Joint Technical Head
Novus Neuron Club (DYPIEMR)
2025 – Present
Guided junior members on machine learning projects and data science workflows, fostering a hands-on AI culture.
Ayush Ranjane
Understands prototyping, interaction, and intersecting data for everyone.
About.
01 / Who I amAspiring AI & Machine Learning Engineer with hands-on experience in building real-world AI systems. I specialize in predictive modeling, anomaly detection, and full-stack AI integration. My work focuses on environmental intelligence and industrial-scale data systems.
- Pune, India
- AI/ML Engineer
- CGPA 8.51
- 3 Projects
What I do
- → Machine Learning model development & optimization
- → Time-series forecasting (Prophet, ML models)
- → Anomaly detection using Isolation Forest
- → Full-stack AI systems (FastAPI + React)
Focus Areas
Environmental intelligence, industrial CO2 monitoring, air quality prediction, and building AI systems that make a tangible impact on sustainability.
Languages
EnglishProfessional
Hindi & MarathiNative / Fluent
GermanA1–A2
Experience & Education.
Milestones TimelineB.E. — Artificial Intelligence & Data Science
Dr. D. Y. Patil Institute of Engineering, Management & Research (DYPIEMR), Pune
2023 – 2027
Pursuing a comprehensive engineering degree with a specialized focus on machine learning algorithms, deep learning architectures, and data science workflows.
Higher Secondary (12th Standard) — Computer Science
Dnyansamwardhini Junior College, Shirwal, Satara
2021 – 2023
Graduated in the Bifocal Stream focusing on Computer Science fundamentals.
Secondary (10th Standard)
Dnyansamwardhini Vidyalaya, Shirwal, Satara
2021
Completed foundational secondary education.
Skills & Tools.
02 / Core competenciesMachine Learning
- Scikit-learn
- Prophet
- Isolation Forest
- XGBoost
- Pandas
- NumPy
Backend & APIs
- Python
- FastAPI
- PostgreSQL
- REST APIs
- SQL
Frontend & Viz
- React
- TypeScript
- Recharts
- Tailwind CSS
- Dashboards
Featured Projects.
03 / Case studiesApplied ML systems, not template demos
Production-style AI System01
GreenCO2
AI-Powered CO₂ Emission Monitoring & Compliance Platform. Track emissions, predict trends with Prophet, and stay compliant using automated alerts and anomaly detection.
The Problem
Industrial plants struggle with fragmented carbon accounting and regulatory compliance, leading to unexpected penalties.
Architecture Decisions
Chose Prophet over ARIMA for its superior handling of missing emission logs and weekly seasonality; used Isolation Forest for robust, high-dimensional anomaly detection without needing labeled outliers.
94%Forecast Accuracy
<50msAlert Latency
100%Compliance
- Python
- Flask
- React
- PostgreSQL
- Docker
AI Productivity Co-Pilot02
LifeSaver (Vibe2Ship)
A hyper-intelligent, AI-powered productivity OS. Uses Gemini to turn natural language into structured tasks, auto-schedule calendar slots, and diagnose procrastination.
The Problem
Modern builders suffer from cognitive overload trying to manage tasks, schedules, and goals across fragmented tools.
Architecture Decisions
Selected Gemini AI for superior natural language entity extraction over regex; utilized Firestore for sub-second real-time sync across clients.
<800msParsing Speed
100%Sync Accuracy
0Inbox Clutter
- Next.js
- Gemini AI
- Firebase
- Zustand
- Tailwind
Time-Series ML03
AQI Prediction System
End-to-end Air Quality Index forecasting system. Uses XGBoost and Random Forest to predict AQI from 11 distinct pollutant parameters with high precision.
The Problem
Citizens and authorities lack granular, localized air quality forecasts based on high-dimensional environmental sensor data.
Architecture Decisions
Deployed XGBoost over Random Forest for gradient-based optimization on non-linear pollutant correlations, ensuring maximum accuracy on messy real-world data.
0.92R² Score
<2.5RMSE
11Pollutants
- XGBoost
- Flask
- Scikit-learn
- Pandas
Certificates
← Scroll to explore my professional credentials →
🎓
Coursera | IBM
Dec 2023
Applied Data Science Capstone
Built an end-to-end predictive model using real-world SpaceX data.
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Coursera | IBM
Dec 2023
Collaborate Effectively for Professional Success
Mastered agile collaboration, communication, and team dynamics.
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Coursera | IBM
Oct 2023
Data Analysis with Python
Wrangled datasets and performed deep statistical analysis using Pandas.
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Coursera | IBM
Sep 2023
Data Science Methodology
Learned the foundational lifecycle of translating business problems to ML solutions.
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Coursera | IBM
Jan 2024
Data Scientist Career Guide and Interview Preparation
Prepared for technical interviews and mapped out a data science career path.
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Coursera | IBM
Oct 2023
Data Visualization with Python
Created interactive charts and dashboards using Matplotlib, Seaborn, and Dash.
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Coursera | IBM
Aug 2023
Databases and SQL for Data Science with Python
Wrote complex SQL queries to extract and manipulate large relational datasets.
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Coursera | IBM
Feb 2024
Deep Learning and Reinforcement Learning
Implemented neural networks and Q-learning algorithms using TensorFlow/Keras.
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Coursera | IBM
Nov 2023
Exploratory Data Analysis for Machine Learning
Extracted feature importance and detected anomalies in messy real-world data.
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Coursera | IBM
Mar 2024
Generative AI Elevate Your Data Science Career
Leveraged LLMs and prompt engineering to accelerate data science workflows.
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Coursera | IBM
Jan 2024
IBM Data Science
Completed the comprehensive 10-course professional certification track.
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Coursera | IBM
Mar 2024
IBM Machine Learning
Mastered the complete ML pipeline, from regression to deep learning.
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Coursera | IBM
Mar 2024
Machine Learning Capstone
Deployed a full-stack recommender system into production using Flask.
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Coursera | IBM
Nov 2023
Machine Learning with Python
Built and tuned robust classification and clustering models using Scikit-Learn.
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Coursera | IBM
Jul 2023
Python for Data Science, AI & Development
Mastered core Python programming, data structures, and foundational AI libraries.
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Coursera | IBM
Jan 2024
Supervised Machine Learning Classification
Trained advanced classification models including SVMs and Random Forests.
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Coursera | IBM
Dec 2023
Supervised Machine Learning Regression
Implemented highly accurate continuous prediction models to forecast trends.
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Coursera | IBM
Aug 2023
Tools for Data Science
Gained proficiency in Jupyter, RStudio, GitHub, and IBM Watson Studio.
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🎓
Coursera | IBM
Feb 2024
Unsupervised Machine Learning
Discovered hidden patterns using K-Means clustering and PCA dimensionality reduction.
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🎓
Coursera | IBM
Jun 2023
What is Data Science
Understood the vast applications of data science and AI in modern industries.
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Engineering Impact.
04 / Evidence-focused3+
AI systems built end-to-end
8.51
CGPA in AI & Data Science
100%
Projects shipped with real APIs
24/7
Real-time monitoring pipelines
How I build AI systems
I treat machine learning as a complete engineering system rather than just model training. It starts with the real business problem and clean, scalable data pipelines — then models validated for performance, stability, and real-world reliability, not just accuracy. Production-ready APIs integrate AI into applications, and dashboards turn complex predictions into actionable insights.
Let's build something impactful.
Open to AI/ML internships, research opportunities, and real-world problem solving.
I usually reply within 24 hours