Build production-grade AI systems from data pipelines and model training to Large Language Models, Retrieval-Augmented Generation (RAG), agentic workflows, and deployable APIs. Master the complete AI engineering lifecycle using enterprise-ready tools and frameworks.
Industry-Grade AI Technologies You'll Master
Choose a specialist track or complete the full AI Engineering program to build production-ready AI systems from machine learning to enterprise AI deployment.
Build robust machine learning pipelines with data analysis, feature engineering, supervised and unsupervised learning.
Master neural architectures, TensorFlow, PyTorch, computer vision, object detection, and speech models.
Learn LLMs, prompt engineering, OpenAI APIs, LoRA fine-tuning, and enterprise AI application development.
Build production AI systems using RAG, AI agents, vector databases, FastAPI deployment, and MLOps.
Four specialized tracks designed to bridge the gap between mechanical engineering, embedded systems, and artificial intelligence.
Build a complete machine learning solution that predicts customer churn using data preprocessing, feature engineering, model training, evaluation, and deployment.
Develop a deep learning application capable of detecting and classifying real-world objects using CNNs and YOLO models.
Build a production-ready AI assistant using Retrieval-Augmented Generation (RAG), vector databases, LangChain, and OpenAI/Hugging Face models with document search, memory, and multi-agent workflows.
Deploy a scalable AI application with automated CI/CD pipelines, cloud infrastructure, monitoring, model versioning, and production-grade APIs.
Master the most in-demand AI, Machine Learning, Generative AI, and Cloud technologies used by leading organizations worldwide.
A structured learning journey from programming fundamentals to production-ready AI applications.
Python & Machine Learning →
Learn Python programming, data analysis, visualization, and build your first machine learning models.
Deliverable:ML Prediction Project
Deep Learning & Computer Vision →
Build neural networks, CNN models, object detection systems, and deploy AI vision applications.
Deliverable:ML Prediction Project
Generative AI & AI Agents →
Master LLMs, Prompt Engineering, Retrieval-Augmented Generation (RAG), and AI Agent development.
Deliverable:Enterprise AI Assistant
AI Deployment & MLOps →
Deploy AI applications with Docker, Kubernetes, cloud platforms, CI/CD, and production monitoring.
Deliverable:Production AI PlatformWatch aspiring developers transform into production-ready AI Engineers with industry projects, real-world experience, and modern AI technologies.
Limited understanding of AI, Machine Learning, and modern development tools.
Mostly theoretical learning without building production-grade AI applications.
Little experience with cloud deployment, AI agents, or enterprise workflows.
Build intelligent AI applications using Python, Machine Learning, and Deep Learning.
Develop AI Assistants, RAG applications, LLMs, and AI Agents for real-world businesses.
10+ production-ready AI projects showcasing your expertise to employers.
Join thousands of learners building careers in Artificial Intelligence, Machine Learning, and Generative AI.
Develop production-ready AI solutions that showcase your expertise to employers.
Description here.
Seamlessly blend online theoretical depth with offline real-world practicals. Build and deploy intelligent AI systems with hands-on exposure to machine learning models, LLM integration, live agent projects, and internship opportunities.
Live sessions paired with in-lab AI system practicals.
Work with ML models, LLM APIs, and live intelligent agent projects.
Apply your skills with real AI engineering teams.
Real stories from professionals who transformed their careers with Artificial Intelligence.
"The AI Engineering Program completely changed my career trajectory. I went from a junior software developer to leading a team of 5 AI engineers at a Series-B startup — with a 180% salary increase in just 8 months after graduation."
Senior AI Engineer
@ Microsoft
"The Python and Scikit-learn modules were exactly what I needed."
@ IBM
"The PyTorch modules were production-grade. Now architecting computer vision systems."
@ NVIDIA
"I went from writing basic prompts in week 4 to deploying LangChain agents by week 14."
@ OpenAI
"Came from pure web dev. Now I'm an AI engineer at Amazon AWS!"
@ Amazon AWS
"The MLflow and Docker modules were a game-changer for shipping models to production."
"Mechanical engineer here. Now an AI Engineer at Accenture."
@ Accenture
Flexible learning paths tailored to your career milestones. Select the track that fits your background.
Total INR 59,160* (Inclusive of taxes)
*Estimates based on market placement reports. Individual outcomes may vary.
Your certification formally validates your skill set in recruiter searches.
Unique cryptographic hashes registered on global validation boards.
Add directly to your credentials panel with pre-filled ID tracking.
Your name will be printed exactly like this on your official Pantech certificate.
Track 01 • Electric Vehicles
Learn EV powertrain design, battery management systems, motor control, and charging infrastructure fundamentals.
Track 02 • Computer Vision
Develop image processing pipelines, object detection models, and intelligent perception systems using deep learning frameworks.
Track 03 • ASIC RTL
Master chip-level RTL design, synthesis, and verification methodologies used in real-world ASIC development flows.
Artificial Intelligence is revolutionizing every industry. Discover where your AI expertise can create the biggest impact.
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Develop AI-powered solutions for medical imaging, disease prediction, diagnostics and personalized healthcare.
40% Growth
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Build AI systems for fraud detection, credit scoring, algorithmic trading, financial forecasting and customer analytics.
$50B Market
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Develop predictive maintenance, computer vision quality inspection, and AI-powered industrial automation.
30% Productivity
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Create enterprise AI assistants, LLM applications, Retrieval-Augmented Generation (RAG) systems and autonomous AI agents.
Fastest GrowingNo prior AI experience is required. Basic computer knowledge is sufficient, and we begin with Python fundamentals before moving into Machine Learning and AI concepts.
You'll work with Python, TensorFlow, PyTorch, OpenAI API, Hugging Face, LangChain, Docker, Kubernetes, FastAPI, and modern cloud AI platforms.
Yes. You'll build production-ready Machine Learning models, Computer Vision applications, AI Assistants, RAG systems, AI Agents, and cloud-deployed AI solutions.
Absolutely. The curriculum covers Prompt Engineering, LLMs, Fine-Tuning, Retrieval-Augmented Generation (RAG), AI Agents, and enterprise AI development.
Yes. Our career services include resume preparation, LinkedIn optimization, mock interviews, portfolio reviews, career mentoring, and hiring partner referrals.
Yes. Flexible weekday and weekend learning options, recorded sessions, and mentor support make the program ideal for working professionals.
Graduates can pursue roles such as AI Engineer, Machine Learning Engineer, Data Scientist, Computer Vision Engineer, NLP Engineer, MLOps Engineer, and Generative AI Developer.
Yes. After successfully completing the program and capstone projects, you'll receive an industry-recognized AI Engineering certification that validates your practical skills.
Transform your skills into industry-ready AI Engineering & Intelligent Systems expertise. Learn Machine Learning, Deep Learning, LLM APIs, RAG & Vector Databases, Python, PyTorch, MLOps, and Intelligent Agent Design through hands-on industry projects.
