To become a data scientist, it is necessary to understand the practical realities of data analysis. Data encountered in the real-world is typically not the well-organized examples that appear in textbooks. Between the steps of collection and analysis, virtually all the data accumulated by organizations require multiple stages of “cleaning”. After this cleaning process, it is necessary to add various real-world constraints, analyze the data, and make proposals that are effective and useful to organizational leaders. To be successful, students need to prepare for this reality through experience prior to taking on a data science role in a company.
In our program, students can experience the entire process of real-world data analysis because the data we use is supplied by companies. Students are required to take the initiative and master the set of techniques necessary for analysis. Once they are proficient, not only do they perform the analysis and apply the results to actual business activities, they must also provide feedback to the companies that supplied the data. As part of this process, they will also develop their presentation and communication skills. In the Industry-Academia Collaboration Workshops, students are given the opportunity to present their own proposals to actual managers and company representatives.
As mentioned above, in our program students will learn about data science using data actually gathered by companies. However for some, this alone may not be sufficient. At an early stage in the learning process, it is also useful for students to learn how data is handled at actual business sites, and how they themselves can make a contribution. Therefore the DS program also offers a business internship program in which students gain workplace experience by working for a fixed time at a company. With this program it is possible for students to participate in an internship over the summer vacation after their first year.
For interested students, the internship program is a good opportunity to gain practical business experience – something that cannot be acquired in a graduate school classroom. This allows them to improve their ability to apply the theories and techniques they have learned in related classes. Students can also discover their own topics of interest for the future based on what they learn from their experience. Through the internship period, students can be expected to discover their own aptitudes and abilities, and improve their understanding of workplace environments.
Through close collaboration between universities, students can receive a specialized education via the sharing of teaching resources among our partner universities. This collaborative effort is a distinctive feature of our program and ensures the quality of our teaching material for improving students’ data analysis skills. By maintaining high educational standards reinforced through this collaboration and committing to constantly improving the quality of our program content, we will continue to produce capable graduates ready to embark on data science careers.