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Program Fee
INR 16,422/month
(Six-month interest-free EMI)
Application deadline
10th August, 2026
Duration
~36 weeks
Type of program
Certificate
Program introduction
An AI Engineering and MLOps professional builds and manages the systems required to take AI and machine learning solutions from experimentation to production.
The profile typically combines software engineering, machine learning, cloud infrastructure, data pipelines, deployment, automation, monitoring, and model optimization.
Why choose this program
Built for engineers who take AI to production. Learn deep. Build real. Ship to production.
Most professionals stop at experimentation. Few learn how to take AI and ML solution from experimentation to a production like system.
Learn deeper,
rise higher
by building familiarity with the processes and concepts involved in modern AI engineering workflows, covering areas such as data engineering, model engineering, quality engineering, platform engineering, cost optimization, while learning the principles and practices used in production like AI systems.
Knowing the tools isn't the same as running them at scale. Enterprises need engineers who can deploy and operate AI in real production environments.
Learn deeper,
rise higher
with hands-on experience in some of the leading AWS equivalents of open-source AI and MLOps technologies such as MLflow, vLLM, and ONNX that provide similar capabilities, developing the skills to deploy, scale, and manage AI workloads in enterprise production environments. Also note, tools can change basis Institutes assessment on what is best for the learner.
An accurate model isn't enough. If it's slow or expensive to run, it never makes it into a real business.
Learn deeper,
rise higher
with practical expertise in model serving, quantization, inference optimization, distributed training, and GPU-based computing, the engineering that makes AI systems faster, more scalable, and economically viable.
In the real world, AI doesn't just get built, it has to keep working. That's where most professionals fall short.
Learn deeper,
rise higher
with command of model versioning, data validation, drift detection, monitoring, CI/CD automation, A/B testing, and continuous retraining, the disciplines that distinguish AI engineers and MLOps professionals.
A certificate tells employers what you studied. It doesn't prove what you can build.
Learn deeper,
rise higher
with a comprehensive capstone that demonstrates end-to-end capability, from data engineering to platform engineering and monitoring, producing proof of your ability to deliver production like AI system.
In most programs, concepts make sense in the classroom but fall apart in production, leaving a gap between academic learning and real-world execution.
Learn deeper,
rise higher
with an experienced industry professional who brings real-world expertise to your learning journey. Apply your learning through one capstone project, with the topic selected at the Institute’s discretion and executed independently by each learner, helping you solve real-world challenges and build an industry-ready portfolio.
Knowing AI isn’t enough. You need the direction and confidence to put it to work in your career. That’s where our Career Services framework steps in which provides
Learn deeper,
rise higher
- Expert Guidance: Mentorship from industry professionals who help you align skills with real-world expectations.
- Curated Career Enablement: Access to opportunities through the BITS Pilani Digital’s career services ecosystem.
Disclaimer:
BITS Pilani Digital equips learners with industry-relevant skills and career support to enhance employability. However, job placement or advancement is not guaranteed. Opportunities depend on market conditions, learner performance, and individual goals. Learners are expected to take ownership of their career growth and actively apply what they learn.
Who should apply?
For engineers ready to go beyond building models and start shipping them. This program is built for professionals who want to work with production ML pipelines, deployment and serving stacks, MLOps automation, and enterprise AI infrastructure and turn AI from a promising prototype into a system that performs in the real world.
Software, Data & AI Professionals
For software engineers, backend developers, data engineers, and aspiring AI/ML engineers who can already build software and now want to build, deploy, and scale production-grade AI systems.
Cloud, DevOps & platform engineers
For infrastructure and platform professionals ready to run AI workloads at enterprise scale, containerisation, orchestration, model serving, and monitoring and become the MLOps backbone of their organisation.
Technical leads & architects
For tech leads, solution architects, and engineering managers responsible for taking AI initiatives live, who need genuine production depth to design, evaluate, and lead AI systems with confidence.
