Learn AWS and AI/ML live, from an engineer with 17 years in production.
Small live batches of up to 20 people. Hands-on labs. A new batch starts every Monday. Join from India, the USA or anywhere.
- 17 years in Oracle, Linux & AWS
- 3,000+ engineers trained
- AWS Certified Solutions Architect – Associate
- Live classes, not recordings
Free: AWS Solutions Architect 30-day study plan · Need help on a project? Cloud & AI/ML consulting →
Pushpjeet Cholkar
I'm Pushpjeet Cholkar. For 17 years I've built, tuned and rescued Oracle, Linux and AWS systems for Deutsche Bank, IBM, Wipro, Accenture, Capgemini and Oracle University — across four continents. Now I train the engineers who run those systems, and consult on the AI layer going on top of them.
Three ways to work with me
The same engineering experience, delivered at three different sizes — a company, a team, or one person deciding to level up.
Consulting
For companiesSomeone senior who has already fixed this before. Performance tuning, migrations, cloud architecture, and getting AI/ML working against real production data.
- Oracle & SQL performance tuning
- Database migration and upgrade (8i → 26ai)
- AWS / OCI architecture review
- Data warehouse & ETL design
- RAG and LLM integration on enterprise data
Corporate training
For teamsCustom cohorts built around your stack, not a generic syllabus. Delivered on-site or live-virtual, the same way I've delivered for Oracle University and AWS reStart.
- Curriculum written to your systems
- Hands-on labs on your cloud accounts
- On-site, live-virtual, or blended
- Assessment and post-training support
- English delivery, global time zones
Open batches
For individualsSmall public cohorts for students and working professionals. Some paid, some free. Live sessions, real labs, and a certificate you actually earned.
- Weekend and evening batches
- Live, not pre-recorded
- Lab environment provided
- Free labs and material for everyone
Newsletter
New batch dates and free tutorials, by email
New AWS batches, AI/ML tutorials, Oracle tips and blog posts. No spam, unsubscribe anytime.
Three thousand engineers, one room at a time
Corporate floors in Pune and Bangalore, university labs, bootcamp cohorts in Germany and the UK, and Live Virtual Classes for Oracle University reaching people I never met in person. Same approach every time: short explanation, then hands on the keyboard.
Labs, projects and material — no charge
Teaching has always been the part I enjoy most, so a lot of it is simply open. Build the lab, break it, ask me questions.
Oracle 23ai on Docker
LabStand up a multitenant container database on your laptop, create PDBs, and practise DBA work without touching a licence server.
AWS VPC from scratch
LabBuild a three-tier VPC by hand — subnets, route tables, NAT, security groups — then tear it down. The lab that makes the SAA exam click.
Build a RAG tutor
ProjectA retrieval-augmented tutor over your own PDFs, end to end: chunking, embeddings, vector store, evaluation. My live research area.
Tell me what you're trying to do.
A slow database, a cloud migration nobody wants to own, a team that needs to be trained properly, or a batch you'd like to join. WhatsApp is fastest — I usually reply the same day.
WhatsApp +91 70492 35525 Email pc@pushpjeet.com pushpjeet@gmail.com LinkedIn /in/pushpjeet-cholkar Instagram @coachpushpjeet Office 8/5 Manas Mayfair, 4th Floor South Tukoganj, Indore 452001 Entities PITC Solutions LLC (USA) Pushpjeet IT Consultant (India)
Live batches, not recorded courses
Every batch is taught live by me. You get the labs and the ability to interrupt and ask why. Batch sizes stay small enough that I know who is stuck.
AWS S3 in Detail — From Zero to Pro
Every MondayOne service, all the way down. Buckets and objects, storage classes and lifecycle rules, versioning, encryption, bucket policies versus IAM, replication, static hosting, event notifications, and the cost traps that surprise people on their first bill.
- Starts
- Every Monday
- Level
- Zero → Pro
- Group size
- Up to 20 participants
- Mode
- Live virtual
- Fee
- On request
Oracle SQL & PL/SQL
RegisteringFrom SELECT to packages, cursors, collections and exception design. The foundation everything else in the Oracle world stands on.
- Level
- Beginner → Intermediate
- Length
- 40 hours · 6 weekends
- Mode
- Live virtual
- Release
- 19c · 23ai · 26ai
- Fee
- On request
Oracle DBA 23ai
RegisteringMultitenant architecture, backup and recovery with RMAN, performance tuning, high availability and replication. Taught the way it's actually run.
