Tirth PatelAI Engineer
OPEN TO AI / SOFTWARE ENGINEERING ROLES & MASTER'S RESEARCH

Tirth Patel

BCA Graduate

Aspiring AI Engineer • Python Developer

Building intelligent software with Python, AI, and modern web architectures.

Computer Science graduate with a solid foundation in software engineering, backend systems, and applied machine learning. Creator of real-world AI applications including multi-agent career guidance, predictive skill gap analyzers, and the 100 Days of Python Lab. Currently preparing for advanced Master's studies in Computer Science & Artificial Intelligence.

Education
BCA Distinction
Python Lab
100 Days
AI & ML Practice
Applied AI
Industry Practice
5 Internships
Explore Projects100 Days Python LabResume (PDF)
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Tirth Patel

Aspiring AI Engineer • Python Developer

$focus
Applied AI & NLPMachine Learning PipelinesPython 3.11+FastAPI & Microservices
$status
Building AI systems → 100 Days Python Lab → Preparing Master's Research
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Empirical Track Record

Verified Technical Background

Backed by real repositories, project code & documented implementations
Degree Verified

BCA Computer Science

Academic Foundation

Rigorous undergraduate training in algorithms, discrete mathematics, OOP, and relational database systems.

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3 AI Projects

Production AI & NLP Systems

Applied Engineering

Built multi-agent platforms with Gemini API, Random Forest with watsonx.ai, and TF-IDF skill gap analytics.

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100 / 100 Days

100 Days Python Lab

Systematic Code Journey

100 distinct Python problem sets spanning classical algorithms, Tkinter GUIs, Flask APIs, and Scikit-learn pipelines.

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Appointment on File

AI Research Internship

Industry Appointment

Appointed at UptoSkills focusing on applied AI research, API integrations, and machine learning pipeline development.

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Hackathon Project

Hacklabify Hackathon

AI/ML Track Participant

Built and submitted SkillSync AI, an intelligent talent match and predictive skill gap analytics system.

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Research Aspirant

Academic Focus for Master's

Graduate Preparation

Focusing on multi-agent systems, scalable inference pipelines, and mathematical foundations for M.S. programs.

View evidence
Interactive Python Code Explorer

100 Days of Code: Complete Python Architecture Studio

Explore 100 structured days of verified Python implementations featuring an in-browser Pyodide WebAssembly runner, real stdout/stderr execution, line numbers, and multi-format outputs.

Launch Python Lab
Competency Matrix

Technical Skill Architecture

Categorized by practical application, systems engineering, and algorithmic mastery. Grounded in actual production code and project repositories—free from subjective fake percentage bars.

AI & Machine Learning

4 core competencies

Machine Learning & Scikit-Learn

Advanced

Classification algorithms (Random Forest, SVM), model evaluation, 5-fold cross-validation.

#Random Forest#Cross-Validation#Metrics#Pipelines

NLP & Vectorization

Advanced

TF-IDF text vectorization, cosine similarity, tokenization, semantic search matching.

#TF-IDF#Cosine Similarity#Text Mining

LLM & Agentic Workflows

Proficient

Multi-agent systems, Google Gemini API, IBM Granite (watsonx.ai), prompt engineering.

#Multi-Agent#Gemini API#watsonx.ai#Prompt Engineering

Feature Engineering & Data Preprocessing

Advanced

Handling missing data, standard scaling, categorical encoding, ratio feature derivation.

#StandardScaler#Imputation#Feature Extraction

Programming Languages

4 core competencies

Python 3.11+

Core

Advanced OOP, decorators, generators, concurrency, async I/O, algorithmic problem solving.

#100 Days of Code#AsyncIO#OOP#Data Structures

TypeScript

Core

Strong typing, interfaces, generics, Next.js App Router integrations.

#Type Safety#Generics#Modern Web

JavaScript (ES6+)

Core

Event loops, DOM manipulation, asynchronous programming, modern ES syntax.

#Promises#Async/Await#Modular JS

SQL

Proficient

Relational queries, joins, aggregations, indexing, schema design.

#PostgreSQL#SQLite#Relational Design

Backend & Systems

4 core competencies

FastAPI

Advanced

Pydantic validation, dependency injection, OpenAPI documentation, asynchronous endpoints.

#Pydantic#Async Endpoints#Microservices

Next.js & React

Advanced

App Router, Server Components, client state management, responsive UI systems.

#React 19#Server Components#Tailwind CSS

Celery & Redis

Proficient

Distributed background task execution, asynchronous queues, worker scheduling.

#Task Queues#Redis Caching#Workers

Flask & Node.js

Proficient

Lightweight microservice backends, REST APIs, middleware architectures.

#Express.js#Jinja2#RESTful

Data Science & Databases

4 core competencies

Pandas & NumPy

Advanced

Vectorized arrays, multi-index aggregation, dataset slicing, time-series handling.

#Vectorization#DataFrames#Aggregations

PostgreSQL & SQLAlchemy / Alembic

Proficient

Relational modeling, migrations, ORM queries, transactional consistency.