Essential proficiency requirements
Applicants seeking admission to the Professional Certificate in AI Engineering and MLOps must meet the following eligibility requirements:
Learning methodology
The program follows a flipped-classroom model, combining flexible self-paced learning with structured live sessions.
Learn in a flipped classroom format
- The program follows a flipped-classroom methodology, where learners first build conceptual understanding through self-paced learning material.
- Wherever applicable, they complete practice exercises and labs to apply these concepts before attending periodic live sessions scheduled mostly on weekends.
- The live sessions are designed for instructor interaction, doubt resolution, deeper discussion, and augmented learning.
Apply learning to real-world AI challenges
- Learners engage with a range of real-world AI challenges throughout the program, connecting conceptual learning with hands-on application.
- The program is designed to help learners translate classroom knowledge into practical industry-relevant solutions through exercises, labs, and project-based work.
Structured weekly learning routine
- Learner effort is expected to be typically 9–10 hours per week engaging with the program, including self-paced learning material, demos, lab practice, and live sessions.
- The mix of learning components may vary from week to week based on the requirements of each module.
- Note that the periodic live sessions are for ~2 hours, and the remaining learner effort is required to consume self-paced materials, demos, and lab practice.
Weekly live instructor interactions
- Learners attend weekly live sessions of ~2 hours, mostly on weekends.
- These sessions are led by subject matter experts, many of whom are industry practitioners.
- These sessions help bridge the gap between conceptual understanding and practical execution, supporting clarity and confidence as learners progress.
Support through teaching assistants
- Learning support is available beyond live sessions through teaching assistants and discussion forums.
- Learners can use these forums to seek clarifications, receive guidance on concepts, and get support on practice exercises and labs where applicable.
Global AI hiring is exploding, and skilled builders are the rarest resource.
That's where India's AI market will be by 2027 (Source: NASSCOM and Boston Consulting Group)
For every ten AI jobs, there's only one qualified engineer. (Source: TeamLease Digital)
That's how much more AI professionals earn over traditional tech roles.
Where opportunity meetsoutcomes
Build production-ready AI systems and accelerate your career.
Integrated throughout the curriculum to build practical, in-demand skills
Average salary hikes after completing such programs
That's all it takes to transform into an AI engineering leader.
Job roles in the industry
*Source: 6figr, Indeed, SOC Masters, GeeksforGeeks, Sharpener
This information is based on publicly available sources, and individual experiences may vary depending on multiple factors. Salary figures are based on publicly available information and are provided for reference only. Enrolment in or completion of this program does not guarantee any specific salary, job role, promotion, or employment outcome.
Learners across top organisations
Curriculum snapshot
Module Name | Brief Description |
| Applied AI Engineering Foundations | Understand AI/ML development lifecycles and their real-world applications. |
Module Name | Brief Description |
| Data Engineering for AI Systems | Design and manage data preparation workflows using labeling, validation, versioning, and project management tools. |
Module Name | Brief Description |
| Model Engineering (Classical + LLM) | Learn feature engineering, model training, tuning, evaluation, and advanced AI architectures, including LLMs. |
Module Name | Brief Description |
| AI Quality Engineering | Learn AI-specific testing for data, models, and pipelines using relevant tools and platforms.. |
Module Name | Brief Description |
| AI Platform Engineering | Develop practical AI deployment and MLOps skills across orchestration, containerization, monitoring, optimization, automation, scalability, and cost efficiency. |
Module Name | Brief Description |
| Responsible & Cost-Optimized AI | Understand AI governance, compliance, ethics, cost management, and organizational responsibilities for production systems. |
Project | Brief Description |
| Capstone Project | All the learners will work on 1 comprehensive guided capstone that demonstrates end-to-end capability, from data engineering to platform engineering and monitoring, producing proof of your ability to deliver production like AI system. |
Note: The curriculum provided for this program is indicative and may be updated from time to time.