- Level
- Intermediate → Advanced
- Length
- 50 hours · 8 weekends
- Mode
- Live virtual
- Lab
- Container DB provided
- Fee
- On request
AWS Solutions Architect
RegisteringThe SAA-C03 blueprint taught through labs, not slides. VPC, IAM, S3, EC2, RDS, ELB, CloudFront, well-architected trade-offs. Built from three AWS reStart cohorts.
- Level
- Beginner → Associate
- Length
- 40 hours · 6 weeks
- Mode
- Live virtual
- Outcome
- SAA-C03 ready
- Fee
- $100
Linux Fundamentals
RegisteringThe Linux a DBA or cloud engineer actually uses: filesystem, permissions, processes, networking, shell scripting, log hunting.
- Level
- Beginner
- Length
- 15 hours · 5 modules
- Mode
- Live virtual
- Fee
- On request
SQL Performance Tuning
Dates soonReading execution plans, indexing strategy, statistics, hints, and the twelve query shapes that cause most production slowness. Bring your own slow query.
- Level
- Advanced
- Length
- 20 hours · masterclass
- Mode
- Live virtual
- Fee
- On request
RAG & LLM Applications
Dates soonBuild a working retrieval-augmented application over real documents: chunking, embeddings, vector stores, prompt design, evaluation, and what breaks in production.
- Level
- Intermediate
- Length
- 30 hours · 5 weeks
- Mode
- Live virtual
- Needs
- Python basics
- Fee
- On request
Python for Data & ML
Dates soonPython, pandas, scikit-learn and the modelling workflow, aimed at people who already understand data but haven't written the code side yet.
- Level
- Beginner → Intermediate
- Length
- 35 hours · 6 weeks
- Mode
- Live virtual
- Fee
- On request
Snowflake & Power BI
Dates soonModern warehousing end to end — loading, modelling, warehouse sizing and cost, then the semantic layer and reporting on top in Power BI.
- Level
- Intermediate
- Length
- 25 hours · 4 weeks
- Mode
- Live virtual
- Fee
- On request
Terraform on AWS
Dates soonInfrastructure as code from first principles — providers, state, modules, plan and apply discipline. The curriculum I deliver for neue fische × SPICED.
- Level
- Intermediate
- Length
- 20 hours · 4 weeks
- Mode
- Live virtual
- Fee
- On request
What a session actually looks like
University labs, corporate floors, and my own training room in Indore. Small explanation, then hands on the keyboard — which is why these photographs are mostly of people working rather than of me talking.
Corporate training
Most of my seventeen years has been spent training engineering teams inside large companies. The syllabus gets written after I understand your stack, not before.
How a corporate engagement runs
- Scoping call — your stack, your team's current level, the business reason for the training.
- Custom curriculum — written to your systems, reviewed by you before delivery.
- Delivery — on-site, live-virtual, or blended, in your time zone.
- Anyone in the USA — can take AWS, AI/ML, Linux, Oracle SQL and Terraform live online, scheduled in your US time zone.
- Hands-on labs — on your cloud accounts or an environment I provide.
- Assessment — pre and post measurement so you can see the movement.
- Follow-up — a support window after delivery for real questions from real work.
Formats I deliver in
- On-site
- Classroom at your office, India and international
- LVC
- Live Virtual Class — the format I ran for Oracle University Singapore, worldwide
- Bootcamp
- Multi-week intensive, the AWS reStart model (3 months, 14+ cohorts run)
- Short burst
- 1–3 day masterclass on a single topic
- Academic
- Semester modules for universities — currently Parul and ITM
- Video
- Recorded modules for an internal learning library
Learn in a simple way, do it practically.
Labs you can run tonight, projects worth putting on a CV, and reference material I wish someone had handed me in 2009. No payment, no course upsell.
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Generative AI Tutorials and Guides
NewFree generative AI material on this site: the new RAG vs fine-tuning decision guide, the RAG tutorial in Python with its student lab, AI agents, GANs and VAEs, and the foundations to start from.
- Format
- A hub page that lists every generative AI guide, tutorial and training page on this site
- Start here
- RAG vs fine-tuning: when to retrieve company documents and when to change model weights, with a decision guide and hybrid patterns
- Also here
- Build a RAG app in Python with Amazon Bedrock, the RAG student lab and quiz, AI agents, and GANs and VAEs
AWS Tutorials and Guides
NewFree AWS material on this site: the S3 vs EBS vs EFS storage guide, AWS in the AI/ML tutorials (Amazon Bedrock, SageMaker AI), Linux and Bash for labs, and a free SAA study plan.
