During my internship at AWS First Cloud Journey (FCJ) from January 4, 2026 to April 5, 2026, I had the opportunity to learn, practice, and apply my knowledge in a real-world working environment.
I participated in the Slothub project - an AI-powered location discovery platform, through which I improved my skills in cloud infrastructure, DevOps practices, software development, and AWS services.
As an extroverted person who enjoys communication, I always strived to complete tasks well, complied with workplace regulations, and actively engaged with colleagues and mentors to improve work efficiency. I maintained a strong sense of responsibility and consistently delivered quality work on time.
To objectively reflect on my internship period, I would like to evaluate myself based on the following criteria:
| No. | Criteria | Description | Good | Fair | Average |
|---|---|---|---|---|---|
| 1 | Professional knowledge & skills | Understanding of the field, applying knowledge in practice, proficiency with tools, work quality | ☐ | ✅ | ☐ |
| 2 | Ability to learn | Ability to absorb new knowledge and learn quickly | ✅ | ☐ | ☐ |
| 3 | Proactiveness | Taking initiative, seeking out tasks without waiting for instructions | ✅ | ☐ | ☐ |
| 4 | Sense of responsibility | Completing tasks on time and ensuring quality | ✅ | ☐ | ☐ |
| 5 | Discipline | Adhering to schedules, rules, and work processes | ✅ | ☐ | ☐ |
| 6 | Progressive mindset | Willingness to receive feedback and improve oneself | ✅ | ☐ | ☐ |
| 7 | Communication | Presenting ideas and reporting work clearly | ✅ | ☐ | ☐ |
| 8 | Teamwork | Working effectively with colleagues and participating in teams | ✅ | ☐ | ☐ |
| 9 | Professional conduct | Respecting colleagues, partners, and the work environment | ✅ | ☐ | ☐ |
| 10 | Problem-solving skills | Identifying problems, proposing solutions, and showing creativity | ☐ | ✅ | ☐ |
| 11 | Contribution to project/team | Work effectiveness, innovative ideas, recognition from the team | ✅ | ☐ | ☐ |
| 12 | Overall | General evaluation of the entire internship period | ✅ | ☐ | ☐ |
Strong foundation in AI/ML and Data: My background in artificial intelligence, machine learning, and data analysis provided a solid base for understanding the AI components of the Slothub project, particularly AWS Bedrock integration and data processing workflows.
Excellent communication skills: Being extroverted and enjoying interaction, I effectively communicated with team members, asked questions when needed, and actively participated in discussions and meetings.
High sense of responsibility: I consistently completed all assigned tasks on time and ensured quality deliverables, taking ownership of my work and following through on commitments.
Strong learning ability: Despite having limited experience in cloud computing and software development initially, I quickly learned new technologies, tools, and best practices through self-study and guidance from mentors.
Proactive attitude: I took initiative to explore new areas, seek out additional tasks, and contribute ideas to improve project outcomes without waiting for explicit instructions.
Cloud and DevOps expertise: While I have a good foundation in AI/ML and data, I need to deepen my knowledge and hands-on experience in cloud infrastructure, DevOps practices, and AWS services. This internship was an excellent opportunity to start building these skills.
Software development experience: I recognize the need to improve my practical software development skills, including best practices, code quality, testing, and software architecture patterns. The Slothub project helped me gain initial experience in this area.
Problem-solving in new domains: When encountering problems in unfamiliar areas like cloud infrastructure or software development, I sometimes need more time to analyze and propose solutions. I will continue to develop my problem-solving skills through practice and learning.
This internship at AWS FCJ was a valuable learning experience that exposed me to professional software development and cloud computing practices. It helped bridge the gap between my academic knowledge in AI/ML and the practical skills needed in the industry. I am grateful for the opportunity to work on a real project, learn from experienced mentors, and gain exposure to enterprise-level development practices.