IT & SoftwareAdded 1 days ago

Certified AI Engineer Masterclass: Build AI Agents 2026

Build real AI systems, LLM apps, RAG, agents & deploy on AWS — from beginner to advanced

2.6 / 5.0
5 ratings
12h 35m 25s
On-demand
English
Audio
Data Science Academy, School of AI
Instructor
Certified AI Engineer Masterclass: Build AI Agents 2026100% OFF
  • 12h 35m 25s on-demand video
  • Certificate of Completion
  • Mobile, TV & Desktop Access
  • Full Lifetime Access

What you'll learn

Build real-world AI applications using Large Language Models (GPT, Claude, etc.)
Master Prompt Engineering techniques (zero-shot, few-shot, structured outputs)
Develop AI Agents with memory, tools, and automation workflows
Implement Retrieval-Augmented Generation (RAG) using embeddings and vector databases
Integrate AI into applications using APIs (Python & JavaScript)
Design and build full-stack AI systems (frontend + backend)
Deploy AI applications using AWS, Docker, and modern DevOps practices
Optimize AI systems for cost, latency, and performance
Understand and mitigate AI risks, security issues, and bias

Course Description

“This course contains the use of artificial intelligence”

This is not just another AI course — this is a complete AI Engineer roadmap designed to take you from zero to building real-world AI systems.

In this masterclass, you won’t just learn theory — you’ll build, deploy, and scale AI applications using the most in-demand technologies in the industry today.

You’ll start by understanding the fundamentals of Artificial Intelligence, Machine Learning, and Deep Learning, then quickly move into hands-on Python, where you’ll learn how to work with data and build reusable code.

From there, you’ll dive deep into Generative AI and Large Language Models (LLMs) — including how models like GPT and Claude work, and how to control them using advanced prompt engineering techniques.

But we don’t stop there.

You’ll learn how to:

  • Build AI-powered applications using APIs

  • Implement Retrieval-Augmented Generation (RAG) systems

  • Create AI Agents that can think, act, and automate tasks

  • Design multi-agent systems that collaborate like real teams

  • Develop full-stack AI applications

  • Deploy your projects using AWS, Docker, and modern DevOps practices

You’ll also learn how to optimize costs, reduce latency, and secure AI systems — skills that separate beginners from real engineers.

By the end of this course, you will be able to:

  • Build real AI products

  • Deploy them to production

  • Understand how AI systems work end-to-end

  • Position yourself as a job-ready AI Engineer

This course is designed with a project-first approach, ensuring you gain practical, real-world experience — not just theoretical knowledge.

Who this course is for:

  • Beginners who want to become AI Engineers and build real-world AI systems from scratch
  • Developers (frontend/backend) looking to transition into AI, LLMs, and automation
  • Data Analysts / Data Engineers who want to move into Generative AI and advanced applications
  • Students and fresh graduates preparing for careers in AI, Machine Learning, or software engineering
  • Entrepreneurs and startup builders who want to create AI-powered products or automate workflows
  • Professionals interested in AI Agents, RAG systems, and modern AI architectures

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