Artificial Intelligence

Certified Professional in AI Engineering

Companies are scrambling for engineers who can build, not just theorize. The Certified Professional in AI Engineering is an intensive program designed to take you from a standard developer to an AI specialist. Whether you are a fresh graduate or a professional looking to switch domains, this program bridges the gap between basic Python scripting and building autonomous, large-scale AI applications. You won’t just learn about AI; you will build agents, Retrieval Augmented Generation (RAG) systems, and multimodal apps that solve real-world problems.

20 hours 15 min

6 Modules

Intermediate

₹1,00,000₹2,00,00050% OFF

Course Curriculum

Week 1: Advanced System Architecture & High-Dimensional Logic

5 Lessons

1.1: From Microservices to Compound AI Systems

1.2: Probabilistic Engineering & Error Budgets

1.3: Distributed AI Pipelines & Kernel-Level Optimization

1.4: The Enterprise Utility Calculus

1.5: Deconstructing Production Outages

Week 2: Data Engineering & Vectorized Intelligence at Scale

5 Lessons

2.1: High-Performance ETL for Unstructured Data

2.2: Advanced Chunking & Multi-Modal Embedding Strategies

2.3: Vector Database Internals & Indexing

2.4: Semantic Versioning for Datasets

2.5: Retrieval-Augmented Generation (RAG) Optimization

Week 3: Deep Model Mechanics & Performance Tuning

5 Lessons

3.1: Transformer Internals for Architects

3.2: Quantization & Model Distillation Logic

3.3: PEFT & LoRA Engineering

3.4: Hardware-Aware Inference

3.5: Model Governance & Benchmarking Frameworks

Week 4: Enterprise Production & MLOps 2.0

5 Lessons

4.1: LLM-Specific CI/CD Pipelines

4.2: Advanced Observability & Semantic Monitoring

4.3: Hardened Guardrail Architectures

4.4: Adversarial Red-Teaming

4.5: Strategic Fallback & Circuit Breaker Design

Week 5: Agentic Systems & Autonomous Reasoning

5 Lessons

5.1: Agentic Cognitive Architectures

5.2: Multi-Agent Systems & Orchestration

5.3: Tool-Use & API-Interaction Patterns

5.4: Long-Term Memory & Stateful Agents

5.5: Benchmarking Agentic Performance

Week 6: The Future of AI Infrastructure & Frontier Research

5 Lessons

6.1: Frontier Architectures (State Space Models & Beyond)

6.2: Mixture-of-Experts (MoE) Scaling

6.3: Large World Models (LWM) & Multi-Modal Tokenization

6.4: Neuro-Symbolic Integration

6.5: Ethical AI & The Alignment Problem

Ready to start?

Join users mastering these skills today.