DBA
Education
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Data Science and Analytics
Machine Learning and AI
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Accounting and Finance
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Earn recognised credentials and academic recognition.
Top 10 percentile performers in each cohort receive a Certificate with Distinction, recognised on the credential itself.
Executive Post Graduate Certificate in Applied AI & Machine Learning
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TypePG Certificate
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Start DateAugust 31, 2026
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Duration8 Months
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- #215 globally in the QS World University Rankings 2026
- #5 Engineering in India (NIRF)
From Foundations to Gen AI & Agentic AI led by IIT Kharagpur’s Artificial Intelligence Department
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100% Live Learning
All sessions delivered live by IIT Kharagpur faculty, ensuring depth, clarity, and academic rigour throughout the programme.
100% Faculty Led Learning
End to End learning led by professors from the Department of Artificial Intelligence.
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6 Core Modules. 6 Real-World AI Systems
Every module includes a guided, hands-on project to help you apply concepts immediately and build confidence step by step.
Foundations to GenAI, Agentic AI & Deployment
AI Foundations Bridge → ML & Deep Learning → NLP & Transformers → GenAI → Agentic AI → RAG → Deployment & MLOps
Industry-Aligned Capstone & Projects
End-to-end - 6 projects & 1 Capstone under faculty mentorship, from problem definition to deployed solution.
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Executive Certificate & Campus Recognition
On-Campus Graduation Ceremony - Celebrate your achievement in India’s first IIT’s iconic legacy.
An End-to-End AI Engineering programme: The Full-Stack AI Engineering Curriculum
AI Foundations Bridge
A structured bridge module designed to prepare learners for the core AI curriculum. Taught with clarity and intuition to ensure every learner starts the programme confident, aligned, and ready.
AI from First Principles
Machine Learning and Deep Learning taught with a focus on how and why models work, not just how to apply libraries.
Production-First Curriculum Design
Every concept is taught with real-world deployment constraints in mind – including scalability, reliability, cost, and monitoring.
GenAI & Agentic AI Integrated, Not Overlaid
Generative AI & Agentic AI is embedded naturally into the curriculum as an engineering capability, not treated as a standalone or hype-driven track.
Enterprise-Grade Deployment & MLOps
Deploy, monitor, and operate AI systems using industry-grade practices.
End-to-End AI Engineering Curriculum
Covers Machine Learning, Deep Learning, GenAI, Agentic AI, RAG systems, and MLOps.
Programme Faculty
Whom will you learn from?
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Instructors
Prof. Plaban Bhowmick
Associate Professor, Dept. of AI
Research Areas
Artificial Intelligence, Natural Language Processing, Digital Library, Machine learning
Artificial Intelligence, Natural Language Processing, Digital Library, Machine learning
Prof. Jiaul Hoque Paik
Associate Professor, Dept. of AI
Research Areas
Natural Language Processing, Information Retrieval, Big Data Analytics, Artificial Intelligence, Machine learning
Natural Language Processing, Information Retrieval, Big Data Analytics, Artificial Intelligence, Machine learning
Prof. Somdyuti Paul
Assistant Professor, Dept. of AI, IIT Kharagpur
Research Areas
Video Processing, Computer Vision
Video Processing, Computer Vision
Prof. Niloy Ganguly
Professor & Head, Dept. of CSE
Research Areas
Artificial Intelligence and Machine Learning, Complex andSocial Networks, Data and Web Mining, Natural Language Processing
Artificial Intelligence and Machine Learning, Complex andSocial Networks, Data and Web Mining, Natural Language Processing
Prof. Sourangshu Bhattacharya
Lead Faculty, Associate Professor, Department of Computer Science & Engineering, IIT Kharagpur
Research Areas
Artificial Intelligence and Machine Learning, Complex and Social Networks, Data and Web Mining
Artificial Intelligence and Machine Learning, Complex and Social Networks, Data and Web Mining
Prof. Pawan Goyal
Associate Professor, Dept. of AI
Research Areas
Complex and Social Networks, Data and Web Mining, Communication Medium and Technologies: Language, Speech and HCI
Complex and Social Networks, Data and Web Mining, Communication Medium and Technologies: Language, Speech and HCI
Prof. Koustav Rudra
Assistant Professor, Dept. of AI
Research Areas
Responsible AI, AI for Social Good, AI and ML in healthcare, Information Retrieval. Natural Language Processing
Responsible AI, AI for Social Good, AI and ML in healthcare, Information Retrieval. Natural Language Processing
The Complete Curriculum
Your End-to-End Journey to Becoming an Enterprise-Grade AI Engineer
Build a strong foundation to succeed in advanced AI topics - designed to align learners from mixed backgrounds.
Topics Covered:
- Python
- SQL
- Statistics
- Linear Algebra
- Probability
- Calculus
Topic Covered:
- Understand core ML concepts including data preprocessing, model evaluation, supervised and unsupervised learning, and classical algorithms.
- Design ML solutions with clarity and correctness.
- Data analysis, pre-processing and visualization, ML workflow, cross - validation, error types and performance metrics.
- Supervised learning: linear and logistic regression.
- Supervised Learning: Decision trees and support vector machines.
