PROFESSIONAL CERTIFICATE IN ARTIFICIAL INTELLIGENCE
- Industry-recognized Professional Certificate Program in AI
- Hands-on training in Deep Learning, Generative AI & Agentic AI
- 6 modules + 4 production-grade AI projects
- Live deployment labs: PyTorch, TensorFlow, LangChain
- MLOps and production AI systems training
- Mentorship from AI researchers and ML engineers
- AI/ML Engineer placement pipeline
- Transformers, RAG systems, autonomous agents
Professional Certificate in Artificial Intelligence
Gain hands-on AI experience through real-world projects, tools, and expert mentorship.
The Professional Certificate in Artificial Intelligence is an industry-driven program designed to help learners build a solid foundation in AI, machine learning, and deep learning.The comprehensive curriculum emphasizes practical learning through real-world projects, equipping participants with the ability to design, train, and deploy intelligent systems. This program is ideal for students, professionals, and career changers seeking to enter or advance in the fast-growing AI domain.
Regular Program
6 MonthsComprehensive AI foundation with 6 modules + 4 enterprise projects
Specialization
3 MonthsAdvanced Deep Learning, Generative AI, MLOps, and Agentic AI mastery
Placement Activity
6 MonthsAI/ML Engineer and Data Scientist career acceleration pipeline
Program Curriculum
6 core modules + 4 production AI projects across 6 months.
Core Modules
Six foundational courses for enterprise AI expertise.
Comprehensive introduction to AI paradigms, symbolic reasoning, machine learning, probabilistic inference, search strategies, and knowledge representation.
Python proficiency for AI development with algorithm design, data structures, OOP, and core AI libraries implementation.
Statistical analysis, exploratory data analysis, data preprocessing, feature engineering, and model evaluation for AI pipelines.
Ethical frameworks, data privacy, algorithmic fairness, transparency, bias mitigation, and regulatory compliance for responsible AI.
End-to-end AI system engineering, MLOps, model deployment, performance monitoring, scalability, and reliability engineering.
Autonomous agent architectures, reinforcement learning, RPA, conversational agents, and enterprise automation systems.
Production AI Projects
4 enterprise-grade projects for ML engineer portfolio.
Supervised Machine Learning Pipeline
End-to-end ML pipeline with data preprocessing, model training, hyperparameter tuning, and production deployment.
NLP Transformer Model Deployment
Build and deploy transformer-based NLP model (BERT/GPT) with real-time inference capabilities.
Computer Vision Object Detection
YOLO/SSD object detection system with custom dataset training and edge deployment.
Intelligent Agent Automation System
Multi-agent reinforcement learning system for enterprise process automation and optimization.
The Artificial Intelligence Landscape
Designed to launch your career as ML Engineer in production AI systems.
Comprehensive Curriculum
Job-aligned curriculum designed by AI researchers.
120+ Learning Hours
Live sessions, labs, mentoring with AI experts.
12+ Production Projects
Deployed models using real enterprise datasets.
95% Placement Success
Learners transition to ML Engineer roles.
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.
Program Highlights
Enterprise AI benefits from joining this professional program.
Production AI Program
- 6-Month accelerated AI training
- Live model deployment labs
- PyTorch/TensorFlow mastery
Enterprise AI Stack
- Transformers, LangChain, MLOps
- Production deployment patterns
- Agentic AI systems
AI Researcher Mentorship
- PhD-level AI instruction
- 1:1 project guidance
- Live debugging sessions
ML Engineer Pipeline
- Deployed model portfolio
- Kaggle competition prep
- AI/ML placement support
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.