#Migrations#Alembic#ORM

MongoDB Atlas

Proficient

Document store schema modeling, aggregation pipelines, cloud clusters.

#NoSQL#Mongoose#Atlas M0

Matplotlib & Chart.js

Proficient

Scientific charts, confusion matrices, data distribution histograms, dashboard visuals.

#Data Viz#Confusion Matrix#Dashboards

Tools, DevOps & Testing

4 core competencies

Docker & Docker Compose

Proficient

Multi-container environment orchestration, reproducible builds, network isolation.

#Containerization#Microservices

Locust Load Testing

Proficient

High-concurrency user simulation, throughput benchmarking, bottleneck identification.

#Performance Testing#Benchmarking

Git & GitHub

Core

Branching strategies, pull request workflows, CI/CD actions, version management.

#Git Flow#Version Control#Collaboration

Linux & Bash / PowerShell

Proficient

CLI automation, server administration, shell scripting, environment configuration.

#CLI#Automation#Shell Scripting
Academic Focus & Graduate Preparation

Academic Direction & Master's Statement

My academic pursuit is driven by a deep fascination with machine learning systems, multi-agent coordination, and bridging the divide between mathematical modeling and high-throughput production software. Through rigorous self-directed development—from mathematical data preprocessing to distributed FastAPI microservices—I have built an empirical foundation ready for graduate-level research and innovation.

Undergraduate FoundationCompleted

Bachelor of Computer Applications (BCA)

Veer Narmad South Gujarat University (2021 – 2024)

Cumulative Grade:CGPA 7.52 (First Class with Distinction)
Final Semester SGPA:8.27 (462 / 550 Marks)

Core coursework encompassed Data Structures, Design and Analysis of Algorithms, Object-Oriented Software Engineering, Discrete Mathematics, Relational Database Management Systems, and Web Architectures.

Target Program: Master of Science in Computer Science / Artificial Intelligence
Specific Research Interests:
Multi-Agent Coordination & Agentic AI ArchitecturesNatural Language Processing & Semantic SearchPredictive Analytics & Human-AI CollaborationRobust Machine Learning Systems in Production
“Graduate studies represent an opportunity to transform practical engineering skills into rigorous research contributions that advance real-world artificial intelligence.”

Preparation Pillars for Advanced Research

Theoretical & Mathematical Grounding

Deepening knowledge of linear algebra, multivariate calculus, probability distributions, and algorithmic complexity underpinning modern neural networks.

Active Preparation

Empirical System Building

Moving beyond toy examples by implementing full-stack ML workflows, feature pipelines, TF-IDF vectorizers, and Random Forest classifiers on real governmental datasets.

Active Preparation

Distributed Backend Architecture

Engineering resilient microservices with FastAPI, Celery background queues, Redis caching, and containerized deployments ready for scale.

Active Preparation

Commitment to Continuous Mastery

Demonstrated through 100 consecutive days of Python projects spanning low-level algorithms, data science notebooks, and capstone full-stack tools.

Active Preparation
Industry Practice & Roles

Work Experience & Engineering Milestones

Real-world backend software development, high-throughput microservices, and applied AI systems.

AI/ML Intern

Internship
Creative Web InfotechSurat, Gujarat, IndiaDecember 10, 2025 – January 09, 2026
Completed industrial internship and on-the-job training facilitated through Sutex Bank College. Awarded Grade O (Outstanding, 48.5/50 marks) (Certificate ID: CWI20261200) under supervisor Haresh Shiyani for engineering predictive classification pipelines in Python and optimizing relational schemas in MySQL.

Core Engineering Contributions:

  • Machine Learning Development: Developed and implemented predictive classification and regression models in Python to address empirical data analysis tasks.
  • Data Engineering: Performed rigorous data preprocessing, null imputation, and feature engineering to optimize model accuracy and reduce training variance.
  • AI Integration: Collaborated on integrating ML model inference into web-based platforms, bridging core algorithm logic with user interfaces.
  • Research & Evaluation: Evaluated various supervised algorithms and Python libraries to determine optimal trade-offs between latency and recall.
  • Technical Documentation: Formulated comprehensive documentation covering model architectures and evaluation metrics for reproducibility.

Verified Deliverables

  • • Awarded Grade O (Outstanding, 48.5/50 marks) evaluated by industry reviewers.
  • • Official Completion Certificate on file (ID: CWI20261200).
PythonPandasNumPyScikit-LearnClassification ModelsFeature EngineeringMySQL

Virtual Data Science with Python Apprentice Intern

Internship
YuvaIntern (Henry Harvin Education)RemoteJuly 23, 2026 – August 27, 2026
Completed virtual internship program in Data Science & Python programming. Awarded official Certificate of Experience (Certificate No: YI/2026/135101/332365) signed by Kounal Gupta for structured exploratory data analysis (EDA), statistical distribution plotting, and automated data processing pipelines.

