Smart Data Science: Your entry into professional data analysis (Online)

This online course offers you a digital blended learning concept that has been specially developed for part-time learning. With a time budget of at least 3-4 hours per week, you are sure to reach your goal. Alternatively, you can schedule the learning units flexibly. This is how you learn in the course:

Self-study phases: Learn independently, at your own pace and whenever you want. Our courses offer you didactically high-quality learning material with videos, articles, interactive exercises, quizzes and learning checks.

Live webinars: In regular online seminars, you will meet your trainers in person. You will receive answers to your questions, specific assistance and instructions on how to deepen your knowledge and apply the skills you have acquired in practical exercises.

Practical assignments: To learn the skills in practice, you will be given access to data projects that allow you to apply the techniques and methods you have learned to real-world problems. Through these exercises, you will gain a deep understanding of working with data and develop methods and techniques that you can apply in your everyday work.

Learning community: A digital learning community is available to you throughout the course. Exchange ideas with other participants and the trainers and clarify your questions.

Certificate of attendance and Open Badge: As a graduate of the course, you will receive a certificate and an Open Badge that you can easily share in professional networks (e.g. LinkedIn). 

Future Jobs Club: Get exclusive access to a business network, micro-learningssparks), news and future work hacks.

In your online learning environment, you will find useful information, downloads and extra services for this training course once you have registered.

Are you a decision maker and want to gain more than just an overview of data science? Are you a subject matter expert and want to make better use of the data you deal with every day? Here's what you'll take away from this data science course:

• You can assess how you are positioned in the area of data science and what potential lies in the company's data.
• You will gain comprehensive and application-oriented insights that you can use as a basis for data-driven decision-making processes.
• You will develop a business understanding of data analysis across various industries and learn how to define goals for data projects using concrete scenarios.
• You will learn the basic steps of a data science project along the cross-industry framework CRISP DM.
• You will carry out your first data analyses in exercises and practice with real data sets.

Dennis Bogen