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Data Analytics and Data Science Portfolio Projects

Building an application portfolio for the job market

Certificate of completion

(Cross) boarding

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 audience

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

Table of contents

1
Introduction

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

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

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

Why should I choose a career in data, coding or AI?

The demand for data experts is high. Around 4 million data experts will be needed in Europe by 2025. In Germany alone, 149,000 IT jobs are currently vacant. The demand for data and AI experts in particular continues to grow enormously.

But a decision for a data career is so much more than just a safe decision for the future! As a data expert, you deal with powerful, socially relevant topics, are a tech professional, and are communicative and creative at the same time. The profession is varied, can be combined with most other professions and offers an attractive salary. And most importantly, with us it can be learned unerringly!

Am I qualified to work in this profession after further training as a data analyst and data scientist and can I make a lateral move?

Yes, after successful completion of the training, you will receive a certificate of completion from us that you can show in your job applications. Data Analysts and Data Scientists are desperately sought after in many business sectors. Even without relevant work experience, your chances of finding an entry-level job are good. In addition, there are analysts in almost every industry who have different job titles, but the skills you need are the same as those of a data analyst or data scientist.

Can I really organize my learning time freely?

Yes, our online training courses are designed to offer you the greatest possible flexibility. In general, we recommend that you plan six to eight hours per week for learning. When you want to schedule this time is up to you and is not prescribed by us. In our career paths, the Data Analyst and Data Scientist course, we offer live webinars where you can ask our mentors questions, but you don't have to attend if it doesn't fit into your schedule.

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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 course 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 courses.

Lutz Schneider
Strategic IT Buyer at Axel Springer SE

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The content of StackFuel's online course was very practical. There were plenty of good examples and projects. I found that very interesting and educational. Since the course, my day-to-day 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 course 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 new things I've learned in my day-to-day work in test automation in more detail and process data more easily and efficiently than before.

Jenny Lindenau
Technical Manager Test Management at Bank Deutsches Kraftfahrzeuggewerbe GmbH

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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