Scaler AI/ML Fees 2026: Course Cost, EMI Options and What's Included
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If you are searching for Scaler AI ML course fees, you probably want one answer first: how much does the course actually cost?
Scaler's AI & Machine Learning with Agentic AI programme is currently listed at ₹3,99,000, with EMI starting at ₹9,791 per month and a ₹20,000 upfront commitment. The programme page also states that no-cost EMI is available. The programme is presented as a 12 to 15-month programme, depending on the track.
That is a substantial investment. It is also important to understand exactly what the fee covers, what you may have to pay separately, how the EMI works, and whether a structured AI/ML programme makes sense for your particular situation.
This guide breaks down the published fee, payment options, programme inclusions and the questions you should ask before enrolling.
How much does the Scaler AI/ML course cost?
Scaler's AI & Machine Learning with Agentic AI programme is listed at ₹3,99,000 total, with EMI starting at ₹9,791 per month and a ₹20,000 upfront commitment. The course page also states that no-cost EMI is available. Confirm the current pricing and financing terms with admissions before enrolling, as fees and financing conditions can change.
Fees checked on Scaler's AI & Machine Learning course page in October 2026.
For the latest programme details, visit Scaler's AI & Machine Learning course page.
Scaler AI/ML course fees at a glance
| Fee component | Published information |
|---|---|
| Programme | AI & Machine Learning with Agentic AI |
| Total programme fee | ₹3,99,000 |
| Upfront commitment | ₹20,000 |
| EMI starting from | ₹9,791 per month |
| No-cost EMI | Available |
| Programme duration | 12 to 15 months |
| Certification | NSDC certification |
| Career support | Included |
| Mentorship | Included |
| Projects and practical learning | Included |
| Lifelong access | Included |
The figures above should be treated as the published information available at the time of checking. Financing arrangements can vary, so confirm the exact EMI amount, tenure, upfront payment and lender conditions before signing an agreement.
Your exact EMI amount depends on the tenure and financing terms you choose, so ask admissions or the financing partner for your full repayment schedule before you commit.
Which Scaler AI/ML course is this fee for?
One important distinction can save you considerable confusion.
The ₹3,99,000 fee discussed in this article is for Scaler's AI & Machine Learning with Agentic AI programme. It is not the same programme as Scaler's Data Science and Machine Learning course, even though the published total fee for the two programmes is currently the same.
Scaler offers multiple learning products related to AI, machine learning and data science. These programmes can differ in curriculum, duration, learning format and intended learner profile.
If you are comparing programmes, identify the exact course before comparing its fee.
For example, Scaler also offers an advanced AI engineering certification with IIT Roorkee. Its pricing and structure should be evaluated separately rather than assumed to be the same as the AI & Machine Learning with Agentic AI programme.
The same principle applies when you see third-party websites quoting Scaler fees. An older fee for another Scaler programme can easily be mistaken for the current AI/ML fee.
What does the Scaler AI/ML fee actually cover?
A ₹3,99,000 programme fee can sound very different depending on what you believe you are actually buying.
The fee is not simply payment for access to a collection of Python or machine learning videos. The programme is structured around live learning, mentorship, practical projects and career preparation.
According to the programme information, learners receive access to:
- The programme's different learning tracks and modules
- Live learning
- 1:1 mentorship from working professionals
- Project-based learning
- AI-assisted labs
- Practical projects
- AI mock interviews
- Resume review
- Mock interviews
- Placement assistance
- NSDC certification
- Lifelong access to recordings
- Curriculum and future updates
The curriculum is designed around AI and machine learning skills, with the Agentic AI component adding another layer to the programme.
This distinction is important when evaluating the price.
You are not paying ₹3,99,000 because Python, PyTorch or machine learning algorithms are unavailable elsewhere. They are not. A large amount of high-quality technical learning material is available for free.
What you are paying for is the learning structure around that material.
That includes having a defined sequence to follow, deadlines, projects to complete, mentors to approach, feedback mechanisms and career preparation.
You can also review the agentic AI syllabus to understand the programme's learning areas in greater detail.
What is not included in the fee?
