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AI Engineer with less than a year in Data Science & AI with 0.1 Years of internship experience.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final-year B.E. Computer Science and Engineering student with a solid foundation in programming, data analysis, and software design principles. Proficient in Python, Java, C, and C++, with practical experience in Object-Oriented Programming (OOP) using Java and C++. Skilled in web development and software development.
Anand institute of higher technology
B.E · Computer science and engineering
August 1, 2022 – June 30, 2026
NaviTech
Intern
November 1, 2024 – December 31, 2024
India
NaviTech
Intern
November 1, 2024 – December 31, 2024
India
NaviTech
Intern
November 1, 2024 – December 31, 2024
India
Gym Attendance System
June 1, 2026 – Present
User login attendance by unique id number of the members. Gym attendance system which can used to store the user attendance details and it was built on a cross platform application using cordova framework.
Crowd Specified Bus Tracking
June 1, 2026 – Present
Real-time bus Tracking Android Application built with Android Studio using Java and Android XML including Firebase Authentication and Database.
Cultural Fit Analysis
The candidate's academic projects demonstrate initiative in applying learned skills to practical problems (Gym Attendance System, Bus Tracking). The internships at NaviTech in AI, ML, and Data Analytics align well with an AI Engineer role, indicating a focused career interest. However, the brevity of descriptions limits the assessment of project diversity and depth of engagement. The candidate is a final-year student, which implies a learning-oriented mindset, but also a need for significant mentorship and structured development in a professional setting.
Soft Skills & Operational Fit
The candidate's resume indicates a foundational understanding of programming and data analysis. The internship experiences, though brief, suggest an interest in AI/ML. However, the descriptions of projects and internships are very brief, making it difficult to assess communication clarity or depth of involvement. There is no information regarding teamwork, problem-solving approaches, or adaptability from the provided data.