POST GRADUATE PROGRAM IN ARTIFICIAL INTELLIGENCE
- 12 Months Executive PGP Program (21 months total)
- 24 modules + 7 enterprise-grade AI projects
- Live research-grade AI labs: Transformers, GenAI, MLOps
- Enterprise AI: PyTorch, Ray, MLflow, Kubernetes ML
- Principal AI mentorship from PhDs & researchers
- AI/ML Architect leadership placement pipeline
- Sustainable AI innovation frameworks
- Boardroom-ready AI strategy deliverables
Post Graduate Program in Artificial Intelligence
Master advanced AI concepts, drive strategic innovation, and lead data-driven transformation across industries.
The Post Graduate Program (PGP) in Artificial Intelligence is an advanced,comprehensive program designed for professionals aiming to lead AI-driven innovation and transformation. Building upon the Professional Certificate in Artificial Intelligence, this program integrates advanced modules in machine learning, AI decision-making, sustainability, and emerging technologies. Learners will gain both technical depth and strategic insight into the design, deployment, and governance of modern AI systems.
Regular Program
12 MonthsComprehensive PGP curriculum with 24 modules + 7 enterprise AI projects across all AI domains
Specialization
3 MonthsResearch-grade AI: Transformers, GenAI, MLOps, Agentic Systems mastery
Placement Activity
6 MonthsExecutive career acceleration for senior AI/ML Architect roles
PGP Curriculum
24 modules + 7 enterprise AI projects across 12 months of executive AI training.
Module 1: AI Foundations & Data Science
Essential foundation in AI principles, programming, analytics, and responsible AI governance.
Conceptual & historical development of AI. Symbolic reasoning, probabilistic inference, search strategies, knowledge representation, foundational theories & contemporary applications.
Python mastery for AI systems. Algorithm design, data structures, OOP, core AI libraries, Git workflows, scalable software engineering for production AI solutions.
Statistics, EDA, preprocessing, feature engineering, model evaluation. Structured/unstructured data pipelines for enterprise AI decision-making systems.
Ethical frameworks, privacy, fairness, transparency, bias mitigation, regulatory compliance. Responsible AI governance models for enterprise deployment.
Module 2: AI Engineering & Machine Learning
Production AI systems engineering, intelligent automation, decision systems, and advanced ML mastery.
End-to-end AI engineering. MLOps, deployment, scalability, monitoring, testing frameworks, validation methods for production reliability.
Autonomous agents, reinforcement learning, RPA, conversational agents, decision systems, enterprise automation optimization architectures.
Decision sciences, predictive analytics, optimization, human-in-the-loop systems. Strategic business integration of AI insights and risk assessment.
Supervised/unsupervised/reinforcement learning. Linear models, ensembles, SVMs, neural networks, model tuning for production-grade systems.
Module 3: Emerging AI Technologies
Next-generation AI paradigms and sustainable innovation strategies.
Generative AI, federated learning, quantum AI, bio-inspired computing. Next-generation sustainable AI innovation and deployment strategies.
Enterprise Capstone Projects
7 executive-grade projects for AI/ML Architect portfolio.
Production ML Pipeline
End-to-end ML system with data engineering, model training, hyperparameter tuning, MLOps deployment & monitoring.
Transformer NLP Deployment
BERT/GPT model fine-tuning with real-time inference API, vector database integration, and production monitoring.
Computer Vision System
YOLO/SSD object detection with custom dataset training, edge deployment, and performance optimization.
Multi-Agent Automation
Enterprise RPA with reinforcement learning agents, process optimization, and human-in-the-loop validation.
AI Decision Dashboard
Executive analytics platform with predictive insights, real-time monitoring, and strategic decision support.
GenAI Content System
Production Stable Diffusion + RAG pipeline with prompt engineering, content moderation, and scalability.
Final PGP Capstone: AI Innovation Lab
Research-grade AI innovation project with sustainable impact, enterprise deployment, and C-level presentation.
Why AI PGP?
97M jobs, $120K+ salaries, 37.3% CAGR through 2030.
97 Million+
AI jobs by 2025 - World Economic Forum 2023
$1.8 Trillion
AI market by 2030 - Statista 2024
$120K+
AI/ML Engineer salary - Indeed 2024
37.3% CAGR
AI growth 2023-2030 - Fortune Business
Alumni Highlights
200+
Global Companies
$122K PA
Average CTC
$250K PA
Highest CTC
87%
Average Salary Hike
Benefits
Learn from leading academicians and several experienced industry practitioners from top organizations.
Personalised workshops based on your proficiency level to help you get on par.
Mix of Live Classes & Recorded lectures for your convenience.
24×7 Student Support, Quick doubt resolution by industry experts.
Executive PGP Highlights
Leadership benefits from the AI PGP program.
Executive PGP Program
- 12-Month leadership curriculum
- Live research-grade AI labs
- Principal AI mentorship
Research AI Standards
- Transformers, GenAI, MLOps coverage
- Enterprise tools: PyTorch, Ray, MLflow
- Real AI leadership case studies
Executive Mentorship
- AI PhD & Principal Engineer instructors
- 1:1 leadership coaching
- Executive mock interviews
Leadership Outcomes
- AI/ML Architect preparation
- Principal portfolio development
- Executive placement pipeline
Capstone Projects
Test your skills and mettle with a capstone project.
Election Outcome Prediction
Analyze historical election data to predict election outcomes and understand factors influencing voter behavior.
E-commerce
Techniques used: Text Mining, Kmeans Clustering, Regression Trees, XGBoost, Neural Network
Web & Social Media
Techniques used: Topic Modeling using Latent Dirichlet Allocation, K-Means & Hierarchical Clustering
Banking
Techniques used: Linear Discriminant Analysis, Logistic Regression, Neural Network, Boosting, Random Forest, CART
Supply Chain
Techniques used: Text Mining, Kmeans Clustering, Regression Trees, XGBoost, Neural Network
Healthcare
Techniques used: Logistic Regression, Random Tree, ADA Boost, Random Forest, KSVM
Retail
Techniques used: Market Basket Analysis, Brand Loyalty Analysis
Insurance
Techniques used: NLP (Natural Language Processing), Vector Space Model, Latent Semantic Analysis
Our Learners Work At
Leading companies that value data skills.
