00 Live online · Weekends · 10 people a batch
If you have got a job, a boss and probably an EMI, but you still want to learn AI properly, this page is for you.
By Sayeed Amaan, AI Lead at SophyXis Technologies · Last updated 16 October 2026
Quick answer
It depends what you do today. If you code or work with data and want to build with AI, go for a live weekend course that properly gets into LLMs, RAG and agents, and makes you deploy things. If it is the university name you are after, BITS Pilani WILP and IIMBx both run 10 to 11 month programmes at around ₹2.25 to ₹2.45 lakh. Not from a tech background? Google’s AI Professional Certificate is self-paced and not a bad start. Zero budget right now? Coursera and Great Learning have free courses worth starting with.
We hear the same story a lot. Five or six years into IT or analytics. The team has started talking about LLMs and agents. You want to be part of that work, not watch it from the side. And quitting to study for a year? Not happening.
So this is the page we would want to read in that spot. The top half covers the courses people like you usually end up comparing, with fees and durations side by side. The bottom half is ours. If the top half sends you somewhere else, fair enough.
Ours, quickly: live classes on weekends, ten people a batch, and most of the syllabus spent on LLM work — RAG, agents, fine-tuning, and actually shipping it. There is classical ML too. We just do not stop there.
01 Read this first
Most AI course pages are written for freshers. Freshers have time. They do not have much at work to lose.
You are in a different spot. For you the fee is not the real cost — your Saturdays are. Burn four months of them on the wrong course and no refund policy gives them back.
People who end up happy with whatever they picked, us or someone else, seem to have asked three things before paying:
Will I manage these timings in a bad month at work?
Is this syllabus from this year, or 2022 with a fresh cover?
When they say “placement”, what actually happens?
The rest of this page goes after those.
02 Compare
Below are the programmes that keep coming up when people ask us to compare. For each one we have noted format, length, fee, how much coding it expects, whether GenAI gets real time, and whether anyone helps you find a job. All of it is from the providers’ own pages as of October 2026. Fees change, so check with them before paying.
| Course | Format | Duration | Fee | Coding? | LLMs, RAG, agents | Placement help | Best for |
|---|---|---|---|---|---|---|---|
| ShiftToTech AI Course | Live online, weekends (IST). Every class recorded | 10 weeks, 96 live hours | ₹35,000, EMI available | Basic Python helps. Module 1 covers it | Main focus: two full modules | Yes: resume, mock interviews, referrals. No guarantee | Developers, IT and data professionals moving into AI engineering |
| BITS Pilani WILP: PG Certificate in AI & ML | Live weekend classes, virtual labs, in-person exams at centres | 11 months | ₹2,45,000 | Yes. Needs a B.Tech or B.Sc. and 6 months’ work experience | Electives in Generative AI and Agentic AI | No placement assistance | People who want a university credential and alumni status |
| IIMBx: AI for Managers | Online, IIMB faculty-led, with on-campus live sessions | 10 months | ₹2,25,000 + 18% GST | Some. Includes an ML with Python course | One course on GenAI and agentic AI | Not mentioned | Managers and consultants with 3+ years’ experience |
| SAS Academy: AI & ML Course | Live online weekends, recordings, 12 months of eLearning access | 6 months (151.5 hours) | Not listed | Basic programming and statistics recommended | GenAI, RAG and agentic AI on SAS Viya with Python | Not mentioned. Prepares you for SAS certifications | Enterprise and BFSI analytics professionals |
| Google AI Professional Certificate | Self-paced online | 8 short courses, about an hour each | US$49/month in the US. Varies by country | No | Using AI tools at work, not building AI systems | No | Non-technical professionals using AI in their current job |
| Coursera AI and ML courses | Self-paced online | Varies | Many free to audit. Certificates are paid | Varies | Varies a lot by course | No | Low-cost certificates from global brands |
| Great Learning Academy free AI courses | Self-paced online | Mostly 30 minutes to 7.5 hours | Free | Mostly no | Introductory | No | Beginners testing their interest |
| Udemy AI courses | Self-paced video | Varies | Low one-time price | Varies | Varies a lot by course | No | Learning one specific tool cheaply |
Sources: official programme pages of BITS Pilani WILP, IIMBx, SAS India, Google and Great Learning, checked in October 2026.
