Who teaches

Practitioners, not presenters

Every programme is taught by someone who has done the work. Each batch names its own trainer before you enrol, so you know who will be in the room.

Trainers

Who leads the teaching

Vishal Shah

Founder & Principal Trainer

20+ years' experience

Two decades building and teaching commerce, banking and cloud platforms, and still writing code

Vishal has spent more than twenty years across engineering and technical enablement, working on commerce, banking and cloud platforms and teaching the architects and developers who build on them. He is currently a technical trainer and functional architect at commercetools. He teaches the production concerns most courses skip, because he has spent two decades being paged about them.

Java & Spring Boot microservices
TypeScript, React, Angular & Next.js
Composable commerce (commercetools)
Digital banking (Backbase)
Event-driven & cloud-native architecture
AWS, Google Cloud & Azure
CI/CD: Jenkins & GitHub Actions
SDET: Playwright, Selenium, RestAssured, contract testing
AI agents, MCP & LLM application engineering
Technical curriculum architecture

Where that experience comes from

commercetools · technical trainer & functional architect
Backbase · principal bootcamp trainer (contract)
Toptal · technical training programme manager (contract)
Capgemini · senior technical trainer
Training delivered for Cognizant, IBM, Saudi Aramco and Persistent Systems

Certifications

commercetools Certified Functional Architect
Oracle Certified Java Programmer, SE7
AWS Certified Solutions Architect (2020–2023)
AWS Certified Developer (2020–2023)
AWS Certified DevOps Engineer, Professional (2020–2023)
Google Cloud Associate Cloud Engineer (2020–2023)
Google Professional Cloud Architect (2020–2023)

Full profile

Vishal began teaching in Sangli. Between 2009 and 2013 he was a technical trainer at Deesha Computer Education, after four years running the IT department at Gulabrao Patil Institute of Information Technology in Miraj. Deesha Tech Academy is that work picked up again, with eighteen more years of industry behind it.

In between he built the enablement side of several platform businesses. He is a technical trainer and functional architect at commercetools, where he architected the 2026 commercetools course family across the Functional Architect and Developer tracks: six courses covering B2C, B2B and Agentic Commerce, built as a modular, decision-driven curriculum with reusable session plans, hands-on labs and runnable starter code. He built hexagonal Backend-for-Frontend starter projects in Java/Spring Boot and TypeScript/NestJS, and a capability-gated storefront where each endpoint a learner implements unlocks a real storefront feature: a lab that validates itself.

Before that he was principal bootcamp trainer at Backbase, technical training programme manager at Toptal, and a senior technical trainer at Capgemini. As a freelance consultant he delivered training for Cognizant, IBM, Saudi Aramco and Persistent Systems.

More recently he has worked on AI-native enablement: curricula and hands-on environments built on Claude Code, the Model Context Protocol and agentic development workflows, teaching developers to build with AI tooling accountably rather than by copy-paste. The two-tier task loop he designed there (AI accelerates the plumbing, the participant owns the design decisions and the hardening) is the same principle behind how Deesha courses are built.

Shrenik Shah

Principal Trainer

10+ years' experience

Cloud and AI architect who has upskilled over 5,000 engineers in Java, React, Python and cloud

Shrenik is a principal cloud and AI architect with more than ten years of enterprise experience, currently a technical consultant and architect at Capgemini, where he has upskilled and certified over 5,000 engineers. He taught at Deesha in Sangli for six years before that, and has come back to it, which means he has taught this syllabus to beginners and then watched what it has to survive in an enterprise delivery team.

Python: Django, Flask, GenAI & agentic workflows
Java & Spring Boot
React & Angular, micro-frontend architecture
Node.js & Express
AWS & Azure, including Bedrock, SageMaker and Azure OpenAI
LLM orchestration, RAG & autonomous agents
API-first design, REST & GraphQL
MongoDB, MySQL & SQL Server
CI/CD with GitHub Actions
Technical enablement & curriculum design

Where that experience comes from

Capgemini · technical consultant & architect, enterprise enablement
JoulestoWatts Business Solutions · senior consultant, delivering for Capgemini
Deesha Computer Education, Sangli · technical trainer & centre coordinator, 2015–2021

Certifications

AWS Certified Cloud Practitioner (CLF-C01)
Microsoft Technology Associate, Java (98-388)
Microsoft Technology Associate, Python (98-381)

Full profile

Shrenik is from Sangli. He read for a Bachelor of Computer Science at K. Walchand College and spent six years, from 2015 to 2021, as technical trainer and centre coordinator at Deesha Computer Education, teaching Java, React, Python and full-stack development to students and working professionals, designing the curriculum, and running corporate and academic workshops including Python with Raspberry Pi and advanced Java.

He then moved into enterprise consulting. As a senior consultant at JoulestoWatts he designed and ran technical enablement programmes for Capgemini's development teams, and since 2022 he has been a technical consultant and architect at Capgemini itself, where he has upskilled and certified more than 5,000 engineers across Java and Spring Boot, React, Angular, Python, generative and agentic AI, AWS and Azure.

