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Everything you need to elevate your skills.

Comprehensive training programs covering the latest technologies and best practices used by top tech companies.

Advanced

$199

AI Engineering with Model Context Protocol (MCP)

Master the Model Context Protocol (MCP) — the emerging standard that lets LLMs talk to your tools, APIs, databases, and services. Built by engineers, for engineers: this advanced course goes deep on MCP server architecture, building custom MCP integrations, connecting AI agents to real-world systems, and securing MCP endpoints in production. You'll design and deploy MCP servers from scratch, wire them into agentic pipelines, and instrument them for observability. If you're building products on top of LLMs in 2026, MCP is no longer optional — it's the connective tissue of the agentic AI stack.

2 weeks

What Is MCP and Why It Changes EverythingMCP Architecture: Servers, Clients, and Transport Layers+2

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Advanced

$189

Agentic AI Engineering: Build Autonomous Systems

Master the engineering discipline behind autonomous AI agents. Built by engineers who have shipped agentic systems in production, this advanced course takes you from LLM fundamentals to multi-agent orchestration, RAG pipelines, tool-use patterns, and reliability engineering for probabilistic systems. You will design and implement agents using LangChain, LangGraph, and the Model Context Protocol (MCP), integrate vector databases for retrieval-augmented generation, and build evaluation harnesses to measure agent performance. Real-world projects include a code-review agent, a data-analysis copilot, and a multi-agent customer support pipeline. Ideal for software engineers who already write Python and want to engineer AI — not just use it.

2 weeks

Foundations: LLMs, Tokens, and the Agentic ParadigmPrompt Engineering and Structured Outputs+2

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Intermediate

$149

Cloud Engineering on AWS

Master cloud engineering on AWS with a curriculum built by working engineers — not slides-and-theory instructors. This intermediate course goes beyond the basics: you'll architect, deploy, and operate production-grade infrastructure using core AWS services including EC2, S3, RDS, VPC, IAM, Lambda, ECS, and CloudFormation. Every module is grounded in real engineering decisions: capacity planning, cost optimization, high availability design, and least-privilege security. By the end, you'll have hands-on experience building a multi-tier, resilient AWS architecture from scratch — the kind of practical fluency that AWS certification prep alone won't give you. Ideal for backend engineers, DevOps practitioners, and software developers looking to own their cloud layer with confidence.

3 weeks

AWS Core Concepts and the Shared Responsibility ModelIAM: Users, Roles, Policies, and Security Best Practices+2

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Beginner

$49

Introduction to Cloud Computing

Launch your cloud career with this hands-on beginner course built by working engineers. You'll go from zero cloud knowledge to confidently deploying real workloads on AWS. Covering the fundamental building blocks — compute, storage, networking, databases, and IAM — this course gives you the practical vocabulary, mental models, and labs that employers actually test for. No prior cloud experience required. By the end, you'll understand how cloud infrastructure works under the hood, why it matters, and how to navigate AWS with confidence. Ideal for developers moving into cloud roles, backend engineers wanting to understand their production environment, and anyone targeting an AWS Cloud Practitioner certification.

1 week

What Is Cloud Computing? Mental Models & Core ConceptsAWS Global Infrastructure: Regions, AZs, and Edge Locations+2

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Intermediate

$149

LLM Engineering for Developers

Master the engineering fundamentals of large language models and build production-ready LLM-powered applications. This course is designed for practicing software engineers who want to go beyond prompt engineering and into real LLM systems: retrieval-augmented generation (RAG), function calling, fine-tuning workflows, vector databases, and multi-model orchestration. You'll learn to evaluate LLM outputs, handle failures in probabilistic systems, manage latency and cost, and deploy LLM APIs at scale. Hands-on labs use OpenAI, Anthropic, and open-source models via LangChain and LlamaIndex. Ideal for backend, full-stack, and ML-adjacent engineers building AI features into products.

2 weeks

How LLMs Work: Architecture and Inference FundamentalsPrompt Engineering Done Right: Techniques and Pitfalls+2

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Advanced

$179

System Design for Engineers

System design is the skill that separates senior engineers from the rest. This advanced course teaches you how to architect systems that scale to millions of users — not through academic diagrams, but through the real trade-offs and decisions engineers make at companies like Stripe, Uber, and Cloudflare. Topics include: designing distributed databases and caching layers, building resilient event-driven architectures with Kafka, API gateway and service mesh patterns, rate limiting and idempotency, CAP theorem in practice, and how to run a system design interview at a FAANG-level bar. Whether you're preparing for senior engineering interviews or leveling up your architectural thinking at work, this course gives you the frameworks and vocabulary to design systems that actually hold up under load.

2 weeks

Foundations: Scalability, Reliability and AvailabilityLoad Balancing and Reverse Proxies+2

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Custom learning plans for companies

Tailored training programs designed specifically for your engineering team. Perfect for startups and established companies looking to accelerate their team's growth.

Team Training

Customized courses aligned with your tech stack

Accelerated Learning

Fast-track your team's growth with intensive programs

Ongoing Support

Continuous learning and mentorship for your team

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