How we would read it.
University name matters most? Go with BITS WILP or IIMBx and accept the longer timeline and bigger fee. You do not code and want AI to make your current job easier? Google’s certificate. Our course is for the people in the middle — they want to build with LLMs on weekends, and they do not want to spend a year or ₹2 lakh getting there. If you want the edtech platforms compared instead (upGrad, Scaler, Simplilearn and the rest), that is a separate comparison of nine options, and the fee brackets are broken down here.
03 By role
You code already. Please do not pay for three months of Python basics. Find a course where most of the hours go into LLM work, RAG, agents and deployment, and where you build and ship your own projects instead of typing along. Most of our students come from here, for what it is worth — the AI Engineer track is the same programme framed around the job title.
SQL, dashboards, Excel models — you have those. The usual gap is proper ML, then GenAI on top. Pick a course that does not rush through classical ML to reach the exciting part. And if pipelines interest you more than models, look at our data engineering course instead.
Mostly want AI to help with your own work? A short tool-based course like Google’s will do. Running tech teams and need to understand the models well enough to make decisions? IIMBx’s AI for Managers is meant for you. Ours would be more code than you need, if we are being fair.
Try a free course first. You will pick up the words people use and find out if you like this at all. Then a few weeks of basic Python. Module 1 does teach Python, but learning to code from zero next to a full-time job is a slog.
What you are missing is the newer layer — LLMs, RAG, agents, fine-tuning, LLMOps. Ask any provider if you can move faster through the early modules. On our intro call, tell us what you know and we will tell you how much would be repetition. If you only want that layer, the Generative AI course covers it on its own.
04 Syllabus check
Working in tech gives you one big advantage over a fresher here: you can tell when a syllabus is old.
A lot of AI courses in India still teach roughly what was current in 2022 — Python, scikit-learn, a little deep learning, and that is it. Interviews at product companies and GCCs have moved on. They now ask about LLMs, RAG, agents, fine-tuning and some MLOps. Know only classical ML and you will often get stuck in the early rounds.
So with any syllabus, ours included, check one thing: is the LLM side — RAG, agents, fine-tuning, deployment — taught as proper modules, or does it all end at scikit-learn? One bonus ChatGPT video at the end does not count. In ours, GenAI takes up most of the second half.
Try this in a demo class. Ask how they would build RAG over a company’s internal documents, and what usually goes wrong. Someone who builds this at work will start on chunking, bad retrieval, stale docs, and who is allowed to see which file. Someone reading off slides will define RAG and move on. You will know in two minutes.
05 Fit
We would rather not take your money than have you spend four months of weekends wishing you had not. So, both sides.
It is a good fit if
It is probably not for you if
06 Syllabus
Six modules across 10 weeks, 60 hours of live teaching in total. Modules 1 to 3 build the base; 4 to 6 are where we spend most of the effort, because that is what AI interviews and AI work look like now. It is the same syllabus as our main AI course — this page just frames it for people who are doing it alongside a job.
1
NumPy and Pandas for wrangling data, plus the linear algebra, probability and statistics you will lean on later. We teach the maths right next to the code that uses it. Nobody needs a semester of theory at 9am on a Sunday.
Tools: Python, NumPy, Pandas, Jupyter
2
Regression, classification, trees, ensembles, clustering. Why each one works and, more usefully, when it breaks. Feature engineering and evaluation get proper time, because interviewers still ask.
Tools: scikit-learn, XGBoost
3
Backpropagation first, without burying you in notation. Then PyTorch: CNNs, sequence models, and how to debug training when the loss does something strange. After this, transformers in Module 4 will not feel like magic.
Tools: PyTorch
4
What is going on inside an LLM, prompting beyond the LinkedIn hacks, embeddings, and building on the OpenAI, Anthropic and Google APIs. Then fine-tuning: when is it worth it over RAG? Less often than people think — and when it is, LoRA and QLoRA on Hugging Face keep it cheap.