His architecture work covers micro-frontends (breaking legacy monoliths into independently deployable applications with React Module Federation and Angular Single-SPA) and Python-driven generative AI and autonomous agent systems on multi-cloud pipelines, using AWS Bedrock and SageMaker alongside Azure OpenAI and Cognitive Search. He has delivered more than forty corporate workshops and over a thousand hours of hands-on sessions.

That combination is the reason he teaches well: he has taught these fundamentals to complete beginners, and he has seen exactly which of them hold up when a delivery team is under pressure.

Satish Mahajan

Expert Trainer (Java, Testing & Automation)

17+ years' experience

Seventeen years training enterprise engineering teams in Java, Python and test automation

Satish is a technical learning and development consultant with more than seventeen years designing and delivering technical training for enterprise engineering teams, across Java and Python full-stack, cloud, DevOps and test automation. He has owned engagements end to end (needs assessment, curriculum design, capstone build and competency frameworks) for audiences from graduate hires to experienced associates.

Core & advanced Java, Spring Boot
Test automation: Selenium, Playwright, Cucumber
JUnit 5, TestNG, Mockito, Rest Assured, Karate
Python for testing: PyTest, Requests
Cloud & DevOps: AWS, Docker, Kubernetes, Jenkins, CI/CD
Curriculum architecture & competency frameworks
GenAI and LLM tooling for engineering teams

Where that experience comes from

Maveric Systems · competency development and technical training
Capgemini · technical training management and learning frameworks
Zensar Technologies · core and advanced Java training delivery
Seed InfoTech · senior Java subject-matter expert
Training delivered for HSBC, Barclays, Wells Fargo, RBS, ABN AMRO and Societe Generale account teams

Certifications

Pega Certified System Architect (PCSA)

Full profile

Satish has spent his career on the training side of enterprise engineering, most recently as Senior Training Manager for competency development at Maveric Systems, and before that as a technical training manager at Capgemini and Zensar Technologies.

He has delivered Java full-stack and test-automation programmes for global graduate intakes across Singapore, Malaysia, the UK and the US, and cross-skilling and interview-readiness training for associates on banking accounts including HSBC, Barclays, Wells Fargo, RBS, ABN AMRO and Societe Generale. He has designed continuous learning frameworks and competency pathways, mentored other trainers on facilitation quality, and built capstone and enterprise-simulation projects used across delivery batches.

More recently he has been upskilling digital, DevOps and test-automation teams on generative AI and LLM tooling: prompt engineering, RAG, tool calling, MCP servers, LangChain and LangGraph, and Spring AI.

At Deesha he leads testing and automation teaching, and shares the Java and Python programmes.

Anant Khutale

Expert Trainer (Data Analytics & Business Intelligence)

15+ years' experience

Fifteen years in enterprise systems and reporting, teaching Excel, SQL, Python, Power BI and Tableau

Anant is an IT solutions and business process analyst with more than fifteen years across enterprise systems, order-to-cash operations and reporting, currently a system analyst at Hinduja Global Solutions. He works the whole distance from the messy source data to the dashboard a manager acts on, which is the distance most analytics teaching skips.

Excel: advanced formulas, VBA & macros
Power BI: data models & dashboards
Tableau: visual analytics
SQL & MySQL for reporting
Python: Pandas, NumPy, scikit-learn
Machine learning & data science foundations
Business analysis: requirement gathering, process mapping, gap analysis
Salesforce CRM data integrity & analytics
SAP SD, MM and FICO process support
Agile delivery, UAT & stakeholder collaboration

Where that experience comes from

Hinduja Global Solutions · system analyst, SAP order-to-cash process support
Avaya India · senior serviceability engineer, Salesforce and SAP data, Power BI reporting
Maersk Global Service Centre · finance officer, SAP FICO workflows and reporting

Certifications

Data Science Using Python
Python Programming
MySQL (SQL)
Power BI
AWS Certified Solutions Architect – Associate
Cognigy AI Developer
Agile Foundations
General Management Programme for Executives, IIM Lucknow

Full profile

Anant has spent his career where business processes meet the systems that run them. He is a system analyst at Hinduja Global Solutions in Mumbai, supporting SAP SD and MM order-to-cash processes: handling incidents, doing root-cause analysis with cross-functional teams, and writing the functional documents and SOPs that keep support consistent.

Before that he spent nearly sixteen years at Avaya India in Pune as a senior serviceability engineer, managing Salesforce and SAP-integrated data processes, building Power BI dashboards, and automating reporting work that had been manual. He began at Maersk Global Service Centre in Pune, analysing SAP FICO finance workflows and improving reporting accuracy.

Training has been part of the job throughout, not an addition to it: he has delivered CRM, data-quality and system best-practice training to drive user adoption at Avaya, and trained new hires at Maersk on SAP modules and standardised procedures.

He read for a Master of Commerce in Advanced Accountancy at Shivaji University and completed the General Management Programme for Executives at IIM Lucknow in 2019, alongside certifications in data science with Python, SQL, Power BI and AWS architecture.

