Ishangoai/AIMS_course
Oct 2025 – Oct 2025
1 Month active
Languages Used
PythonShell
Technical Skills
API DevelopmentCI/CDDagsterData EngineeringData ValidationDocker
Rojoniaina-Rasoafarihy
PROFILE
Rojoniaina-rasoafarihy
Developed the Student AI/ML Platform Scaffold for the Ishangoai/AIMS_course repository, delivering a modular workflow platform to support student experimentation and learning in artificial intelligence and machine learning. The work integrated Python and Shell scripting with technologies such as FastAPI, Dagster, and MLflow to create an end-to-end system for data ingestion, processing, analytics, and model tracking. The platform features a Langchain and Gradio-powered chatbot for interactive support, a FastAPI application mounting Gradio apps, and a Dagster-based pipeline for data engineering tasks. The solution enables streamlined experimentation, model evaluation, and promotion, supporting educational outcomes in a reproducible environment.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,698
Activity Months1
Your Network
35 peopleWork History
October 2025
1 Commits • 1 Features
Oct 1, 2025October 2025: Delivered the Student AI/ML Platform Scaffold for Ishangoai/AIMS_course, establishing a modular end-to-end workflow platform that enables student-focused AI/ML experimentation and learning. The month focused on implementing a scaffold that unites data ingestion, processing, analytics, and model tracking, enabling faster experimentation and education outcomes. Key outcomes include a new folder structure, a Langchain/Gradio chatbot, a FastAPI application mounting Gradio apps, a Dagster-based data engineering pipeline (ingestion, cleaning, and aggregation), and an MLflow-integrated time-series forecasting pipeline with model tracking and promotion.
1 Commits • 1 Features
Oct 1, 2025October 2025: Delivered the Student AI/ML Platform Scaffold for Ishangoai/AIMS_course, establishing a modular end-to-end workflow platform that enables student-focused AI/ML experimentation and learning. The month focused on implementing a scaffold that unites data ingestion, processing, analytics, and model tracking, enabling faster experimentation and education outcomes. Key outcomes include a new folder structure, a Langchain/Gradio chatbot, a FastAPI application mounting Gradio apps, a Dagster-based data engineering pipeline (ingestion, cleaning, and aggregation), and an MLflow-integrated time-series forecasting pipeline with model tracking and promotion.
October 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance80.0%
AI Usage90.0%
Skills & Technologies
Programming Languages
PythonShell
Technical Skills
API DevelopmentCI/CDDagsterData EngineeringData ValidationDockerFastAPIGradioHyperoptLangchainMLflowMachine LearningModel DeploymentPandasScikit-learn
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