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Analyze & Deploy Scalable LLM Architectures

Analyze & Deploy Scalable LLM Architectures is an intermediate course for ML engineers and AI practitioners tasked with moving large language model (LLM) prototypes into production. Many powerful models fail under real-world load due to architectural flaws. This course teaches you to prevent that. You will learn to analyze multi-stage architectures such as RAG to diagnose and quantify performance bottlenecks with evidence, not assumptions. You will then master the tools of production-grade operations, designing and writing declarative Helm charts to deploy containerized LLM applications on Kubernetes. The curriculum focuses on building resilient, scalable systems by implementing Horizontal Pod Autoscaling (HPA) to handle unpredictable traffic and managing the full deployment lifecycle with controlled rollouts and rapid rollbacks. By the end of this course, you will be able to transform fragile prototypes into robust, reliable, and scalable production services.
Duration 6 Months
Institution Coursera
Format Online

Eligibility Criteria

school

Academic Foundation

A recognized Bachelor’s degree or high school equivalent required for admission into Coursera.

language

Language Proficiency

English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.

Detailed Fees Breakdown

Base Tuition Fee $143
Total Est. Investment $143

Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.

Academic Trajectory

Program Outcome

Graduates of the Analyze & Deploy Scalable LLM Architectures program at Coursera are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.

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