Tools: Hugging Face, LoRA/QLoRA, OpenAI, Claude and Gemini APIs
5
RAG done properly: chunking, hybrid search, re-ranking and citations, so answers come from your documents instead of the model’s imagination. Then agents — tool calls, multi-step workflows, orchestration. We finish on evaluation and guardrails, the part most tutorials skip and the part that usually decides whether an LLM feature ever reaches users.
Tools: LangChain, LangGraph, LlamaIndex, vector databases, MCP
6
Putting a model behind an API, watching it, catching drift, and the LLMOps version of the same. You build a capstone, deploy it and present it. Mock interviews for mid-career AI roles run alongside, and placement help continues after the last class.
Tools: FastAPI, Docker, cloud deployment, monitoring
07 Portfolio
Every module ends with something you can push to GitHub and talk through in an interview. Expect 10+ by the end, each with a README covering the problem, what you chose and what you would change. The seven below are the backbone:
A RAG assistant over company documents, with hybrid search, re-ranking and source citations, deployed as an API
A LangGraph agent that handles a multi-step task, such as triaging and routing support tickets
A fine-tuned small model (LoRA) for a classification task, benchmarked against plain prompting
An evaluation pipeline for an LLM feature: test set, automatic scoring, guardrails
A classical ML pipeline served with FastAPI and Docker
A deep learning model for an image or text problem
Your capstone — ideally a problem from your own job. You build it, deploy it and defend it in front of the instructor
08 Schedule & fees
AI course fees in India are all over the place. Self-paced platforms run from free to about ₹25,000. Live weekend bootcamps are usually ₹35,000 to ₹90,000. University programmes run from about ₹1.5 lakh to well past ₹2.5 lakh — BITS Pilani WILP’s PG Certificate is ₹2,45,000, and IIMBx’s AI for Managers is ₹2,25,000 plus GST.
We are in the bootcamp bracket:
The fee pays for a batch of ten, live classes with a working AI engineer, 10+ portfolio projects, recordings you keep, and placement help that does not stop when the course does. Our refund policy is published in full.
Ask everyone, us included: where is the money going? Small batches and someone actually reading your code? Or a 100-seat recorded cohort and a lot of Instagram ads?
09 Certificate
Finish all six modules and the capstone and you get the ShiftToTech Certificate in Applied AI Engineering.
It is not a degree, and a certificate on its own does not get anyone hired — we will not pretend otherwise. What helps in interviews is a deployed project you can demo, and being able to say why you would pick RAG over fine-tuning, or the other way round. Need a university stamp? The table above shows where to get one.
10 Placement
Few words in this market have been stretched as much as this one.
Usually it means one of two things. Your CV gets bulk-mailed to job portals. Or there is a “job guarantee” with a page of fine print — full attendance, internal tests, a minimum number of applications — that makes it easy for the institute to say no when you claim. And average salary numbers? One big package in a small batch drags the average right up.
What we do is less exciting to write about. Resume and LinkedIn rework. Mock interviews based on how AI rounds actually go now, where RAG and agents come up constantly. Referrals, where we know someone. Help negotiating when an offer comes. No job promise, no salary promise. Your offer depends on your interviews, and we cannot sit them for you.
A test for anyone, us included: ask for the LinkedIn profiles of two or three working professionals they helped in the last six months. Then go and look at where those people are now.
We just told you to ask for proof, so this is ours. Shared with each person’s permission.
| Name | Before | After | Batch | Profile |
|---|---|---|---|---|
| Yash Sharma | AI/ML Engineer Intern, Sudarshan Herb & Health Care | Junior AI/ML Engineer, Sudarshan Herb & Health Care | October 2025 |
11 Instructor
Sayeed Amaan — AI Lead at SophyXis Technologies (4+ years)
Sayeed teaches the AI batches end to end, from the Python and classical ML foundation through deep learning, LLMs, RAG and agents. At work he builds NLP, computer vision and generative AI systems, which is why the LLM modules are built around what actually breaks in production rather than what demos well.
Full instructor profiles and LinkedIn links
Rated 4.5 out of 5 across 15 Google reviews.
