Soumya - Computer programming tutor - Elanjipra
Soumya - Computer programming tutor - Elanjipra

Soumya profile and its contact details have been verified by our experts

Soumya

  • Rate R26
  • Response 13h
  • Students

    Number of students Soumya has accompanied since joining Superprof

    2

    Number of students Soumya has accompanied since joining Superprof

Soumya - Computer programming tutor - Elanjipra

R26/h

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  • Computer Programming
  • HTML
  • Programming Languages
  • Artificial Intelligence
  • C#.NET

I teach students how to build production web apps (C#, .NET Core, Web API, SQL, HTML, JavaScript, Angular) and then apply data science, ML and transformer/LLM techniques to add intelligent features li

  • Computer Programming
  • HTML
  • Programming Languages
  • Artificial Intelligence
  • C#.NET

Lesson location

About Soumya

Practical, project-driven online instructor who bridges modern full-stack development with state-of-the-art NLP and LLM systems. I teach students how to build production web apps (C#, .NET Core, Web API, SQL, HTML, JavaScript, Angular) and then apply data science, ML and transformer/LLM techniques to add intelligent features like RAG, agents and conversational apps. What I teach (high level) Full-stack & Web: C#, .NET Core, Web API design, SQL database design & optimization, HTML/CSS, JavaScript, Angular frontends, deployment and CI/CD. Statistics & Data: Foundations of probability & statistics, exploratory data analysis, cleaning and preprocessing for ML. Machine Learning: Supervised/unsupervised methods, model evaluation, feature engineering, production-ready pipelines. Deep Learning & NLP: Neural networks for NLP, Transformer architecture deep dive, sequence modeling, fine-tuning. Large Language Models & Systems: Prompt engineering, retrieval-augmented generation (RAG) architectures, LangChain framework mastery, Agentic AI with LangGraph, advanced RAG patterns and production considerations. Teaching style & outcomes Hands-on: each concept is paired with code labs and mini-projects (API endpoints, Angular UI, ETL pipelines, fine-tuning small models, RAG demo). Real-world focus: from designing Web APIs and SQL schemas to deploying LLM-powered features (search + context + prompts) in a secure, scalable way. Progressive learning path: start with foundations (stats, SQL, C#) then move to ML essentials, Transformers, and finally RAG/agents & LangChain/LangGraph. Deliverables students can show: working web app with ML/NLP features, productionized RAG pipeline, and a portfolio-ready project.

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About the lesson

  • All levels
  • English

Languages in which the lesson is available :

English

Practical, project-driven online instructor who bridges modern full-stack development with state-of-the-art NLP and LLM systems. I teach students how to build production web apps (C#, .NET Core, Web API, SQL, HTML, JavaScript, Angular) and then apply data science, ML and transformer/LLM techniques to add intelligent features like RAG, agents and conversational apps.

What I teach (high level)

Full-stack & Web: C#, .NET Core, Web API design, SQL database design & optimization, HTML/CSS, JavaScript, Angular frontends, deployment and CI/CD.

Statistics & Data: Foundations of probability & statistics, exploratory data analysis, cleaning and preprocessing for ML.

Machine Learning: Supervised/unsupervised methods, model evaluation, feature engineering, production-ready pipelines.

Deep Learning & NLP: Neural networks for NLP, Transformer architecture deep dive, sequence modeling, fine-tuning.

Large Language Models & Systems: Prompt engineering, retrieval-augmented generation (RAG) architectures, LangChain framework mastery, Agentic AI with LangGraph, advanced RAG patterns and production considerations.

Teaching style & outcomes

Hands-on: each concept is paired with code labs and mini-projects (API endpoints, Angular UI, ETL pipelines, fine-tuning small models, RAG demo).

Real-world focus: from designing Web APIs and SQL schemas to deploying LLM-powered features (search + context + prompts) in a secure, scalable way.

Progressive learning path: start with foundations (stats, SQL, C#) then move to ML essentials, Transformers, and finally RAG/agents & LangChain/LangGraph.

Deliverables students can show: working web app with ML/NLP features, productionized RAG pipeline, and a portfolio-ready project.

See more

Rates

Rate

  • R26

Package rates

  • 5h: R130
  • 10h: R260

online

  • R26/h

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