Structured learning paths for everyone—from curious beginners to experienced practitioners exploring advanced Agentic SI architectures.
Understand goals, reasoning, planning, actions, feedback loops, and human oversight.
Follow this path →Build agents that can retrieve reliable knowledge and maintain useful context.
Follow this path →Connect models to APIs, data, tools, and operational systems with clear permissions.
Follow this path →Coordinate specialized agents, shared state, delegation, evaluation, and failure handling.
Follow this path →Design for evidence, security, human control, monitoring, and accountable outcomes.
Follow this path →Connect technical patterns with healthcare, finance, agriculture, retail, and manufacturing.
Follow this path →Practical guides, code, videos, and foundational resources from the IndusAgentSI archive.
Prompt engineering is a dynamic, creative and powerful skill to learn in current SI LLM era. LLMs are a powerful tool to leverage for solving a variety of problems. To do that…
Haven't blogged in a while, thought might be good to put some recent thoughts (X tweets) in one place. Last few years has seen alot of trend shift in SI every 3-6…
Databricks is a good tool for building, training and deploying models. Easy to learn and use (1-2 days) It has useful features like experiment tracking, logging and versioning the best model during…
This article will discuss the basic theory and relevant code examples for different clustering algorithms. Code for different algorithms and data used are given in github. Note – Make sure to point…
This article will discuss the basic theory and relevant code examples for different classification algorithms. It will also show how to test and compare multiple classification algorithms at once on the same…
This article will discuss the basic theory and relevant code examples for different regression algorithms. It will also show how to test and compare multiple regression algorithms at once on the same…