- Format
- A hub page that lists every AWS guide, tutorial and training page on this site
- Start here
- S3 vs EBS vs EFS: object, block and file storage compared, with current limits and AWS CLI steps
- Also here
- Amazon Bedrock in the RAG tutorial, SageMaker AI in the ML Solutions Quest, and the free SAA 30-day study plan
Bash Scripting: Zero to Pro
NewLearn Bash scripting from zero to pro: 45 modules and 162 tested scripts with real output, exercises, strict mode, trap, getopts, cron and a capstone tool.
- Format
- 45 modules in five levels plus a server-health capstone; every example shows the script, the command and its real output
- Practice
- 25 exercises with worked solutions, a 25-question quiz and all 162 scripts in one zip
- Covers
- Variables, quoting,
if/case, loops, functions, arrays, strict mode,trap,getopts, logging, ShellCheck,cron
Mathematics for Machine Learning: The Essentials
NewLearn mathematics for machine learning: vectors, matrices, gradients and gradient descent, with NumPy labs. Bridge from Python coding into ML maths.
- Format
- Written tutorial with worked examples and a hands-on NumPy lab (45–60 minutes)
- Practice
- 10 MCQs, practice exercises, interview questions and a student cheat sheet
- Covers
- Vectors, matrices, norms, derivatives, gradients, gradient descent
Linear Regression for Beginners
FreeLearn linear regression for beginners: fit y=mx+b with least squares, read R² and RMSE, work two verified examples, then run a free local Python lab.
- Format
- Written tutorial with two worked examples and a free local Python lab
- Practice
- A 10-question interactive quiz, practice exercises and a student cheat sheet
- Covers
y = mx + b, least squares, R², RMSE
Multiple Linear Regression in Python (Expert)
FreeMultiple linear regression in Python at expert depth: OLS normal equations, a worked example, VIF and Cook’s diagnostics, Ridge vs Lasso, and three labs.
- Format
- Expert written tutorial with a worked example by hand and full runnable code
- Practice
- 3 Python labs, a 10-question expert quiz and a cheat sheet with 15 flashcards
- Covers
- OLS in matrix form, adjusted R², VIF, Cook’s distance, Breusch–Pagan, Ridge, Lasso, Elastic Net
RAG Tutorial in Python: build a RAG app step by step
FreeBuild a RAG app in Python step by step: chunking, embeddings, cosine similarity search, prompts, Amazon Bedrock generation and retrieval evaluation.
- Format
- Hands-on tutorial in Python and NumPy, built from scratch; no API key needed for retrieval
- Practice
- A lab to extend the assistant and catch a regression, 10 MCQs and practice exercises
- Covers
- Chunking, embeddings, cosine similarity, prompts, Amazon Bedrock, hit rate@k and recall@k
AI & Machine Learning Fundamentals
FreeFrom “What is AI?” to foundation models, RAG and the AWS AI services — no background in coding or maths needed. Six modules that build on each other: AI vs ML vs DL vs GenAI, ML fundamentals, deep learning, generative AI, and Amazon Bedrock vs SageMaker AI.
- Interactive
- Reveal-the-answer questions, a scored quiz, flashcards and a searchable glossary
- PDF guide
- 62 pages · 88 questions answered from basic to advanced · 30 quiz questions · 32 practice challenges
- Time
- About 4 hours, self-paced
GANs, VAEs and Latent Space
VideoHow machines learn to create new images. What latent space is, how a Variational Autoencoder builds a smooth one, how a GAN's generator and discriminator compete, and where both show up inside today's image generators.
- Format
- Video lesson plus written tutorial with diagrams
- Practice
- 8 self-check questions and a hands-on VAE challenge on MNIST
- Time
- About 25 minutes to read, plus the video
AI & ML Quest: how does a machine learn?
InteractiveA gamified warm-up for the AI & ML Fundamentals tutorial. Eight short levels with mini-games, from the AI family and how models learn to generative AI, RAG and the AWS toolbox. Earn XP and badges as you go.
- Format
- 8 levels with mini-games, checkpoints, a mind map, flashcards and a boss battle
- Practice
- Train a model, build a neuron, be an LLM, estimate an LLM bill
- Time
- About 70 minutes, self-paced
Rise of the AI Agents: from talking to doing
InteractiveWhat an AI agent is and how it works: the brain, tools, memory and planning. Watch an agent run its think–act–observe loop, learn when a human must approve, and meet Amazon Bedrock Agents, AgentCore and MCP.
- Format
- Bonus level with an agent-loop simulator, flip cards and two games
- Practice
- Pick the right tool, play safety officer, clear the checkpoint
- Time
- About 12 minutes
ML Solutions Quest: from idea to a working model
InteractiveA gamified warm-up on developing machine learning solutions. Take one model through its whole life, the way Amazon did for its call centre: business goal, data, training, evaluation, deployment and MLOps with Amazon SageMaker AI. Earn XP and badges as you go.
