For Learners
Choose the right starting point. Then build the next proof.
This learner hub routes you to the right surface: first lesson, 20-lesson syllabus, engineering articles, glossary, career direction, or founder-led guidance when it would change the work.
- Audiences
- 3
- Resources
- 6
- Answers
- 8
Who this is built for
Three real audiences. One curriculum.
The 20-lesson curriculum is calibrated for three specific audiences. If you fit one of these, the route is simple: read the public syllabus, build the artifact, and add paid guidance only when it changes the result.
Students
College learners and graduates who want practical software foundations before chasing advanced AI terminology. Commerce, arts, humanities — all welcome. No PCM in class 11–12 required.
What you get
- A foundation in coding, terminal, Git, Docker, APIs
- A real shippable artefact per module — code, repo, deployment
- Honest framing of what AI can and cannot do, by an engineer
- A starting point that does not assume science background
Professionals
Working professionals — engineers, designers, product managers, marketers — who want to understand modern AI tools (Docker, APIs, databases, AI-assisted coding) at a working depth, not just a buzzword surface.
What you get
- Self-paced lessons that fit around your day job
- A glossary that keeps technical vocabulary readable
- A working vocabulary for AI tools, APIs, Docker, Git, and cloud deployment
- A career-paths page that names real outcomes honestly
Builders
Founders, makers, and anyone shipping a real product who learns best by building small systems and connecting them into real applications. Not just theory — actually deploy it on the open internet.
What you get
- Cloud deployment basics — Cloudflare, Docker, tunnels
- Full-stack patterns from frontend to API to database
- Milestone projects that connect lessons into working systems
- Career paths that explain honest next steps after lesson 20
Your learning map
Six pages that take you from curious to shipping.
Every learner-helping resource on the site, in the right order. Bookmark this page — return to it whenever you are not sure where to look next.
Start here — your first 30 minutes
Gentle entryCommon fears named, your first thirty minutes mapped, the rhythm of a serious learner, what to do when stuck. The gentle path in, before you open lesson 01.
Read /start
The 20-lesson curriculum
The courseFour modules — coding, cloud, full-stack, AI products. Every lesson explains the value before the lab. Twenty public lessons, readable end to end.
Open syllabus
The engineering blog
33 articlesThirty-three deep articles that pair with specific lessons. Read the article first to build the model, then apply it hands-on in the matching lesson.
Browse blog
Reading paths
5 sequencesFive curated sequences through the blog: containers, version control, JSON + APIs, editor + terminal, mobile direction. Each path ends in a curriculum lesson.
Open paths
The engineering glossary
ReferenceEvery technical term — Docker, JSON, API, container, repo — defined plainly with cross-links to the lesson and article that use it. The reference shelf.
Open glossary
Career paths after the curriculum
After the courseThree practical paths after lesson 20: role-ready portfolio, internship or freelance evidence, or a small product of your own. The page keeps ambition high and outcome claims truthful.
Read paths
Tool and platform logos are learning-context references only: no affiliation, endorsement, interview access, hiring promise, salary promise, or placement guarantee.
Common questions
The questions every honest learner asks first.
Honest answers — no marketing softening, no false promises. If your question is not here, send it to Divyanshu and the next version of this page can include the answer.
Do I need a science / engineering background?
No. The curriculum is explicitly designed for learners locked out of formal AI / DS programs by stream gating. Commerce, arts, humanities — all welcome. The only requirement is willingness to read carefully.
Do I need to know coding before I start?
No. Lesson 01 starts with AI-assisted coding from zero. By lesson 05 you can navigate a terminal, use Git, and ship a small app to GitHub. The pace assumes you have not coded before.
How long does the whole curriculum take?
One lesson per week is reasonable — about 20 weeks. At two per week it is 10 weeks. Most learners study evenings and weekends; full-time learners can complete in a month with intensity. Pace is yours.
Is the public syllabus really open, or is there a catch?
Yes. All 20 lessons, 33 blog articles, the glossary, reading paths, and strategic pages are publicly readable on this site. Treat them as the proof layer: paid founder-led plans exist separately, but the syllabus itself is enough to judge the method.
Are placements guaranteed?
No. ABCsteps teaches skill and ships proof of work. Job, internship, and salary outcomes depend on you, the market, and verified employer programs — we do not claim what we cannot prove. See /career-paths for the honest framing of three real paths after the curriculum.
How can I ask a question?
Use the contact page or WhatsApp link when a question is not answered by the lesson, blog article, glossary, or reading path. Specific questions get better answers: name the page, what confused you, and what you already tried.
What if I get stuck during a lesson?
Pair the lesson with its matching engineering blog article and glossary term — most stuck moments resolve there. Re-read the exact section, search the exact error, and write down what you expected versus what happened.
