gain insights into sample projects from the Data Analyst and Data Scientist training program. Datasets are explored, evaluated for their suitability for a project and groups are formed around these projects.
You start with the local installation of the required software (Python, Anaconda, Git) and the setup of a virtual environment. Over the course of the week, you will learn and consolidate the use of Git and Github.
You create your first project board on Notion and are introduced to the most important functionalities of the project management tool. This will optimally prepare you for the collaborative and agile way of working in data and IT professions.
In Week 2 you will apply the principles of project management and learn how to organize your project well through formats such as daily standups, sprint planning, sprint retros, Kanban and individual group meetings.
You put full focus on the implementation of your project and are in constant communication with your mentor. You can choose the form of implementation that best suits your vision, from dashboards with Power BI to your own applications or websites.
In week 3 you finalize, document and clean up your code so that it meets industry standards. You structure and add to your Github repository so that employers can get a good idea of your first project when you apply.
Finally, you prepare a presentation in which your project group reports on the background and results of the project. You present them to other participants and mentors and discuss questions and feedback. After a successful presentation, the portfolio project is complete and you can contact the StackFuel Career Service to develop an application strategy.
Find your training program with us and start your data career! Book a non-binding consultation now.
Our training courses are developed and produced by our own team of data scientists and subject matter experts, who provide you as a participant with personal mentoring during the course. We not only focus on realistic and practical content, but also ensure that all your questions are answered in a personal exchange and thus guarantee your learning success.
Thanks to our "learning-by-doing" principle, you will learn in our interactive learning environment with realistic data sets and real business cases from the industry, preparing you perfectly for a successful career start in a data job.
With StackFuel, you can rely on a market leader with Germany's most innovative learning platform to develop your data skills in a practical way.in certified training programs you learn online, flexibly and with 80 % practical content.
This will enable you to make a lateral entry as a data analyst or data scientist and learn how to use data and the basics of artificial intelligence professionally. Your new data career starts with your online training at StackFuel.
Data has become an integral part of our (professional) lives. In almost all areas, data helps you to better understand facts and make more precise decisions. Data skills are the key to being able to use and interpret data correctly. Even though you may not realize it, you work with, interact with and generate data every day.
This data is becoming increasingly important for companies and is the basis for decisions and business models, which makes data professionals incredibly important for companies.
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