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Soumya
- Rate $1
- Response 13h
-
Students2
Number of students Soumya has accompanied since arriving at Superprof
Number of students Soumya has accompanied since arriving at Superprof
$1/h
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- Computer programming
- HTML
- Computer 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
- Computer 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
- Elementary School
- Middle School
- High School
- +16
levels :
Elementary School
Middle School
High School
Première
Terminale
College
University
Adult Education
Masters/ Graduate School
Doctorate
Other
MBA
Early childhood education
Beginner
Intermediate
Advanced
Proficient
Autres
Children
- English
All 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
- $1
Pack rates
- 5 h: $5
- 10 h: $10
online
- $1/h
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