AI and machine learning can involve costs beyond tuition.
For example, learners working on computationally intensive projects may need access to cloud GPUs or paid compute services. Depending on the tools and scale of a project, this could involve services such as AWS, Google Cloud or Microsoft Azure, or paid compute tiers and rented GPU resources.
External certification examinations can also involve separate fees.
However, these costs should not be assumed to be additional programme charges without confirmation. If you are considering enrolment, ask admissions which infrastructure, software, certifications and other services are included in your specific programme fee and which are billed separately.
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The published course page lists a ₹20,000 upfront commitment, an EMI option starting at ₹9,791 per month, and states that no-cost EMI is available.
That does not mean every learner will receive the same EMI schedule.
Your actual financing arrangement can depend on the lender, repayment tenure and other terms of the financing agreement.
How does no-cost EMI work?
The phrase "no-cost EMI" can make a programme's fee appear simpler than it actually is.
With a no-cost EMI arrangement, the interest component is generally structured so that the borrower does not bear the advertised interest cost in the same way as a standard interest-bearing EMI. However, the financing arrangement is still a loan or credit arrangement through a lender.
That means you should read the financing agreement rather than relying only on the phrase "no-cost EMI".
Before accepting an EMI plan, check:
- The total amount payable
- The repayment tenure
- Processing fees, if any
- The upfront payment
- The lender providing the financing
- Conditions attached to the no-cost option
- What happens if you discontinue the programme
A no-cost EMI is still a financial commitment.
What happens if you leave the course midway?
This is one of the most important questions to ask before enrolling.
Leaving an educational programme does not necessarily mean that an associated financing agreement automatically ends.
The programme fee, refund policy and loan agreement can involve separate terms. If you are considering EMI financing, ask admissions and the lender specifically what happens to your outstanding loan if you withdraw from the programme.
Do not rely on assumptions about what "should" happen.
Get the answer in writing before you commit.
What about refunds?
Refund terms should be checked specifically for the AI/ML programme before enrolment.
Do not assume that the refund policy of another Scaler programme automatically applies to this programme. If a refund or cooling-off period is important to your decision, ask admissions for the current terms applicable to your cohort.
How does the Scaler AI/ML fee compare with typical AI/ML course pricing?
AI and machine learning education covers a very wide range of price points.
At one end, there are free resources, open-source documentation and university-level educational material available online. At the other end, there are career-transition programmes, postgraduate programmes and degree routes costing several lakh rupees.
Our broader guide to how AI and ML course fees vary across India covers these categories in greater detail.
The important point is that ₹3,99,000 sits toward the higher end of the career-transition course range.
That does not automatically make the programme good or bad value. It tells you that the comparison should not be limited to the number printed on the price tag.
A learner comparing a ₹20,000 self-paced course with a ₹3,99,000 structured programme is not necessarily comparing identical products.
Both may teach Python.
Both may teach machine learning.
Both may introduce neural networks.
But one may provide a predefined learning path, live instruction, mentorship, deadlines, projects and career support, while the other may primarily provide educational content.
The difference is structure and accountability, not secret content.
If you already have the discipline to create your own curriculum, complete projects independently and prepare yourself for interviews, you may not need to pay for that structure.
If you repeatedly start courses but struggle to finish them, require external accountability or want direct mentorship and career preparation, the additional services may be more relevant to you.
Is the Scaler AI/ML course worth the fee?
There is no universal answer to whether a ₹3,99,000 programme is worth paying for.
The better question is:
What problem are you paying the programme to solve?
If the problem is simply "I need to learn Python", paying several lakh rupees is difficult to justify when high-quality Python resources are freely available.
If the problem is "I need a structured path from my current technical background into AI/ML, someone to review my work, a sequence of projects, interview preparation and career support", then you are evaluating a much broader product.
What does the fee buy that free resources do not?
Free resources can provide an enormous amount of technical knowledge.
You can learn:
- Python
- Statistics
- Linear algebra
- Machine learning
- Deep learning
- PyTorch
- Transformers
- Generative AI
- Model deployment
without paying ₹3,99,000.