At Deesha he leads data analytics and business intelligence teaching (Excel, SQL, Python, Power BI and Tableau) and shares the Python programme.

Mentors

Who supports learners alongside

Mentors work with learners on projects and direction rather than leading sessions, closer to where a learner is now.

Khushi Shah

Mentor (AI & Machine Learning)

AI and Data Science engineer, mentoring learners through their first ML projects

Khushi is a final-year Artificial Intelligence and Data Science engineering student who mentors Deesha learners through their first machine learning and computer vision work. She has built a gesture-controlled interface with OpenCV and a full-stack service aggregator, so she mentors from recent experience of the problems learners are hitting now.

Python for machine learning
NumPy, pandas, scikit-learn
TensorFlow & PyTorch
Computer vision with OpenCV
Data visualisation: Matplotlib, Seaborn, Power BI
SQL & MySQL

Certifications

Generative AI for Everyday Life (NPTEL)
Advanced Power BI (Rubbicon)
Cybersecurity job simulation, Deloitte (Forage)

Full profile

Khushi is completing a B.E. in Artificial Intelligence & Data Science at Zeal College of Engineering and Research. Her project work covers computer vision (a gesture-controlled virtual mouse built with Python and OpenCV, using real-time hand landmark detection) and full-stack web development, including a multi-vendor service aggregator with authentication, payments and an admin panel.

She served as Vice President of the SESA committee in her department and took part in the Smart India Hackathon.

At Deesha she mentors learners on the AI and machine learning path: framing a first problem, getting a model working end to end, and the gap between a notebook that runs and a project someone else can run.

Suhani Shah

Mentor (IIT Jodhpur)

IIT Jodhpur undergraduate researcher: approximation algorithms, RAG systems, GANs and computer vision

Suhani is a B.Tech student at IIT Jodhpur, ranked 4th in her department, and an undergraduate researcher in the Department of Computer Science, where she benchmarked four approximation algorithms for the NP-hard vertex cover problem across 588 runs. Her team placed 8th among 23 IITs at Inter-IIT Tech Meet 14.0, and she has architected and led a five-person team through a multi-stage computer vision pipeline.

Python, C & C++
PyTorch, NumPy, pandas, scikit-learn
Deep learning, GANs & transfer learning
Computer vision
NLP, RAG & LLM pipelines
LangGraph & agent orchestration
Vector search & embeddings
Data structures, graph & approximation algorithms
Model evaluation
PostgreSQL (pgvector), Docker, Git, Linux

Where that experience comes from

IIT Jodhpur, Dept. of Computer Science · undergraduate researcher, approximation algorithms

Full profile

Suhani is reading for a B.Tech in Chemical Engineering at the Indian Institute of Technology Jodhpur, ranked 4th in her department, alongside research and project work in computer science and machine learning.

As an undergraduate researcher in the Department of Computer Science, supervised by Prof. Tanmay Inamdar, she implemented and benchmarked four algorithms for the NP-hard vertex cover problem (GreedyMIS, LP rounding, NeighborCover and a parallelised variant) across 588 runs on Erdős–Rényi graphs of up to 5,000 vertices. Over 49 size-and-density configurations, GreedyMIS ran fastest in 94% of them while LP rounding produced the smallest covers. That distinction between the fast answer and the good one is exactly the judgment a learner needs and rarely gets taught.

For Inter-IIT Tech Meet 14.0 her team built a conversational analytics platform over 19,621 call-centre transcripts and more than 686,000 messages, orchestrating a 13-node LangGraph agent with query decomposition, multi-hop reasoning, and routing between text-to-SQL and hybrid retrieval combining BM25, dense search and reranking. It beat every RAG baseline on a 100-query benchmark: 8.85 out of 10 for relevancy against 4.63, and 9.21 for citation fidelity, human-validated at a Pearson correlation of 0.76. The team placed 8th among 23 IITs.

Her other work spans deep learning and classical computer science. She trained a VelocityGAN-style CNN encoder–decoder in PyTorch to reconstruct subsurface velocity maps from seismic waveforms, reaching SSIM 0.71 on a 6,000-sample holdout by balancing L1 against adversarial loss. She built a C++ autocomplete engine on a radix trie, BK-tree and min-heap that returns ranked suggestions in under 0.25 ms per keypress, and cut repeated-query latency twelvefold with a constant-time session cache. An earlier course project implemented Dijkstra's algorithm and k-means from scratch over a Haversine-distance graph.

She also architected the INSPECT vehicle damage assessment pipeline (ResNet-50 classification, YOLOv8 detection and Qwen2.5-VL reporting over a 15,000-image corpus) and directed a five-member team through model selection, evaluation and deployment-oriented design across all three stages. She is an active member of RAID, the AI society at IIT Jodhpur.

At Deesha she mentors learners on algorithms, machine learning and computer vision, close enough to the work they are attempting to remember exactly where it goes wrong.

Want to teach with us?

We are always glad to hear from practitioners who teach well.

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