Portfolio of Krishal Karna (Krishal), AI & Data Science Engineer.
Segmented 10,000+ customers using RFM analysis and KMeans clustering to identify key customer groups and improve targeted marketing decisions. Tech: Python, Pandas, Scikit-learn, Power BI
View Project DetailsBuilt and analyzed a retail analytics database with 1M+ records using advanced SQL, CTEs, window functions, joins, and statistical testing for business insights. Tech: SQL, Analytics, Statistics
View Project DetailsImplemented a Retrieval-Augmented Generation assistant with multilingual support using vector search and LLM-based responses. Tech: RAG, LLM, NLP, Vector Database
View Project DetailsCreated Power BI dashboards and business insight reports as part of a Tata virtual job simulation project. Tech: Power BI, Data Visualization
View Project DetailsApplied ML clustering to identify actionable customer groups for targeted strategies.
Delivered advanced SQL insights across large-scale transactional datasets.
Implemented vector search and LLM responses for multilingual information retrieval.
Optimized SQL workflows to accelerate reporting and decision-making.
Created KPI-driven dashboards for leadership visibility and performance tracking.
A step-by-step MySQL learning and analytics blog series published on Hashnode.
Read SQL Blog SeriesWorked with 1M+ row retail datasets for revenue, cohort, and basket insights.
Built segmentation-ready feature sets using RFM and behavioral signals.
Prepared order-level datasets for analytics, forecasting, and cohort analysis.
Curated and indexed documents to power multilingual retrieval pipelines.
Validated advanced SQL skills for analytics and database querying with real-world scenarios.
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Completed hands-on training in Python for data science, AI, and application development.
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Earned the IBM SkillsBuild Data Fundamentals credential for core data concepts and practices.
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This certification showcases proficiency in modern AI tools and frameworks, emphasizing innovative applications using generative AI technologies.
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Earned an industry-recognized credential by mastering essential AI concepts and tools, including machine learning and natural language processing.
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Demonstrated expertise in operating system concepts, including process management, memory allocation, and file systems.
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Gained expertise in graph algorithms and their applications through advanced projects and practical learning.
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Acquired comprehensive skills in AI fundamentals, aligning with Microsoft's industry standards.
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Demonstrated advanced proficiency in data science concepts, securing a prestigious IBM certificate.
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