What free resources generally do not provide as one integrated package is a predetermined sequence, deadlines, personal mentorship, structured projects, mock interviews and a formal career-support process.
That is the part of the programme you should evaluate.
What does the fee not buy?
A high programme fee does not automatically buy:
- A guaranteed job
- A guaranteed salary increase
- A guaranteed career transition
- Guaranteed placement
- Knowledge unavailable elsewhere
The learner still has to complete the coursework, build skills, work on projects and prepare for interviews.
Career support can support that process, but it cannot replace the learner's own effort.
Before making a financial decision, consider your current compensation, your realistic target roles and the salary range you could reasonably expect after developing the required skills. You can use resources such as what AI and ML engineers actually earn in India as one input into that calculation.
Do the break-even calculation using your own circumstances rather than relying on a generic salary promise.
Who should not pay for this course?
This is perhaps the most important section to read before looking at the programme's benefits.
A structured programme is not automatically the right choice for everyone.
You are already strong at mathematics and can self-study
If you are comfortable with linear algebra, probability, calculus and programming, and you have a history of completing difficult courses independently, you may be able to build an AI/ML skillset using free or low-cost resources.
You can learn the same underlying libraries and concepts without spending ₹3,99,000.
If you can design your own curriculum, find projects, seek feedback and prepare for interviews independently, the additional value of a structured programme may be limited for you.
You can keep the money and build the skillset yourself.
You want one specific skill, not a career transition
Suppose your objective is simply to learn PyTorch.
Or perhaps you want to understand large language models.
Or you need enough machine learning knowledge to contribute to one project at work.
In that case, a full career-transition programme may be unnecessary.
A targeted course, documentation or specialised learning path could be enough.
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A structured programme only works if you can actually follow the structure.
If you have a demanding job, family responsibilities or other commitments that make consistent study difficult, consider whether you can realistically maintain the required workload.
Paying for a programme and then leaving halfway through can make the financial decision much more difficult to justify.
The EMI would put you under financial pressure
This one is straightforward.
If the monthly repayment would significantly strain your finances, do not assume that a possible future salary increase will automatically solve the problem.
A loan you cannot comfortably service is a serious financial commitment, regardless of how attractive the programme looks.
You expect the programme to find you a job without doing the work
Career support is not the same thing as a job guarantee.
You will still need to learn the material, complete projects, develop technical skills, prepare for interviews and apply yourself during the job search.
There is no placement guarantee.
If you want to test whether you can learn the subject independently first, you can start with resources such as the free mathematics for machine learning course or the free machine learning roadmap.
Who is the course better suited to?
The programme is designed for tech professionals — such as SDEs, data analysts and data scientists — with at least one year of industry coding experience. Admission is based on performance in the Scaler Entrance Test (SET), which assesses coding skills and aptitude.
The programme may be more relevant to learners who know that they need structure to make consistent progress.
For example, it may suit:
- Software professionals looking to move into AI/ML
- Professionals with some programming experience who want a structured transition
- Learners who repeatedly struggle to complete self-paced courses
- People who value regular mentorship and feedback
- Tech professionals switching into AI/ML roles who want a defined learning sequence
- Learners who want interview preparation alongside technical training
- Professionals who want projects and practical assignments built into their learning path
The key question is not whether you fit one of these categories perfectly.
It is whether the programme addresses a genuine learning or career problem that you have.
What about AI/ML placement and salary numbers?
Outcome statistics can be useful, but only when their methodology is clear.
A placement percentage among learners who completed a programme and met placement eligibility criteria is different from a placement percentage calculated across everyone who enrolled.
Similarly, an average CTC among placed learners does not tell you what every learner earned.
For this reason, AI/ML-specific placement or salary figures should only be published alongside their source, cohort, reporting period, sample size and exclusions.
If a figure cannot be explained clearly, it is better not to use it.
In particular, AI/ML-specific outcomes should not be confused with statistics from Scaler's Data Science and Machine Learning programme or all-programme statistics. Those represent different learner populations.
For a prospective student, the most useful question is not simply "What is the highest salary?"
Instead, ask:
- Which learners were included?
- How many learners were included?