- Format
- 8 levels with mini-games, checkpoints, a mind map, flashcards, myth or fact and a boss battle
- Practice
- Order the ML lifecycle, split your data, diagnose a model, choose the metric, pick the deployment option
- Time
- About 70 minutes, self-paced
The Goldilocks Problem: the bias-variance trade-off
VideoHow does an AI know when to stop learning? A short video on underfitting, overfitting and finding the balance, with a scene-by-scene walkthrough that tests each model on brand-new data.
- Format
- 74-second video plus an interactive scene-by-scene walkthrough
- Practice
- Model doctor and prescribe-the-cure games, plus a checkpoint
- Time
- About 10 minutes
Linux from Scratch: a practical command-line course
FreeLearn Linux from scratch: terminal, files, vim, bash, permissions, processes, scripting, packages (apt & dnf), users, and networking.
- Format
- Hands-on course in 19 modules, from orientation to networking basics
- Practice
- Exercises in every module (MCQs, flashcards, fill-in-the-blank and more), an M3 interactive quiz and a student command cheat sheet
- Next step
- Bash Scripting: Zero to Pro after M14
Linux File Permissions Quest
InteractiveFrom “what is rwx?” to setuid, sticky bits and umask. Read the levels, play the mini-games, hack the practice terminal, earn XP and badges, and finish as a Permissions Root.
- Format
- 16 levels with mini-games, a sandbox terminal with missions, an Octal Dojo and an FAQ
- Practice
- 6 hands-on labs, a 20-question MCQ challenge and practice questions with model answers
- Covers
- rwx, owner/group/other,
ls -l,chmod,chown,chgrp,sudo, special bits,umask
Linux Process Management Lab
InteractiveProcesses, ps, pstree, top, kill, nice, jobs, at and cron. Pick a path, and every topic shows just that level — switch level on any topic whenever you want to go simpler or deeper.
- Format
- Beginner, intermediate and expert paths across 7 topics, with a simulated process-lab terminal
- Practice
- 8 hands-on labs, 30 MCQs (10 per level), FAQ and practice questions with model answers
- Covers
- PIDs, process states, signals,
nice/renice, job control,at,cron
Oracle 23ai multitenant sandbox
LabDocker Compose to a running CDB, then create, clone, unplug and plug PDBs. Includes the teardown script so you can start clean.
AWS VPC from scratch
LabA three-tier VPC built by hand in the console: public and private subnets, route tables, internet and NAT gateways, security groups, bastion access.
Terraform: build and destroy
LabThe same VPC, this time as code. Providers, variables, modules, remote state, and the discipline of reading a plan before you apply it.
Linux for DBAs: 40 drills
LabForty small command-line exercises with answers — permissions, processes, disk, logs, networking, and the shell one-liners you'll use weekly.
Build a RAG tutor
ProjectA retrieval-augmented tutoring assistant over your own PDFs: chunking strategy, embeddings, vector store, retrieval evaluation, and honest failure analysis.
Superset on Parquet
ProjectContainerised analytics stack: a historical Parquet dataset loaded and visualised in Apache Superset via Docker. A genuine portfolio piece.
Twelve slow queries
LabTwelve deliberately bad queries with their execution plans. Fix each one, then compare with my fix and the reasoning behind it.
ETL pipeline starter
ProjectExtract from a source database, transform with Python, load to a warehouse — with logging, idempotency and restartability built in from the start.
Database health-check pack
ScriptsThe SQL scripts I actually run on day one of a tuning engagement: tablespace pressure, top waits, missing indexes, stale statistics, session activity.
Downloads
Cheat sheets and handbooks, free. Ask for any of them and I'll send the file — that way I also know what people actually need more of.
The blog
Longer written walkthroughs across data engineering, AI, machine learning, databases and Linux — published on the main site.
Data engineering
Pipelines, ETL design, warehousing, and the operational side nobody writes about.
Databases
Oracle, PostgreSQL, MongoDB, Snowflake — modelling, tuning and migration.
Cloud
AWS and Oracle Cloud architecture, Terraform, cost, and well-architected trade-offs.
AI & machine learning
LLMs, agents, RAG systems, and getting models to run against enterprise data.
Linux
Commands, scripting and the administration a database or cloud engineer needs.
Career
Certification paths, interview preparation, and moving from support into engineering.
Senior help, without the headcount
Companies usually call me for one of four reasons: something is slow, something has to move, something needs designing properly, or someone wants AI working against data they already have.