- Ensemble methods: Bagging and random forests, adaptive boosting and gradient boosting.
- Unsupervised learning: K-means clustering and PCA.
Topic Covered:
- Learn neural networks, optimization, CNNs, RNNs, and transfer learning.
- Build deep learning models and understand how they scale in real-world applications.
- Feedforward neural networks and backpropagation algorithm.
- Gradient based optimizers and regularization for neural networks.
- Convolutional neural networks.
- Recurrent neural networks.
- Transfer learning and deployment.
Topic Covered:
- Understand how modern language and speech systems work — from tokenization to transformer architectures.
- Build NLP and speech-based AI applications.
- Text preprocessing and representation.
- Attention mechanism and Transformer.
- Transformer architecture variants: Tokenization schemes, encoder-only variants, decoder-only variants.
- Speech/Audio representations, Automatic Speech Recognition (ASR), Text-to-Speech, Voice Cloning.
Topic Covered:
- Build NLP and speech-based AI applications.
- Text preprocessing and representation.
- Attention mechanism and Transformer.
- Transformer architecture variants: Tokenization schemes, encoder-only variants, decoder-only variants.
- Speech/Audio representations, Automatic Speech Recognition (ASR), Text-to-Speech, Voice Cloning.
Topic Covered:
- Design and build retrieval-augmented systems using vector search, orchestration frameworks, and evaluation techniques.
- Move beyond demos to production-ready GenAI systems.
- Foundations of RAG & Vector Search.
- LangChain and RAG Orchestration.
- Advanced RAG Techniques and System Design Issues.
- Evaluation, Debugging & Optimization.
Topic Covered
- Agentic AI: Foundations, Architecture Patterns, and Orchestration Frameworks.
- MLOps for Agentic Systems: Containerisation, Deployment Infrastructure, and CI/CD for Agent Pipelines.
- Agent Observability and Reliability: Tracing, Behavioural Regression, and Production Monitoring.
- Responsible Agentic AI: Risk Frameworks, Guardrails, and Human-in-the-Loop Governance.
Topics Covered:
- Design, build, deploy, and evaluate an end-to-end AI system integrating ML, GenAI, Agentic AI, RAG, and MLOps.
- Graduate with a portfolio-ready system demonstrating enterprise-grade capability.
- Your signature end-to-end build: designed, built, evaluated, and deployed with faculty mentorship.
- Deliver a production-grade AI solution with operational readiness for real deployment. Ideation begins in Module 5.
What You Will Build: Portfolio of real AI systems you can demonstrate, explain, and extend.
END-TO-END ML SYSTEM
A complete machine learning system covering data preparation, model training, evaluation, and deployment.
DEPLOYED DEEP LEARNING MODEL
A deep learning model (vision or sequence-based) trained, optimised, and deployed as a usable service.
PRODUCTION-GRADE RAG SYSTEM
A retrieval-augmented AI system using vector search and orchestration.
GENAI & AGENTIC AI APPLICATION WITH LLM ADAPTATION
A Generative and Agentic AI application using prompting, lightweight fine-tuning, and agent-based workflows.
DEPLOYED AI API
A containerised AI service exposed via APIs. Monitored, versioned, and ready to handle real-world traffic.
INDUSTRY CAPSTONE PROJECT
Your signature project – a complete AI system built end-to-end, from problem definition to deployed solution.
Capstone
Build in Your Domain. Deploy to the Real World
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Choose a real-world challenge across Healthcare, BFSI, Manufacturing, or related domains.
Build a complete, production-ready AI system. From architecture to deployment and monitoring, you’ll engineer and launch an end-to-end solution that showcases true enterprise-grade AI capability.
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Domain Focused - Industry Problem Driven -
Production – Deployment Ready
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Full-Stack - ML + GenAI + Agentic AI + RAG
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Measured - Evaluated & Benchmark Driven
Beyond a Certificate — Built for Career Impact
On-Campus Graduation Ceremony at IIT Kharagpur
The programme concludes with an on-campus award ceremony at IIT Kharagpur, where participants receive their certificates from the Programme Director and Institute leadership.
Our Admission Process
Complete your application and enrol in the program with four easy steps!
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Eligibility
Graduation with a minimum of 50% marks. B.Tech/ M. Tech, B.E/M.E (CS, IT, AI, ECE preferred), B.Sc/M.Sc (CS/Mathematics/Statistics), MCA/BCA. Candidates from other disciplines must have a minimum of 2 years of experience in the technology field.
Complete the Application
Fill your details and complete your application
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Receive the Offer Letter
Get shortlisted and receive Provisional Offer Letter
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Reserve your Seat
Block your seat
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Pay the Block Amount
Post verification, complete the balance payment to confirm enrolment
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Learner Support
Available from 9 AM to 8 PM GMT (Monday - Friday)
Phone Number
Mail us
*All telephone calls will be recorded for training and quality purposes.
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By proceeding, you agree to receive communication from and on behalf of Golden Gate University and upGrad (or its affiliates) about this program and other relevant programs.
*If we are unavailable to attend to your call, it is deemed that we have your consent to contact you in response.
By proceeding, you agree to receive communication from and on behalf of Golden Gate University and upGrad (or its affiliates) about this program and other relevant programs.
