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Data Analytics and Data Science Portfolio Projects

Building an application portfolio for the job market

Certificate of completion
(Cross) boarding
Full time/part time
German, English
Free of charge with education voucher
Course description

The goal of this course is the accompanied development of a portfolio of projects. Career changers in particular are usually better able to convince potential companies 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 focal points are suitable for you. Together with your mentors, you will select suitable data sets and questions. You will then work on projects for your application portfolio, either individually or in small groups.

In this training you will learn
Set up data projects
Presenting data
Agile project management
  • Independent selection and professional implementation of data analytics and data science projects
  • Local creation and publishing of projects
  • Presentation of results and discussion using
    From technical language

Target group

The training is suitable for you and your career aspirations if you have a degree, ideally in the fields of mathematics, computer science, natural sciences, technology, business administration, (business) information technology or have a comparable qualification or previous experience. You should also have already completed further training as a Data Analyst, BI Analyst or Data Scientist.

Requirements for participation

Confident use of Data Analytics workflow with Python or SQL and Power BI or confident use of Data Science workflow with Python.

Learn more about our training
Introduction to BI and Data Analytics

Modules

1
Introduction
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Objectives:
- Strategic selection of projects
- Creating and publishing projects locally
- Carrying out projects in a structured way

Content:
- Introduction:
• Getting to know each other
• Course schedule and look at building blocks
• Introduction to the learning environment
- Selecting a data project:
• Principles for good projects
• Example data analytics and data science projects
• Sources for suitable datasets
• Licenses for datasets
• Estimating how much work will go into a data project
- Weekly Overview:
• Setting up your work environment:
• Installing Python and the necessary modules locally
• Introduction to GitHub Pages
• Optional brief introduction to Git
• Structured working in data teams:
• Data analytics workflow
• Data science workflow
• Starting portfolio work:
• Preparation
• Division into teams and assignment to proposed projects
• Creating a project plan and assigning tasks

2
Basics of agile project management
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Objective:
- Carrying out projects in a structured way

Content:
- Principles of Agile project management:
• Daily stand-ups
• Sprint planning
• Sprint retrospective
• Kanban
• Online project management tools
- Continuation of project work

3
Completion of the project work incl. presentation
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Objective:
- Presentation of results and discussion using technical terminology

Content:
- Completion of project work
- Final presentation:
• Creating the final presentation
• Presenting the final presentation to the other teams and mentors

FAQ
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The StackFuel Data Lab offers me real added value. Here you can feel the practical relevance particularly well. The tasks were always clearly described and presented. So I always knew what I had to do. The training itself was a great experience!
Alexander Gross
Data Analyst at AIC Portaltechnik
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The greatest added value for me is the practical relevance. Thanks to StackFuel, I can quickly implement what I've learned and adapt it for myself. That is the real learning success behind the online trainings.
Lutz Schneider
Strategic IT Buyer at Axel Springer SE
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The content of StackFuel's online training was very practical. There were many good examples and projects. I found that very interesting and instructive. Since the training, my everyday professional life has changed significantly: I am now a data analytics specialist in my department.
Jaroslaw Wojciech Sulak
Specialist for data analysis at IAV GmbH
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The user-friendly and flexible Python programming training has completely changed my view of complex data structures. Thanks to the sustainable and well thought-out learning concept as well as the seamless application of the learning content in the development environment, I can now implement the newly learned knowledge in my everyday job in test automation in greater depth and process data more easily and efficiently since then.
Jenny Lindenau
Technical Manager Test Management at Bank Deutsches Kraftfahrzeuggewerbe GmbH
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Let's start with a consultation.

Our consultants will be happy to help you and answer all your questions. Free of charge and without obligation. We look forward to meeting you.
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