Is the course in English or Hindi?
Course material is in English — readable, plain English, not academic English. Questions can be asked in English or Hindi, whichever you are more comfortable with.
Paid-plan decision
Choose paid guidance only when it changes the next artifact.
Use this decision layer after the FAQ: continue the proof layer when the page answers you, ask a specific question when one blocker remains, and compare plans when accountability or review is the missing piece.
Still exploring
Use the proof layer first
Choose this when the next lesson, article, glossary note, or reading path can answer the question. The public proof layer should solve obvious blockers before any paid-plan conversation.
Continue proof pathOne blocker
Ask a precise question
Choose this when you can name the page, the exact blocker, and what you already tried. Specific questions get useful answers; vague anxiety usually needs more reading first.
Ask on WhatsAppNeed accountability
Compare plans
Choose this when the missing piece is not information but structure: study materials, doubt help, live accountability, private review, or a serious project review.
Compare plansIf the hub is not enough
Use paid help only after the learner map exposes a real need.
The learner hub should answer orientation questions without a sale. If the blocker is no longer information but accountability, review, or a team-level outcome, the paid plan ladder gives the next honest choice.
How to choose
Start with the free lessons. Upgrade when videos, Q&A, live accountability, private review, or institutional delivery helps you finish stronger work.
Free start
Free written lessons
INR 0
20 lessons, blog, glossary, and reading paths remain readable without signup, checkout, or account creation.
Open lessonsJob-Ready Track
FoundingABCsteps AI Engineering Course · Job-Ready Track
INR 4,999
A self-motivated learner who has read enough of the public syllabus to trust the teaching style and wants founder guidance without live cohort pressure.
Open Job-Ready TrackCohort
RecommendedCohort — Live group track
INR 14,999
per cohort batch
A learner who stalls in self-paced courses, needs scheduled live accountability, and can attend Saturday/Sunday IST calls.
Open CohortMentorship
Capacity1:1 Mentorship
INR 49,999
per mentee · 8-week engagement
A career switcher, founder, or engineer with stakes high enough that private review is worth more than another course.
Open MentorshipArchitecture Review
Project Architecture Review
INR 24,999
per session
An engineer, founder, or technical lead with a specific decision expensive enough to justify a serious second opinion.
Open Architecture ReviewWorkshop
Institutional Workshop
INR 2L–5L
quoted after scoping
A college, school, bootcamp, or engineering team with 20-60 participants and a clear AI-engineering capability goal.
Open WorkshopProof standard
Learning proof has to be verifiable.
ABCsteps does not display fabricated success stories, placement claims, or borrowed-looking proof. The site teaches through public lessons and articles; learner outcomes are shared only when they can be verified with real projects, repository links, demo URLs, and clear context.
The four standards on the right are non-negotiable. Any story that cannot meet all four does not get published, no matter how flattering it would be.
Consent first
Every learner story is published only with explicit written permission from the person being featured.
Project evidence
Stories link to real work — repository, demo URL, article, or recorded explanation. Words alone do not qualify.
Verified outcomes
Placement, salary package, internship, and hiring claims are shared only when there is verified evidence we can point to.
Useful detail
Each story explains the starting point, the project built, the difficulty faced, and the next step the learner is taking.
Portfolio proof
The story is not the claim. The project is the proof.
ABCsteps can publish learner stories only when the work itself can be inspected. No fake review cards, no borrowed credibility, no unclear screenshots. A useful story links to a repo, a demo, an explanation, and the exact engineering boundary the learner crossed.
Versioned work
Repository trail
The learner can show what changed over time, what each commit did, and how the README helps another person run or review the project.
Artifact: A public repository with readable commits, a README, and the exact lesson or module it connects to.
Beyond localhost
Runnable demo
The project reaches a working surface beyond the learner laptop, or provides a repeatable build path that another engineer can execute.
Artifact: A reachable demo URL, static deployment, container command, or repeatable build/deploy note.
AI boundary
AI feature boundary
The story explains where AI helps, where it can fail, what data shape passes through the system, and what the human still verifies.
Artifact: A prompt, JSON payload shape, failure path, cost or safety note, and human review step.
Career language
Career explanation
The learner can describe the work in practical engineering language instead of listing tools without context.
Artifact: A short explanation that links the project to lessons, the next path, and the skill surface it demonstrates.
Company and platform logos are ecosystem references only. They do not imply partnership, endorsement, interview access, hiring preference, salary outcome, or placement guarantee.
Begin the path
Your first lesson is one click away.
The 20-lesson public syllabus is readable end-to-end — no signup, no email gate, no paywall. Begin with lesson 01, then use the reading paths when you want a slower conceptual route.
Public lessons · Engineering articles · Glossary · Honest learner guidance