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      Labmentix

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      Recensioni su Labmentix

      Supportive mentors and real-world projects, but tight deadlines - Recensione dipendente - Python Developer presso Labmentix

      4,0
      6 lug 2026
      Python developer
      Consiglia
      Gradimento del CEO
      Pronostico commerciale

      Vantaggi

      Great learning environment with supportive mentors. Worked on real-world Python, SQL, and REST API projects. Gained hands-on experience in teamwork, project management, and software development practices. Flexible and collaborative work culture.

      Svantaggi

      Some projects had tight deadlines, and documentation could be more detailed. More structured training sessions and regular technical workshops would further improve the learning experience.

      Esplora altre recensioni su Labmentix

      5,0
      6 lug 2026
      Intern in ai/ml
      Consiglia
      Gradimento del CEO
      Pronostico commerciale

      Vantaggi

      Gained practical exposure to real-world projects and industry practices. Improved technical, analytical, and problem-solving skills. Received valuable guidance and support from mentors. Enhanced teamwork, communication, and professional skills. Increased confidence and gained a better understanding of workplace expectations.

      Svantaggi

      I have no cons to be listed

      4,0
      16 feb 2026
      Data analyst
      Consiglia
      Gradimento del CEO
      Pronostico commerciale

      Vantaggi

      Worked on 4 real projects end-to-end (cleaning → analysis → dashboards). Used Excel, SQL, Python, Power BI, Streamlit (great tech exposure). Helped me build a portfolio I can show in interviews. Improved my data cleaning, SQL queries, and visualization skills. Clear learning path and good for beginners. Motivated me to present insights and think like a business analyst.

      Svantaggi

      Feedback could be more detailed and faster (especially on submissions). Would help to have more live sessions / Q&A during the program. Sometimes project instructions can be more clear (expected output, rubric). More examples/templates would help for Power BI and Streamlit projects. A bit more guidance on best practices (naming, formatting, documentation).

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