ML&GenAIPortfolio

Mastering Generative AI & Agents for Developers

CodeCademy Bootcamp6 Weeks6 Projects
Completed

ModelViz

Featured

Interactive analytics platform for comparing AI models across multiple providers with real-time performance metrics, cost analysis, and 3D visualisations

ModelViz screenshot
Next.js 16React 19TypeScriptThree.jsFramer Motion
Completed

Morpheus

Week 3

Intelligent document Q&A system with semantic search and source citations using RAG

Morpheus screenshot
PineconeAnthropicOpenAILangChainFastAPI
Completed

Code Generator

Week 1-2

Generate production-ready code with AI assistance

Code Generator screenshot
LangChainGPT-4oPythonFlaskReact
Completed

SQL-Ball

Final Project

Football data analytics with natural language queries and AI insights

SQL-Ball screenshot
SupabaseLangChainReactOpenAIPostGresSQL
Completed

ReviewBot Protocol

Week 2

AI-powered GitHub PR reviews with automated code analysis and intelligent feedback

ReviewBot Protocol screenshot
Next.js 15FastAPILangChainLangGraphPostgreSQL
Completed

Portfolio Dashboard

Meta Project

Interactive AI course portfolio showcasing projects and learning journey

Portfolio Dashboard screenshot
Next.js 15TypeScriptTailwind CSSAnime.js

Skills & Technologies Demonstrated

Expertise in cutting-edge technologies valuable to employers

Gen AI
Azure AI Foundry
RAG pipelines
Machine Learning
LLMs
Python
C#
APIs
OpenAI
LangChain
TypeScript
React

My Learning Journey

Transforming from developer to AI engineer through the Mastering Generative AI & Agents bootcamp

Course Duration: August - September 2025 (6 Weeks)

Projects Completed: 6 Production-Ready Applications

Technologies Mastered: 12+ AI/ML Frameworks & Tools

What I Learned

  • •Building production-ready AI applications with LangChain
  • •Implementing RAG pipelines for intelligent document retrieval
  • •Orchestrating multi-agent systems with LangGraph
  • •Optimizing prompts for GPT-4 and Claude 3.5
  • •Vector database integration with Pinecone & ChromaDB

Course Highlights

  • •Weekly hands-on projects with real-world applications
  • •Expert mentorship from industry professionals
  • •Collaborative learning with passionate developers
  • •Cutting-edge AI technologies and best practices
  • •Building a portfolio that showcases AI mastery

What I Enjoyed Most

  • •Creating the SQL-Ball contest entry with innovative features
  • •Solving complex problems with AI-driven solutions
  • •Learning from feedback and iterating on projects
  • •Exploring the boundaries of what's possible with AI
  • •Contributing to the AI community through open source

Contest Entry: SQL-Ball

Football data analytics with natural language queries, AI-powered insights, and interactive performance visualisations.