BITS Pilani Digital may revise the curriculum, topics, tools, learning components, or sequencing based on the assessment of its technical experts, evolving market requirements, and emerging industry needs.
A program designed by AI practitioners and academic experts
Tarun Mishra
Expertise: Computer Vision | Machine Learning | Industrial Automation
- AI Architect, ex-Intel, ex-IBM, ex-Samsung, and ex-Wipro, with 17+ years of experience in full-stack development and applied AI
- 8+ years in AI/ML, specializing in Computer Vision, Signal Processing, and Robotics
- Proficient in Python, C/C++, TensorFlow, PyTorch, OpenVINO, LLMs, RAG, and fine-tuning models
- Built and deployed intelligent automation systems across industrial and enterprise domains
- Deep focus on bridging software engineering with AI-driven innovation
Ashish Prasad
Expertise: AI Systems Architecture | Applied Machine Learning | Enterprise AI Integration
- Senior Software Engineering Lead, Microsoft with 12+ years of experience at the intersection of AI and software engineering
- Builds large-scale AI systems integrating C#, .NET, TypeScript, SQL, Azure ML
- Works on AI-driven productivity and contextual intelligence for global enterprise users
- Contributes to Microsoft’s Project Turing, advancing AI research and real-world deployment
Dr. Hemant Rathore
Assistant Professor, Computer Science & Information Systems BITS Pilani, Goa Campus
- PhD from BITS Pilani with focus on adversarial robustness and explainable AI for malware detection
- 13+ years of combined industry & academic experience, including Symantec (Computer Security)
- Published extensively in top-tier SCI journals and CORE-ranked (A*, A, B) conferences with 180+ citations
- Recipient of multiple prestigious awards including Best Paper (DFRWS APAC 2024) and Best PhD Thesis (BITS Pilani)
- Principal Investigator on DRDO-funded project on explainability and out-of-distribution detection for AI systems
Prof. Subhrakanta Panda
Associate Professor, Computer Science & Information Systems BITS Pilani, Hyderabad Campus
- PhD in Computer Science from NIT Rourkela with academic and teaching experience at BITS Pilani
- Research spans medical analytics, social network analysis and blockchain applications using ML and data science
- Author of Data Structures and Algorithms in Python (Wiley, Indian Edition), strengthening algorithmic foundations
- Published 40+ peer-reviewed papers in reputed journals, conferences and edited volumes
- Strong background in software testing and reliability, enabling robust, production-ready AI systems
Note: The program is designed with inputs from academic and industry experts; however, the experts involved in its design may not necessarily participate in course delivery.
Sample certificate
Frequently asked questions
Fee structure
Total program fee
INR 96,000 +GST
Includes booking fee of INR 12,500
(Non-refundable)
Interest-free EMI
INR 16,422
(Six-month easy EMI)
The exercises designed as part of the program require the use of AWS Cloud Services such as GPU, compute, storage, virtual machines, and related cloud resources. Such usage costs are not included in the program fee, and the Institute does not provide free AWS credits. Leaners have to manage their AWS accounts and bear the cost for the same. Usage & cost details
Build a stronger foundation in Python, AWS and Mathematics with our Bridge Program at INR 25,000 + GST. Click here to learn more.
The most asked questions
BITS Pilani Digital is the Digital Learning Division of BITS Pilani, one of India’s most respected and future-driven institutions. It offers a range of rigorous, industry-aligned upskilling programs for technology professionals who want to stay at the forefront of innovation and continuously grow with the evolving digital world.
By combining BITS Pilani’s academic excellence with hands-on, practice-oriented learning, BITS Pilani Digital enables professionals to strengthen their expertise, advance their careers, and stay future-ready — without stepping away from their current roles.
The Professional Certificate in AI Engineering and MLOps is built for technology professionals who want to design and deploy real, production-like AI systems. It has focus on practical, industry-aligned learning, enabling professionals to learn the complete AI lifecycle with confidence.
