Basics for data-driven thinking and working 

Data Literacy Course

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
  • Play Video

    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
    Data literacy course: Become data literate and learn to work in a data driven way.
    Online course
    12 hours
    4 modules + 2 business cases
    Beginner
    German or English
    Certificate of attendance
    € 290.00
    p.a. incl. VAT
    07.03.2022
    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

    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

    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 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
    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 

    07.03.2022

    Duration: 5 Weeks

    04.04.2022

    Duration: 5 Weeks

    02.05.2022

    Duration: 5 Weeks

    Dauer: 6 weeks
    Dauer: 6 weeks
    Dauer: 6 weeks

    Download the curriculum now.

    Curriculum_DL
    Curriculum_DL
    LEARNING ENVIRONMENT

    Train online in your browser in our interactive learning platform.   

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    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.

    Künstliche Intelligenz in Unternehmen: AI Literacy hilft Dir dabei, den Einsatz von KI in Unternehmen besser zu verstehen und Du bekommst die nötigen Kernkompetenzen, um bestehende und neue KI-Anwendungen anhand verschiedener Szenarien aus dem Business-Alltag sicher zu verstehen, für Dein Unternehmen erfolgreich zu übertragen und mit ihnen zu interagieren.
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