Learn it in depth
Deep notes, hand-picked lectures and animated explainers for every concept. Nothing skimmed, nothing skipped.
Don't just use AI. Build it.
Go from your first line of Python to shipping production AI: LLM apps, RAG, agents and deployment. 13 modules. 12 portfolio projects. Every skill proven.
- 10,000+ learners taught since 2023
- 13 modules, zero to production
- 12 portfolio projects
- Every lab checks your code
Plan your pace
I am a
58weeks to finish all 13 modules at this pace
346 guided hours in total
346 guided hours in total
- M1AI & Computing Foundationsweek 2
- M2Python for AIweek 8
- M3Mathematics & Statistics for AIweek 13
- M4Data, SQL & Machine Learning in Practiceweek 18
Evenings and weekends. Start with Module 1's tools and use the labs on problems from your own job.
Write real code from day one
Hands-on labs in your browser, with instant feedback that tells you exactly what to fix.
Prove every skill
Every lab, exam and project builds your Industry Readiness Index: a skill-by-skill score employers can verify.
Companies are hiring AI engineers right now
These open roles ask for exactly what you'll master here.
Lynx AnalyticsAI Engineer (India), PunePulsoraAI Engineer, IndiaValGenesisSoftware Engineer, AI/ML, HyderabadPatternStaff AI Engineer, PuneZimperiumAI Software Engineer (DevOps), BangaloreEgenSenior AI Engineer, RemoteQuickHyreAI Associate / Data Scientist, IndiaInfoskaters TechnologiesAI Developer, India
ClearQuoteComputer Vision Engineer, IndiaInfoCeptsMachine Learning, IndiaPublicis SapientData Science Manager, IndiaWINITAI/ML Trainee, IndiaStirring MindsAI Software Engineer, IndiaTayana SolutionsAI Agent Engineer, IndiaCoforgeForward-deployed engineers (scaling to 100), IndianewsEPAM SystemsForward-deployed engineers (50 → 100), Indianews
Learn. Practise. Prove. Apply.
- 1
Learn
Master each concept through deep notes, lectures and quick video checks.
- 2
Practise
60+ practice questions and an auto-graded lab in every lesson.
- 3
Prove
Clear the timed exam, ship the project and grow your IRI score.
- 4
Apply
Walk into interviews with a portfolio, a verified score and well-drilled answers.
The program
Thirteen modules. One path from your first script to production AI.
13 modulesSelf-pacedOnline
The AI Engineering Program
From your first line of Python to production LLM apps, RAG, agents, evals and fine-tuning. Reverse-engineered from 2026 AI-engineer job descriptions.
13modules
346guided hours
12portfolio projects
6–14hours a week
PythonGitGitHubGoogle ColabJupyterpytestNumPypandasMatplotlib
What you'll master
13 modules. Each one ends with work you can show.
Module 1AI & Computing Foundations9 hours, 5 lessonsStarts hereModule 2Python for AI34 hours, 15 lessonsUnlocks after Module 1Module 3Mathematics & Statistics for AI33 hours, 15 lessonsUnlocks after Module 2Module 4Data, SQL & Machine Learning in Practice26 hours, 12 lessonsUnlocks after Module 3Module 5Deep Learning & Transformers from Scratch28 hours, 10 lessonsUnlocks after Module 4Module 6LLM Application Engineering30 hours, 12 lessonsUnlocks after Module 5Module 7AI-Native Engineering with Coding Agents22 hours, 9 lessonsUnlocks after Module 6Module 8RAG Engineering30 hours, 13 lessonsUnlocks after Module 7Module 9Evals, Guardrails & AI Security24 hours, 11 lessonsUnlocks after Module 8Module 10Agents & MCP32 hours, 13 lessonsUnlocks after Module 9Module 11Fine-Tuning, Open Models & Inference24 hours, 10 lessonsUnlocks after Module 10Module 12Production AI & LLMOps24 hours, 10 lessonsUnlocks after Module 11Module 13Capstone & Career Launch30 hours, 10 lessonsUnlocks after Module 12
Inside every lesson
A look at Lessons 2.5 and 3.8.