Following are the distinctive features of this program:
- Learn the End-to-End AI Lifecycle: Learn how AI systems move from problem definition and data preparation to deployment, monitoring, and continuous improvement.
- Deploy on Enterprise MLOps Stack: Gain hands-on experience with industry-relevant AI engineering and MLOps technologies used to deploy and manage AI in production environments.
- Build an Industry like Capstone: Complete an industry-aligned capstone project that demonstrates your ability to deliver production-like AI solutions.
- Mentorship from Industry Experts: Learn from practising industry experts who bring both academic rigor and real-world implementation experience.
- Learn from industry professionals: Learn from experts who actively build AI systems
End-to-End Coverage: From AI development and deployment to monitoring, optimization, and continuous improvement of production-grade AI systems.
This program is best suited for:
- Software Developers working in the industry and aspiring to build AI products and applications.
- Professionals seeking to transition into roles such as AI Engineer, MLOps Engineer, Full Stack AI Developer, or AI Product Engineer.
- While the program is open to all eligible applicants, it is best suited for professionals with two or more years of work experience in software development.
Applicants are expected to have string proficiency in Python, AWS and Mathematics. While any graduate meeting the eligibility criteria can apply, those with little or no prior exposure to programming may find some courses challenging and may take this up at their own will.
To support such learners, BITS Pilani Digital offers an optional 8-week Python, AWS and Mathematics bridge program focused on building essential computational and coding skills required for success in the AI Engineering & MLOps program.
Eligible applicants can either join directly or first complete the Python Preparedness Programme before enrolling in the AI Engineering & MLOps program.
The program runs for approximately ~36 weeks. It comprises 6 modules + 1 Capstone Project, delivered in a linear sequence, with each module building upon the previous one.
Weekly learning structure:
- ~1 learning hours of pre-recorded video content
- 2 hour of live instructor-led session for deeper insights and discussions
Learners may require an estimated 9-10 hours per week of investment for total learning engagement, optimized for technology professionals who can pursue this program along with their jobs.
Tools may include MLflow, Docker, AWS Sagemaker, AWS Glue, S3, faiss-cpu
Yes. You'll develop and deploy a complete AI system through progressive modules during the capstone.
No. While the focus of the program is primarily the entire End-to-End AI Engineering stack along with MLOps, it introduces Generative AI, LLMs, and their place in the AI stack.
Yes. Strong foundation in programming in python, AWS and Mathematics and 2-5 years of software development experience.
Learning at BITS Pilani Digital combines academic rigor with expert-led, industry insights.. The program is 100% online and follows a flipped classroom model, integrating self-paced digital learning experiences with live weekend sessions, interactive discussions, and collaborative work.
Delivery is anchored by industry leaders, supported by exercises demonstrated in cloud-based environments using real-world tools and workflows. Active forums and mentor interactions ensure continuous guidance.
Break is possible and allowed only once as part of this program. If you take a break, you will be moved to the next available cohort at no extra cost. The program is structured and the workload is designed to enable you to complete the program at one stretch without taking breaks and continuity is encouraged to match the modular schedule. Please note: that your continuity after break is subject to availability of the next cohort which is decided as per the discretion of the institute.
No traditional exams. Evaluation is through quizzes per module quiz and a final capstone.
Evaluation typically focuses on: Completing the Quizzes and Capstone. The philosophy is simple: you’re graded by what you build, not what you memorize
Successful learners will receive a certificate of completion titled - Professional Certificate in AI Engineering and MLOps.
Successful completion of the certificate program would require participation in all quizzes and completion of the capstone project with a minimum “fair” grade.
The Transcript will contain the list of modules and the Capstone project title with non letter grades.
The primary focus of BITS Pilani Digital is to make every learner industry-ready through a combination of rigorous, industry-aligned curriculum, capstone project, and mentorship from experienced professionals. This learning methodology is designed to build deep, career-relevant skills that empower professionals to progress confidently in their chosen domain.