Something is slow
PerformanceDatabase and SQL performance tuning on Oracle, PostgreSQL, MS SQL and Snowflake. Execution plans, indexing, statistics, contention, storage. I've done this for a national ERP in Cape Verde and for banking systems in Pune.
- Health check and prioritised findings, usually within a week
- Query-level tuning with before/after measurement
- Instance and storage-level configuration review
- Knowledge transfer so the fix doesn't leave with me
Something has to move
MigrationVersion upgrades across Oracle 8i through 26ai, cross-platform migrations (Oracle ↔ MySQL, PostgreSQL), and lift-and-shift or re-architecture onto AWS and Oracle Cloud Infrastructure.
- Assessment, risk register and rollback plan before anything moves
- Multitenant conversion and PDB strategy
- Cutover rehearsal and go-live support
- Post-migration tuning, which is where most projects go wrong
Something needs designing
ArchitectureData warehouse and ETL design, high availability and replication, backup and recovery strategy, and AWS architecture reviewed against the well-architected framework.
- Warehouse and dimensional modelling
- ETL pipeline design with restartability built in
- HA, replication, RMAN backup and tested recovery
- VPC, IAM and cost architecture on AWS / OCI
AI on your own data
AI / MLThe layer everyone is being asked to add this year. Retrieval-augmented generation over internal documents, ML models against operational data, and a realistic assessment of what will and won't work.
- RAG systems over enterprise documents
- Machine learning on operational and warehouse data
- Evaluation — how you'll know it's actually working
- An honest opinion on whether AI is the right answer at all
Engagement models
Contracting
Two entities, so clients can contract on whichever side suits them:
- USA
- PITC Solutions LLC
- India
- Pushpjeet IT Consultant, Indore
- Remote
- Worldwide, any time zone
- On-site
- India and international, by arrangement
Start with a conversation
Tell me the symptom, not the solution. A twenty-minute call is usually enough for me to say whether I'm the right person, and what I'd do first. No charge for that.
Seventeen years, mostly at the data layer
I started as an Oracle developer and DBA in 2009, and spent the first decade doing the unglamorous work — tuning queries that had been slow for years, recovering databases at two in the morning, migrating systems that nobody had documented.
Somewhere in there I discovered I was better at explaining it than most people were, and training took over. I've since delivered for Oracle University, AWS reStart, and engineering teams at IBM, Wipro, Accenture, Capgemini and Deutsche Bank, in India and across a dozen other countries, including three teams in the USA as a freelance trainer.
Today the work splits three ways: consulting on databases and cloud, training engineers and university students, and research into how AI can actually be used to teach — which is where I intend to spend the next stage of my career.
Certifications
- AWS Certified Solutions Architect — Associate
- Oracle Cloud Infrastructure Foundations 2020 — Associate
- Oracle Certified Professional — Database 11g Administrator
- Oracle Certified Professional — Advanced PL/SQL
- Oracle Certified Professional — Developer Track (9i, 10g, 11g)
Education
- 2009
- B.E. Computer Science & Engineering, RGPV Bhopal
- 2026
- M.E. Computer Science & Engineering, RGPV Bhopal
- 2026
- M.Sc. Mathematics, Manipal University (in progress)
- 2028
- Ph.D. — target intake
Where I've worked
Seventeen years only counts if the last year is in it
The stack I teach keeps moving, so I keep showing up where it moves — cloud-native conferences, new Oracle releases the month they land, and the AI tooling that is rewriting how all of this gets built. What I teach on Monday is what I was reading about on Sunday.
What I'm working on academically
I'm working towards a Ph.D. with a target intake of Fall 2028. The research question I keep returning to is whether a language model can genuinely teach — and how you'd measure it if it could.
Primary interests
- RAG-based tutoring systems — retrieval-augmented models as subject tutors, and where the retrieval layer fails students
- Learning analytics — measuring what a learner has actually understood, not what they clicked
- Evaluation of AI tutors — designing benchmarks that reflect learning outcomes rather than answer similarity
- Query optimisation — carried over from seventeen years of tuning work
Teaching & supervision interests
- Database systems — Oracle, SQL, PL/SQL, PostgreSQL, MongoDB
- Data structures and algorithms
- Operating systems — Unix and Linux
- Cloud computing — AWS and Oracle Cloud
- Data warehousing and business intelligence
- Artificial intelligence and machine learning
- Software engineering and project management
Let's talk
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opp. Nath Mandir Road, South Tukoganj,
Indore, Madhya Pradesh 452001
Pushpjeet IT Consultant — India
Response time
WhatsApp is fastest — usually the same day. Email within two working days. For consulting enquiries, say what system and what symptom and I can be useful in the first reply.