Notes, Lesson 3.8: gradient descent
Take a small step against the slope of the loss. The learning rate η sets the step size.
θnew = θ − η · ∂L/∂θ
θ = 2.0, η = 0.1, ∂L/∂θ = 4.0 gives θnew = 1.6
Code lab, checked in your browser
def step(theta, grad, lr=0.1):
return theta - lr * grad
print(step(2.0, 4.0)) # 1.6- step(2.0, 4.0) ≈ 1.6
- moves against the gradient
- loss falls for 50 steps
Lesson 2.5 exam
A fraud team's script sees about 5 million device IDs per day and must flag any device that shows up more than once. For each incoming ID it asks 'have I already seen this?'. Which container should hold the IDs already seen?
- AA list, because it keeps the IDs in arrival order
- BA set, because membership checks stay fast as it grows
- CA tuple, because device IDs must never be changed
- DA sorted list, re-sorted after every new ID arrives
Practice workbook, Lesson 2.5
62 items in 4 sections
- Warm-up14
- Core practice28
- Challenge11
- Interview drills9
Glossary search: "learn"
- FairlearnAn open-source Python library for assessing and improving fairness of machine learning models. I…
- Federated learningA training approach in which many devices or organisations each train a model on their own local…
- Machine unlearningTechniques for removing the influence of specific training data from a trained model without ret…
Your Industry Readiness Index
Every lab you pass, exam you clear and project you ship adds to one score that shows exactly what you can do. Try it.
IRI score
sample
Foundations and toolingM1, M7
PythonM2
Maths and statisticsM3
Data and machine learningM4
Deep learning and LLM appsM5, M6
RAG, evals and agentsM8–M10
Fine-tuning and productionM11–M13
Sample profile.
The demand is here. The talent isn't.
growth in AI/ML hiring in India, July 2026 vs July 2025
Source: Naukri JobSpeak, Jul 2026of Indian recruiters struggle to find qualified candidates
Source: LinkedIn, Jan 2026typical fresher pay for GenAI specialists in India
Source: Instahyre, Jun 2026of AI-engineer roles are production work, not research
Source: 889 job descriptions, AI Shipping Labs, Jan 2026Why Synaptova
| Aspect | Typical online course | Synaptova |
|---|---|---|
| Proof of skill | Watch-time certificate | Graded labs, exams and an IRI score |
| Evaluations and AI security | Rarely covered | A full module |
| Working with coding agents | Rarely covered | A full module |
| Projects | Follow-along | 12 deployed, on Indian data |
| Learning by doing | Mostly watching | Code in every single lesson |
| Kept current | Recorded once | Updated as the industry moves |
Questions people ask
Still curious? Talk to us.
Do I need a coding background?
No. Module 1 starts from zero and takes you step by step into real code. Give it 60–90 minutes a day.
How do the modules unlock?
In sequence. Complete a module and the next one opens, so every new skill builds on the last. You can read the full curriculum of every module before you enrol.
Will this get me a job?
Nobody can promise you a job, and anyone who does is selling you something. What you will have: the skills in today's AI-engineer job descriptions, 12 projects to show and a verified readiness score.
Why is it discounted right now?
We turn three this year. To celebrate three years of teaching AI, the complete program is at its anniversary price. After the offer ends, the price returns to ₹56,999.
What do I need to start?
A laptop and an internet connection. Labs run right in your browser, so there's nothing heavy to install.
Is it live or recorded?
Self-paced. Start any day, study at your own hours and revisit any lesson whenever you need to.
Your first lesson is on us.
AI vs ML vs DL vs GenAI: deep notes, a hands-on lab and a quiz. No card. No catch.