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Basics for Data-Driven Thinking and Working

Data Literacy

Course description

Data literacy is one of the most important skills of our modern working world. There is a reason people are referring to data as the gold of the 21st century. But we can’t derive value from data without a link between data literate humans and the data. More and more employees in today’s workplace need to collect, work with and understand data.

With our Data Literacy course, you will get to grips with the topic of data and acquire basic data literacy in order to process data profitably in your own company. You will expand your knowledge of the most important data technologies such as big data, artificial intelligence or the Internet of Things. By the end of the course, you will have a holistic overview of all the data processing steps and will be able to integrate data into your day-to-day work. Become data literate today.

In this  course you will learn:  

Get to know data technologies such as big data or artificial intelligence and learn how to differentiate between them

Learn about data processing procedures for data analysis and complex data models

Learn how to communicate professionally with data experts

Evaluate data projects and data visualizations

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Target Audience  

This beginner’s course is suitable for anyone who wants to become data literate and will encounter topics such as big data and artificial intelligence in their career or who would like to prepare for working with data in general. You should have a general interest in the world of modern data processing.

Prerequisites for participation 

No previous knowledge is required for the Data Literacy course

Online course

12 hours

4 modules + 2 business cases

Beginner

German or English

Certificate of attendance

€ 290.00 per membership

p.a. incl. VAT

Monthly

What to Expect

Course Overview

Python skills

With this entry-level course, you'll dive into the world of data and build data literacy skills.

Multi-level access

Learn about handling data professionally from leading data experts and their day-to-day work. 

Image Classification (CNN)

Apply and consolidate your knowledge in interactive tasks so you can apply what you learn in everyday life.

Python skills

With this entry-level course, you'll dive into the world of data and build data literacy skills.

Multi-level access

Learn about handling data professionally from leading data experts and their day-to-day work. 

Image Classification (CNN)

Apply and consolidate your knowledge in interactive tasks so you can apply what you learn in everyday life.

Modules

Chapter 1: Big Data

In the first chapter, you will be introduced to the world of “Big
Data”. This chapter focuses in particular on the steps in a typical
data analysis process, from its collection to the analysis. This
context allows participants to recognize the added value and
importance of high quality data in a structured form. You will learn
rules and guidelines on how to make sure data is of the necessary
quality.

Explanation of what Big Data means and its use case scenarios

Using data to make decisions

Understanding the data analysis process:

Overview of the whole process

Focus on structured data

Aggregation and data quality

Visualizing data I:

General Best Practices

Understanding bar charts and pie chart

Chapter 2: Datafication

In this chapter, you will learn to recognize the added value and the
opportunities data has to offer. You will learn all the relevant points
when it comes to implementing new data infrastructures and learn
about visualizing data to communicate the results as clearly as
possible and how to avoid confusion.

An introduction to data structures in companies

Understanding the data analysis process:

Focus on various data models

Dealing with missing data

Visualizing data II:

Understanding histograms

Best practices for line graphs

Information on location with maps

Chapter 3: Artificial Intelligence

Chapter three explains what the terms artificial intelligence,
machine learning and deep learning mean. You will be able to
assess what artificial intelligence can do as well as what it can’t do.
By learning the technical terms, you will be able to communicate
with employees in the data analysis departments on an equal
footing.

Definition and applications of Artificial Intelligence

Focus on machine learning

Supervised learning: Regression and classification

Unsupervised learning: Clustering

Importance of data quality

Recognizing correlations

Visualizing data III:

Interpreting scatter plots

Using regression lines to identify influencing factors

Chapter 4: Internet of Things

The final chapter “The Internet of Things” explains how sensors can
provide all kinds of different data. You will learn how this data can also
provide important insights. You will gain an understanding of how
connecting devices to a network can improve processes or lead to new
opportunities for added value.

Internet of Things, smart manufacturing and Industry 4.0

Clarification of key terms, opportunities and use case scenarios

Combining data from multiple sources

A/B testing principles

Presenting and interpreting data

Storytelling principles

Best practices for data storytelling

Start dates 

Download the curriculum now.

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LEARNING ENVIRONMENT

Train online in your browser in our interactive learning platform.   

StackFuel provides an innovative learning environment to develop your data skills in the most effective way – interactively and with real-world exercises. Learn to code in our Data Lab and develop algorithms and automate things with real industry datasets. Learn more now and benefit from 80% practical content in our courses.

WHY STACKFUEL 

We are your strategic learning partner - including mentoring & support.   

Whether you are an employee, a manager, or looking for a job – we will help you become a data expert with our certified and fundable upskilling and reskilling courses, which are suitable for every specialist department and every career level. We’ll ensure you learn successfully with our dedicated mentoring team to keep an eye on your progress. Our practical tasks and projects will prepare you for dealing with the latest technologies and applications.

Feedback

Here's what our graduates say.

The StackFuel Data Lab offers real added value for me. Here you can feel the practical relevance particularly well. The tasks were always clearly described and presented clearly. So I always knew what I had to do. The training itself was a great experience!

Alexander GroßData Analyst at AIC Portaltechnik

The practical relevance offers the greatest added value for me. Thanks to StackFuel, I can quickly implement what I have learned and adapt it for myself. This is the real learning success behind the online training.

Lutz SchneiderStrategic IT buyer at Axel Springer SE

The content of StackFuel's online training was very practice-oriented. There were many good examples and projects. I found that very interesting and instructive. My day-to-day work has changed significantly since the training: I am now a specialist for data analysis in my department.

Jaroslaw Wojciech SulakSpecialist for data analysis at IAV GmbH

The user-friendly and flexible further training in Python programming has completely changed my view of complex data structures. Thanks to the sustainable and well thought-out learning concept and the seamless application of the learning content in the development environment, I can now apply the newly acquired knowledge in test automation in my everyday work and since then I can process data more easily and efficiently.

Jenny LindenauTechnical management of test management at Bank Deutsches Kfzgewerbe GmbH

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Check out our learning platform now!

Find out why more and more leading companies are using StackFuel to train their employees online. In our a call with us, you’ll learn how your company can build data skills and make your workforce transformation a smooth success.

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Data Literacy

Course description

In this  course you will learn:

Target Audience