- What period does the data cover?
- What does the placement percentage use as its denominator?
- Are all enrolled learners included?
- What qualifies a learner for placement support?
- Is the salary figure an average, median or another measure?
Those questions give you a more realistic picture of outcomes than a single headline number.
What do learners say about the programme?
Reviews can provide useful context, particularly around the actual learning experience.
When reading reviews, look beyond individual star ratings or isolated comments.
Pay attention to recurring themes such as:
- Quality of mentorship
- Difficulty and pace of the curriculum
- Project workload
- Support received during interview preparation
- Responsiveness of mentors
- Experience of working professionals balancing the course with a job
- Whether learners found the structure useful
It is also worth reading critical feedback alongside positive experiences.
A programme designed for intensive learning may feel manageable to one learner and overwhelming to another.
You can explore Scaler learner reviews before making your decision.
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FAQs
How much does the Scaler AI/ML course cost?
Scaler's AI & Machine Learning with Agentic AI programme is currently listed at ₹3,99,000. The programme page also lists EMI starting at ₹9,791 per month and a ₹20,000 upfront commitment. No-cost EMI is stated to be available. Confirm the current fee and financing terms before enrolling.
Does Scaler offer no-cost EMI for the AI/ML course?
Yes. The current programme page states that no-cost EMI is available. It also lists a ₹20,000 upfront commitment and EMI starting at ₹9,791 per month. Confirm the exact tenure, lender and repayment schedule before signing the financing agreement. A no-cost EMI remains a credit arrangement with a lender.
How long is the Scaler AI/ML course?
The programme is currently presented as a 12 to 15-month programme, depending on the track. Confirm the duration applicable to your cohort before enrolling.
Who is eligible for the Scaler AI/ML course?
The programme is designed for tech professionals, such as SDEs, data analysts and data scientists, with at least one year of industry coding experience. Admission is based on performance in the Scaler Entrance Test (SET).
Is the Scaler AI/ML course the same as its Data Science and Machine Learning course?
No. They are separate programmes with different curricula and learning objectives. The published total fee for both programmes is currently ₹3,99,000, but the programme names and course structures are different. Make sure you are comparing the exact programme you intend to join.
What happens to my EMI if I leave the course partway through?
Do not assume that withdrawing from the course automatically cancels an EMI arrangement. Ask admissions and the lender what happens to your outstanding financing if you withdraw. Get the answer in writing before enrolling.
Are there additional costs beyond the course fee?
Potential costs can include cloud GPU or compute usage and external certification examinations. However, you should confirm which costs are included in your programme rather than assuming that every infrastructure or certification expense is separate.
Is there a cheaper way to learn AI and ML?
Yes. Many AI and machine learning concepts can be learned through free resources, university courses, official documentation and open-source material. The reason to consider a paid programme is therefore not access to secret technical knowledge. It is the additional structure, mentorship, projects and career support.
Is the Scaler AI/ML course worth ₹3,99,000?
That depends on what you need from the programme. If you are highly self-directed and can build your own curriculum, projects and interview preparation, free and low-cost resources may be sufficient. If you need structured learning, mentorship and career support, those services may have greater value. Compare the cost against your own goals, finances and time commitment.
Final thoughts
The Scaler AI/ML programme currently carries a ₹3,99,000 published fee, with EMI starting at ₹9,791 per month and a ₹20,000 upfront commitment. It also offers no-cost EMI, live learning, mentorship, practical projects, career support and lifelong access to learning material.
But the price should not be evaluated in isolation.
The technical content itself is not exclusive. Python, statistics, machine learning, deep learning and AI frameworks can all be learned through free resources.
The real question is whether you need the structure and accountability surrounding that content.
If you are already capable of designing your own learning path, completing projects independently and preparing for interviews, you may be able to achieve your goals without spending ₹3,99,000.
If you know that you learn better with deadlines, mentors, structured projects and a defined career path, the programme offers those components in one package.
Either way, check the current fee, EMI terms, refund conditions and withdrawal terms directly with admissions before committing.
Most importantly, make the decision based on your own learning style, financial position, available time and career objectives.
