I didn't have any prior experience or background in the data field. I moved to Berlin last year and I want to change my career and get a job as soon as possible. The Data Analyst position is highly recommended on the internet, and I decided to study this field. However, I didn't want to spend 3 or 4 years at university studying computer science or a related field. I wanted a more practical and intensive course, so I decided to enroll in the bootcamp at CAB.

What are the reasons you chose Code Academy Berlin?

I contacted several organizers of Berlin Tech Bootcamps and had short interviews. When I talked with the admission advisor, I asked her about the CAB's strong points compared to the many others in the area. She mentioned that one of the strengths was its small group size with enthusiastic mentors. I thought I would fit well into this course because I always need a lot of help from mentors, so I decided to take your course.

About the Data Analytics course

The expertise of the Data Science Lead Mentor, Killian, was always evident, and he had a deep understanding of almost every topic related to data. When discussing project ideas, he already had a grasp of the potential challenges and solutions I might encounter. He gave me time to work through issues on my own but was always ready to provide clear guidance when I needed assistance. Another mentor, Muayad, emphasized not giving unilateral feedback but rather prioritized understanding how I thought about problems. This helped me identify and address issues on my own. I received a lot of support from my cohort. They were always kind and patient, listened to me very well, and I enjoyed studying with them. We still keep in touch sometimes.

About your learning experience

I learned a lot from the course, from necessary technical skills to soft skills like storytelling. I really enjoyed the learning experience, especially with the e-commerce analysis project. In that project, I derived insights from customer data through visualization and conducted clustering analysis based on Customer Lifetime Value (CLV) to provide business recommendations using Python, SQLite, data visualization (Tableau), and machine learning (clustering). It was very rewarding.

About your life after the Academy

After the course, I felt I needed more practice. So I started learning from other online courses and working on my personal projects while continuing to apply for data analyst positions. I believe one day I can get a job as our alumni have done.