COVID has fundamentally changed how we work and learn in a few weeks only - everything is now digital. Therefore, it was a great pleasure to create, record, and host our free online course on >Artificial Intelligence and Machine Learning for Beginners< on openHPI. A project together with my fellow student and friend - Johannes Hötter.

With our online course on openHPI we have already reached over 15,800 learners and reached an average of 4.73/5 stars with 151 ratings (as of june 2022).

Motivation: Only a few months into knowing Johannes, we ideated about creating our own online course on Artificial Intelligence for Beginners. Our primary goal was to give back to the online learning community that we have benefited so much from in our university and professional careers.

Johannes and I both took part in courses from openHPI, edX, and Coursera while learning about AI and ML as well as other computer science or business-related topics.

The platform: With openHPI, the Hasso Plattner Institute (where Joahnnes and I study in our masters in “Data Engineering”) offers its own MOOC-Platform (“Massive Open Online Courses,” or MOOCs for short). On openHPI, one can get free access to the latest university knowledge in the rapidly changing fields of information technology and innovation. So far, this has mainly been done in German and English. In the meantime, roughly 982,000 course registrations have been registered on openHPI. 280,000 people from 180 countries currently belong to the platform’s permanent user base (August 2021). Partner platforms that work with the same learning technology are openSAP and openWHO.

For us, of course, this was a welcome opportunity to offer a course on openHPI. We, therefore, talked to the people responsible and started with the preparations after we agreed on the topic >Künstliche Intelligenz und Maschinelles Lernen für Einsteiger< (or in English: Artificial Intelligence and Machine Learning for Beginners).

The target audience: With our course, we try to target beginners in the field of Machine Learning and Artificial Intelligence, whereby we do not require any experience in mathematics or programming. Since Johannes and I have been learning the topic of machine learning ourselves recently, we both still had our learnings in mind. Almost all offers are for technical and mathematical intermediate to expert people and start with mathematical definitions from minute 5. To allow for discussions about this highly socially relevant topic possible for all people, we have deliberately dispensed with these prerequisites and tried to work with a more simple language.

The organization: The course is organized in four weeks, containing both video and textual lectures and self-quizzes after each video. After each week, there is a graded homework quiz, and after week 4, there follows the final exam in quiz form.

  • Week 1: Essential differences of conventional programming and machine learning.
  • Week 2: Basic concepts of supervised, unsupervised, and reinforcement learning, differences in data provision, concrete use case.
  • Week 3: Introduction to the process of how machine learning can recognize patterns, for example, in the context of supervised learning
  • Week 4: Outlook on the pace of progress in artificial intelligence, opportunities and risks and discussion of key ethical aspects.

The official course period was September 8th 2020 - October 6th 2020, but the online course is available for free self-paced learning anytime on openHPI.

Learnings: Overall, the success of the course really impressed us and made us very proud. We had a great audience with over 15,000 registrations (September 2021) and continuously still rising numbers. If we look back at the time, the preparation was very strenuous as it coincided with the exam period, and Johannes and I were also working or running a startup - but very rewarding and a great learning opportunity for ourselves. Some of the learnings, we summarized afterward as the following:

  • How to see the world through the eyes of the audience. Creating slides for regular presentations – almost everyone is on the same knowledge level, but having the 83yo “life-long-learner” Rudi with a background in physics or the 20yo psychology student is an exciting challenge but important to consider from the first minute.
  • An active learning community is important. Only in the four weeks of our course, there were more than 2,300 posts of learners with questions or feedback. It was, therefore, great to see that others who already understood the matter stepped in and helped and answered questions or ambiguities. Creating such an engaged community is an excellent leverage to the own work.
  • Being tangible and actively incorporate feedback. During the course, some topics (which we did not see at first) have triggered particularly many questions/ambiguities. In the feedback, learners especially outlined that our active engagement and the resources we provided left a good impression. This changes the learning style from “watching” videos to “being a learning community”/“classroom-mentality”. At least for us – a tangible teacher who incorporates feedback, answers questions, and responds to wishes creates a far more engaging environment.

Final remarks: Looking back, it was much fun to design the online course, prepare the content, and film it. It was a very new experience - I think I can also speak for Johannes here. Above all, it was very exciting to stand in front of a camera for the first time.

The feedback on the course was very positive - as reflected by the fact that we won the Marianne-Englert-Award (Association for Media Information and Media Documentation - in german Verein für Medieninformation und Mediendokumentation) for the course and Johannes had the opportunity to give an interview with Frankfurter Allgemeine Zeitung (FAZ) on the topic “How to make AI easy to understand](https://www.faz.net/aktuell/karriere-hochschule/hoersaal/kuenstliche-intelligenz-17071800.html).

This positive feedback made Johannes and I decide to create a second online course on openHPI - this time with a stronger focus on the practical application of AI. As before, we will not require any prior knowledge of math or programming, but we still want to show what it means to use machine learning in practice with four practical examples.

Update April 2022: As part of our presentation of our online course at the World AI Festival in Cannes (14th-16th of April 2022), the whole online course was subtitled in French, English, Arabic and German.

More on that in the post about our second online course :)