Core Engineering Contributions:

  • Conducted exploratory data analysis (EDA), outlier detection, and data cleansing across complex tabular datasets.
  • Implemented statistical summaries, correlation heatmaps, and distribution plots using Matplotlib & Seaborn.
  • Assisted in developing automated data transformation scripts and validating dataset integrity against schema standards.

Verified Deliverables

  • • Awarded official Certificate of Experience (ID: YI/2026/135101/332365).
  • • Official Offer Letter on file (Ref: YI/2026/135101).
PythonData CleaningStatistical AnalysisMatplotlibSeabornEDA

Virtual Data Science Explorer Intern

Internship
YuvaIntern (Henry Harvin Education)RemoteJuly 23, 2026 – August 20, 2026
Completed foundational internship track as a Data Science Explorer. Awarded official Certificate of Experience (Certificate No: YI/2026/135101/332312) signed by Kounal Gupta for hands-on data exploration, mathematical array operations with NumPy & Pandas, and visual analytics.

Core Engineering Contributions:

  • Performed hands-on data manipulation, filtering, and aggregation using Pandas & NumPy.
  • Analyzed multidimensional data structures and generated visual reports for empirical observations.
  • Verified data pipelines and contributed to dataset hygiene protocols.

Verified Deliverables

  • • Awarded official Certificate of Experience (ID: YI/2026/135101/332312).
  • • Official Selection & Offer Letter on file (Ref: YI/2026/135101).
PythonNumPyPandas BasicsData ExplorationVisual Analytics

Emerging Technologies Intern (AI & Cloud)

Internship
Edunet Foundation & AICTE (IBM SkillsBuild)Remote / IndiaAugust 17, 2026 – September 11, 2026
Selected through the AICTE Internship Portal (Student ID: STU6a4fa5579627b1783604567) for a specialized program in Emerging Technologies (AI & Cloud) leveraging IBM SkillsBuild & IBM Cloud enterprise architectures.

Core Engineering Contributions:

  • Completed foundational learning tracks in artificial intelligence architectures, machine learning concepts, and cloud service models.
  • Earned verified IBM SkillsBuild credentials in AI fundamentals and cybersecurity defense principles.
  • Participated in virtual technical labs and explored hands-on code troubleshooting in cloud sandboxes.

Verified Deliverables

  • • Official AICTE & Edunet Foundation Internship Offer Letter on file (Signed by Nagesh Singh, Chairman).
  • • Earned verified Credly badges in Artificial Intelligence and Cybersecurity.
IBM Cloud PlatformIBM SkillsBuildArtificial IntelligenceCloud ArchitecturePython

AI Research Intern

Internship
UptoSkillsRemote / IndiaSeptember 18, 2026 – December 18, 2026
Appointed as AI Research Intern (Ref No: US/HR/2026/181T8C) reporting to Shivam Agarwal. Focuses on applied AI research, REST API integrations, and machine learning pipeline development with FastAPI and Python 3.11.

Core Engineering Contributions:

  • Researching state-of-the-art applied machine learning architectures and vector search paradigms.
  • Prototyping FastAPI backend microservices with strict Pydantic schema validation.
  • Collaborating on data engineering workflows and AI benchmark evaluations.

Verified Deliverables

  • • Official Appointment Letter on file (Ref: US/HR/2026/181T8C).
Python 3.11FastAPIMachine LearningREST APIsData Pipelines
Competitive Hackathons

Hackathon Submissions & Track Recognitions

Build with AI • Generative AI & Foundation ModelsCertificate of Appreciation • Verified Generative AI Challenge 4 Submission (ID: 2026H2S07PWVCHL4-A00792)

PromptWars Virtual • Google for Developers & Hack2Skill

Project: Generative AI Solution Challenge 4 • August 25, 2026

Problem & Solution: Designed and submitted a verified Generative AI pipeline utilizing structured prompt engineering, output schema validation, and API integration for automated domain problem solving.

Generative AIGoogle Cloud AIPrompt EngineeringPythonRESTful APIsLLM Workflows
Inspect Hackathon Project
Artificial Intelligence & Open Innovation TrackCertificate of Secure Top 200 (Verified via GoCertiflo)

Hacklabify V1.0 • Sillionona Technologies

Project: SkillSync AI: Intelligent Talent Match & Predictive Skill Analytics • August 2026

Problem & Solution: Engineered an NLP-powered skill assessment engine that compares candidate skills against industry datasets using TF-IDF vectorization and cosine similarity, categorizing missing skills into an actionable learning path.

PythonScikit-learnTF-IDF VectorizationCosine SimilarityStreamlitPandas
Inspect Hackathon Project
Get In Touch

Let's discuss AI engineering & graduate research.

Whether you are reaching out regarding AI engineering opportunities, distributed machine learning systems, or graduate academic research collaboration, my inbox is open.

Primary Inquiries
tirthpatel82032@gmail.com
GitHub Profile
/Tirth3929v
LinkedIn
/in/tirth-patel-ai

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