Data science is becoming an essential skill in today's business and academic world. As the demand for data scientists continues to grow, so does the need for quality data science education. However, it can be difficult to practice and apply data science techniques in physical and remote classrooms. Fortunately, Mineo is changing the way data science is taught and solving the challenges that arise.

In this article, we explain the main challenges a professor faces when teaching data science and how we solved them with Mineo.

Dealing with environments

The first thing a student needs to do when starting to experiment with data science and Python notebooks is to be able to configure and set up a proper environment on their computer. This is something that is difficult for many students today. Corporate computers with restricted permissions, lack of free resources (RAM or even disk space), and incompatibility of Python packages and tools with the operating system sometimes make it incredibly difficult to start writing a single line of code.

This is one of the things that sets Mineo apart from traditional data science education environments, providing an online environment where students can start programming immediately from any device without having to install a local development environment. This makes it incredibly easy for students to access and use the platform, making it a perfect tool for remote learning and for students who may not have access to a powerful computer. Even corporate students with tablets and iPads can interact with these technologies and quickly understand the value of data science.

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Keep up the pace at the classroom

Providing a personalised learning experience for each student can be a challenge. Especially in this age of blended learning, when students are in class and at home at the same time.

Mineo allows teachers to keep all students on the same page, providing a unified environment that is easily managed with permissions and groups. They can also monitor their students' progress, see how much they have completed, and provide timely feedback. This allows teachers to personalise their teaching and help their students more effectively.

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Collaboration

Another exciting feature of Mineo is that students can easily share their work with their teachers and classmates. This allows students to collaborate and get feedback from others, leading to a better understanding of concepts and a more engaging learning experience.

In addition to sharing, Mineo supports to add comments students and teachers directly on notebooks to start conversations and assign tasks to specific blocks.

Different levels of complexity

Providing a personalised experience for each student and group is another major challenge in education today. Each group has a different level of knowledge and as a teacher you need to choose the level that suits each student.

Mineo provides a friendly environment that adapts to each use. Instead of solving everything with code, which is the goal of traditional Python notebooks like Jupyter, Mineo provides widgets, which are components that implement common solutions without writing a single line of code. Widgets allow students to quickly and easily visualise data in tables and charts without having to write any code. This feature is great for those who may be new to programming or for those who want to quickly visualise data without spending time coding.

Conclusions

Overall, Mineo is transforming data science education by making it more accessible, interactive and collaborative. With its powerful features and ease-of-use, Mineo makes it easier for students to learn and master the essential skills required for data science.

Are you a student or teacher interested in using Mineo for your class or project? Feel free to contact us for an educational plan.