The profile of Soumya and their contact details have been verified by our experts
Soumya
- Rate 18 GHS
- Response 13h
-
Students2
Number of students Soumya has accompanied since arriving at Superprof
Number of students Soumya has accompanied since arriving at Superprof
18 GHS/hr
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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
- Primary school
- Junior high school
- SHS 1
- +20
levels :
Primary school
Junior high school
SHS 1
SHS 2
SHS 3
BTS
University education
Adult Education
Facultate (Licență)
Master's degree
Higher national diploma
Doctor of philosophy
Other
GDL
Qualified Lawyer Transfer Scheme
MBA
Pre school
Beginner
Intermediate
Advanced
Professionel
Others
Child
- 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
- 18 GHS
Pack prices
- 5h: 90 GHS
- 10h: 180 GHS
online
- GHS18/h
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