What Machine-Learning Students Think/Like/Know/Are …

This is another post in our series What Machine-Learning Students Think/Like/Know/Are …, which we began during teaching our Machine-Learning module at Trinity College Dublin, Ireland. Today, we present the machine-learning students’ experience and preferences of machine-learning libraries such as scikit-learn, Tensorflow, and Weka. This survey was conducted in one of the Read more…

Students apparently had a strong focus on the application of machine learning. Students could each distribute 100 points to the different categories, and most students (24% of the points) wanted to learn about machine learning frameworks like scikit-learn, or Tensorflow. However, also a deep understanding of algorithms was demanded (19%). Read more…

The majority of the machine-learning students believed their presentation skills to be average (41%), good (25%) or even excellent (18%). Only a small proportion rated their skills as poor (9%) or very low (7%).

According to the students´ self-assessment, they had – on average – average knowledge of JAVA (3.2 out of 5 points). However, there was quite a bit of variance. Many students had very little knowledge of JAVA, while others had excellent knowledge. The knowledge of C/C++/C# was similar to JAVA (3.1 on Read more…

The top careers for the machine-learning students were machine-learning engineer (16%), software engineer (16%), business start-up founder (14%), and data scientist (13%). However, also careers in project management (10%), research (9%) and consultancy (8%) were interesting to some students. “Business manager” was the least attractive career to the machine-learning students. Read more…

On average, the machine-learning students had average knowledge in databases and general writing (around 3 out of 5 points), below-average knowledge in writing research papers (1.9 out of 5 points), and little knowledge in machine learning (1.5 out of 5). The little knowledge about machine learning is not surprising though, Read more…

10% of the students had very low motivation to participate in the module, while the majority of the students had high (28%) or even very high (48%) motivation to learn about machine learning.