const careerTransition = {
background: "Agriculture Graduate 2023",
currentPath: "Self-Taught Programmer",
journey: "1.5+ years of intensive coding",
passion: "Discovered love for programming",
strengths: [
"🧠 Analytical Problem Solving",
"🌱 Growth Mindset",
"💪 Self-Learning Ability",
"🎯 Determination & Focus"
],
goal: "Bridge agriculture tech gap with code"
}; |
class UniqueCandidate {
vector<string> agriculturalSkills = {
"Data Analysis", "Research Methods",
"Problem Solving", "Project Management"
};
vector<string> techSkills = {
"Android Dev", "C/C++", "Linux",
"Python", "JNI Integration"
};
string getUniqueValue() {
return "Fresh perspective + Technical skills";
}
}; |
Coding Journey Right after graduation |
Practice Time Dedicated daily learning |
Built & Learning Hands-on experience |
Career Switch 100% committed |
What I've Built:
- 📱 Personal productivity apps
- 🌾 Agriculture-focused mobile solutions
- 🔗 Native integration experiments
- 🎨 UI/UX learning projects
Tech Stack: Kotlin Android Firebase Google Maps API Material Design
Features:
- 📊 Crop yield tracking and analytics
- 🗺️ GPS-based field mapping
- 📱 Weather integration for farming decisions
- 📈 Data visualization for farm insights
Why This Project:
- Combined my agriculture background with coding skills
- Solved real problems I understood from my education
- Learned mobile development through practical application
Technical Learning:
- Android app architecture (MVVM)
- Real-time database synchronization
- API integration and data handling
Tech Stack: C++ Linux System Calls Shell Scripting Process Management
Features:
- 💻 Real-time system resource monitoring
- 📊 CPU, memory, and disk usage tracking
- 🔍 Process management utilities
- 📈 Performance data logging
Learning Journey:
- Dove deep into Linux internals
- Mastered C++ for system programming
- Understood operating system concepts practically
Tech Stack: Java C++ JNI Android NDK Data Processing
Features:
- ⚡ High-performance data processing for agriculture datasets
- 🔗 Seamless Java-C++ communication
- 📊 Statistical analysis of crop data
- 📱 Mobile-friendly data visualization
Unique Aspect:
- Applied JNI knowledge to agriculture domain
- Combined background knowledge with new tech skills
- Performance optimization for large datasets
Tech Stack: Python Data Analysis Automation Web Scraping
Collection Includes:
- 🌡️ Weather data collection and analysis
- 📊 Crop price monitoring and alerts
- 📈 Yield prediction using basic ML
- 🔄 Automated report generation
Background Application:
- Used domain knowledge to identify automation opportunities
- Self-taught Python for practical problem-solving
LeetCode & HackerRank |
Android & Cloud Certs |
GitHub Contributions |
Showcase Projects |
|
🌾 UNIQUE PERSPECTIVE
|
💪 PROVEN SELF-MOTIVATION
|
🎯 HUNGRY & DETERMINED
|
B.Sc Agriculture (2023) Research Methods • Data Analysis • Project Management |
Domain Knowledge Agriculture Technology • Sustainability • Innovation |
Self-Taught Journey (2023-Present):
- 📱 Android Development - YouTube, Udemy, Official Docs
- 💻 C/C++ Programming - Books, Online Courses, Practice
- 🐧 Linux Systems - Hands-on Learning, Community Forums
- 🐍 Python - Automate the Boring Stuff, Real Python
- 🔗 JNI Programming - Official Documentation, Experimentation
- 📱 Google Android Developer Certification (In Progress)
- ☁️ Google Cloud Associate (Planned)
- 🐍 Python Institute Certifications (Next Goal)