12 FAQ
It depends on your role and where you want to end up. If you have a coding or data background and want to build AI systems, look for a live weekend course that covers LLMs, RAG and agents properly and makes you deploy your own projects. If you want a university name, the usual picks are BITS Pilani WILP’s PG Certificate in AI and ML (11 months) and IIMBx’s AI for Managers (10 months). If you are non-technical and just want AI to help at work, Google’s AI Professional Certificate fits better. The comparison table on this page lays it all out.
Yes. Almost everyone in our batches has a full-time job. Classes run live on Saturdays and Sundays, 8:00–11:00 PM IST, and every one is recorded, so a release week or a late client call will not sink you. Budget about 8 to 10 hours a week across 10 weeks.
Probably not ours, to be honest. If you do not code and want AI for research, writing, analysis or small tools, Google’s AI Professional Certificate fits better and it is self-paced. If you manage tech teams and need to understand models well enough to make decisions, IIMBx’s AI for Managers is built for that. We would rather send you there than sell you something too code-heavy.
Plenty. Coursera, Great Learning Academy and Google all have free or cheap introductory courses, many only a few hours long. They are good for the vocabulary and for working out whether you enjoy this. The catch, if you are working, is finishing: nobody follows up, there is no one to ask when you are stuck, and you rarely end up with anything deployed. Start free, and pay once you know you want more.
Roughly: free to ₹25,000 for self-paced platforms, ₹35,000 to ₹90,000 for live weekend bootcamps, and ₹1.5 lakh to ₹2.5 lakh and beyond for university programmes. BITS Pilani WILP’s PG Certificate is ₹2,45,000 and IIMBx’s AI for Managers is ₹2,25,000 plus GST. Ours is ₹35,000, with EMI available.
Our programme runs 10 weeks — about four months — at roughly 8 to 10 hours a week if you already code. That is enough to go from the basics to building and deploying LLM, RAG and agent projects. University programmes take 10 to 11 months. Tool-focused certificates take a few weeks, but they teach you to use AI rather than build with it.
Probably yes, if you stopped at scikit-learn. The second half — LLMs, RAG, agents, fine-tuning and MLOps — is exactly the part people who learned ML around 2020 to 2022 tend to be missing, and it is what interviews look at now. Tell us what you already know on the intro call and we will say honestly how much of the early modules would be repetition.
Live classes run Saturdays and Sundays, 8:00–11:00 PM IST. Every session is recorded and shared afterwards, so if you miss one you watch the recording and bring your questions to the next class. Everyone misses a class at some point; the format is built to absorb that.
Both, but the weight is on GenAI. Module 4 covers LLMs, transformers, prompting and fine-tuning. Module 5 is RAG, vector databases, agents and evaluation. Classical ML comes first because you will use LLMs better once you understand what is underneath them.
No — and be wary of anyone who does. A no-strings guarantee is a marketing line, and one with lots of strings is written so it cannot be claimed. What you get from us is resume and LinkedIn work, mock interviews, referrals where we have contacts, and help negotiating an offer. We do not publish an average salary figure either, because one large package in a small batch makes that number meaningless.
By itself, not much, whoever issues it. For AI engineering roles interviewers want to see what you have built and hear you think through trade-offs — when RAG is enough and when you would fine-tune. University certificates help on a CV, and vendor ones from Google or SAS show tool skills. Ours comes with a deployed capstone, and that is what you will end up talking about in the room.
Both, really. Machine learning — classical and deep — is the base, and modern AI such as LLMs, generative AI and agents sits on top. Most 2026 roles want both. If data pipelines interest you more than models, our data engineering course is the better fit.
You can, but be realistic about it. Module 1 starts Python from a practical base and motivated beginners do keep up. Starting from zero code with only a few spare hours a week is tough, though. On the intro call we will tell you straight whether to join now or spend a few weeks on Python first.
13 Free intro session
Book a free intro session. You will talk to an instructor, not a sales team. Tell them what you do and when you are free, and ask the RAG question from earlier. By the end you will know if this course makes sense for you, what it costs, and which roles are worth going for. Next batch starts November 15, 2026.
14 Enroll
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