To complement this, BITS Pilani Digital offers career enablement support, including resume guidance, career mentorship, and curated opportunities from its industry partner network. These opportunities, however, are not guaranteed and depend on several factors such as market conditions, learner performance, and individual career aspirations.
Learners are encouraged to take ownership of their career journey, actively leverage the program’s learning experiences, and pursue roles aligned with their skills and goals.
Both options are valuable , the right choice depends on your career goals and learning objectives. BITS Pilani Digital`s degree programs offer a comprehensive academic foundation, deeper specialization pathways, and a broader progression toward advanced roles or higher education.
The Professional Certificate Program, on the other hand, is designed for technology professionals seeking a focused, intensive, and outcome-oriented learning experience. It enables you to gain deployment-ready expertise, mentored by industry experts, and apply these skills directly to real-world scenarios.
If your goal is to build advanced, applied capabilities and accelerate your career growth in a structured approximately 8-9 months format without the longer duration of a degree this program is an ideal choice.
Experiential learning is at the heart of every program at BITS Pilani Digital. All labs are designed to help learners translate concepts into real-world applications using industry-like datasets, tools, and cloud environments. You’ll gain hands-on experience across every stage, from deployment and monitoring to optimization and troubleshooting guided by industry mentors who ensure that every exercise reflects real professional challenges. This immersive, applied learning approach ensures that you don’t just learn the technology — you practice and implement it.
Program fees include access to all learning modules, mentorship sessions, and evaluation support.
Flexible payment options are available, and detailed fee information can be found on the BITS Pilani Digital Program page.
While the demonstration makes use of Python notebooks for conceptual understanding of the concepts, the nature of this program is such that enterprise cloud use is required and is learner-funded. BITS Pilani Digital will not have any AWS credits
Yes. The program is specifically designed for technology professionals and follows a flexible, part-time learning structure that allows you to balance work and study effectively.
Each week includes:
- ~1 hours of pre-recorded content per week, expert-led digital learning modules
- ~2 hour of live instructor-led sessions for deeper insights and discussions
In total, you can expect around 9–10 hours that the learner has to dedicate per week, thoughtfully optimized for working professionals who wish to upskill without taking a career break.
In this program, we have placed strong emphasis on the deployment, implementation and full‐lifecycle of AI Engineering pipeline
How much “time” / “hands-on” you should expect
- The program runs approximately 36 weeks (≈ 8.5-9 months) with ~9-10 hours per week of learner investment for working professionals.
- Importantly: the program incorporates “significant practical learning”. Every module includes extensive lab demonstrations.
- Finally, you can focus your capstone Project on the Deployment and MLOps aspects where you will complete a comprehensive capstone executed as a course.
Given below are broad usage and cost estimates for learners pursuing the Professional Certificate in AI Engineering and MLOps. Actual costs may vary based on cloud provider, region, GPU type, usage pattern, and how efficiently learners manage their resources.
Medium usage (regular experiments and training; ~15 GPU hrs/week)
Estimated total: ₹16,000 – ₹34,000 for the full 9-month course.
Intensive usage (heavy experimentation; many training runs; ~40 GPU hrs/week)
Estimated total: ₹25,000 – ₹50,000 for the full 9-month course.
These broad estimates include GPU compute, a modest persistent disk, small CPU VM time for development, egress, and a buffer for miscellaneous services.
Practical ways to keep costs low
- Switch off or delete VMs whenever not in use.
- Use preemptible / spot GPUs whenever possible — typically 30–80% cheaper — ideal for experiments and long training runs (checkpoint frequently).
- Start with managed notebooks and free tiers — e.g., Google Colab (free) or Colab Pro — which can be the most cost-effective option for many learners.
- Schedule heavy training outside peak times; use smaller batch sizes or mixed precision to reduce GPU hours.
- Use small persistent disks (50–100 GB) and store large datasets in cheaper cloud object storage; delete heavy VMs once finished.
- Where feasible, keep persistent data on your local machine rather than in the cloud to avoid storage and egress costs.