What I teach, I have 18 years experience working in companies like Intel, UST Global, TCS, etc
Student laptop environment setup and troubleshooting (Windows / macOS / Linux).
Why we write code: problem framing, requirements, and how software solves business problems.
How requirements arrive in real software companies and daily engineering workflows (tickets, standups, CI/CD).
Full C#, .NET Core from basics to advanced patterns.
SQL + database design, optimization and deployment.
HTML/CSS from basics to advanced with live web projects.
ASP.NET Core MVC (end-to-end) with live project builds and deployment.
JavaScript, TypeScript and modern frameworks (Angular and common ecosystems).
Software design: design patterns, clean architecture, dependency injection.
Security: ASP.NET Identity and secure authentication/authorization practices.
Production tooling: error logging with Serilog, observability and monitoring.
Integrations: payment gateway integration and secure transaction flows.
Cloud publishing: Web + API + SQL deployment to Azure (Docker/Containers, hosting, CI/CD).
Real-time project work to reinforce concepts and build portfolio artifacts.
=======================================================================================
Advanced & Production topics
------------------------------------------
Microservices and micro-frontend architectures.
Troubleshooting production with Splunk and other logging/observability tools.
Customer behavior analysis and “glass box” techniques for production insights.
Advanced production debugging strategies, routing, orchestration, parallelization.
=======================================================================================
Data Science & AI module
------------------------------------
Foundations: statistics, probability, EDA, preprocessing.
Machine learning essentials, feature engineering, model evaluation.
Deep learning for NLP (RNN/LSTM, embeddings) and custom BERT fine-tuning.
Transformer architecture, tokenization, LLM fundamentals, prompt engineering.
RAG systems design, vector stores, chunking, retrieval, evaluation.
LangChain & LangGraph for agentic workflows, multi-agent orchestration.
Deploy & optimize AI services (FastAPI, Docker, Azure), inference optimization, caching and monitoring.
Feel free to enquire more
Thanks and Regards,
Kasmeera C S
Subjects
-
SQL Expert
-
JavaScript Expert
-
Azure Expert
-
C# .NET Expert
-
ASP.NET Core Expert
Experience
No experience mentioned.
Education
-
B tech in Computer Science (Aug, 2008–May, 2011) from B tech
-
Govt Poly technic (Jul, 2005–Apr, 2008) from Govt Poly Technic Collage
Fee details
₹25–100/hour
(US$0.26–1.05/hour)
What I teach, I have 18 years experience working in companies like Intel, UST Global, TCS, etc
Student laptop environment setup and troubleshooting (Windows / macOS / Linux).
Why we write code: problem framing, requirements, and how software solves business problems.
How requirements arrive in real software companies and daily engineering workflows (tickets, standups, CI/CD).
Full C#, .NET Core from basics to advanced patterns.
SQL + database design, optimization and deployment.
HTML/CSS from basics to advanced with live web projects.
ASP.NET Core MVC (end-to-end) with live project builds and deployment.
JavaScript, TypeScript and modern frameworks (Angular and common ecosystems).
Software design: design patterns, clean architecture, dependency injection.
Security: ASP.NET Identity and secure authentication/authorization practices.
Production tooling: error logging with Serilog, observability and monitoring.
Integrations: payment gateway integration and secure transaction flows.
Cloud publishing: Web + API + SQL deployment to Azure (Docker/Containers, hosting, CI/CD).
Real-time project work to reinforce concepts and build portfolio artifacts.
=====================================================================================
Advanced & Production topics
-----------------------------------------
Microservices and micro-frontend architectures.
Troubleshooting production with Splunk and other logging/observability tools.
Customer behavior analysis and “glass box” techniques for production insights.
Advanced production debugging strategies, routing, orchestration, parallelization.
======================================================================================
Data Science & AI module
-----------------------------------
Foundations: statistics, probability, EDA, preprocessing.
Machine learning essentials, feature engineering, model evaluation.
Deep learning for NLP (RNN/LSTM, embeddings) and custom BERT fine-tuning.
Transformer architecture, tokenization, LLM fundamentals, prompt engineering.
RAG systems design, vector stores, chunking, retrieval, evaluation.
LangChain & LangGraph for agentic workflows, multi-agent orchestration.
Deploy & optimize AI services (FastAPI, Docker, Azure), inference optimization, caching and monitoring.