AI Engineering Courses and Certifications

LearnKartS Career Certificate

Agentic AI Engineering: RAG, MCP & MERN

Master building autonomous AI systems using RAG, MCP & MERN stack—integrating OpenAI, vector databases, and tool calling to deploy production-ready agentic AI applications.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course

Edureka

Generative AI Tools for Modern Software Engineering

Discover AI-powered tools to revolutionize software engineering workflows, from code understanding and quality assurance to debugging, security, and optimization.

• Coursera
• 12 hours 8 minutes
• Self-Paced
• Paid Course

Prompt Engineering for AI Image Generation

Master prompt engineering techniques to create professional AI-generated images for business use, covering tool selection, style description, and ethical implementation.

• Coursera
• 5 hours 10 minutes
• Self-Paced
• Paid Course

Whizlabs

Prompt Engineering Generative AI & LLM Models Fundamentals

Master prompt engineering and LLM fundamentals through hands-on training, optimization techniques, and advanced architectures like RAG for real-world AI applications.

• Coursera
• 6 hours 28 minutes
• Self-Paced
• Paid Course

MathWorks

AI for Engineering: An Overview

Explore how AI enhances engineering workflows—from simulation and virtual sensors to predictive maintenance and digital twins—while applying responsible AI principles like explainability and observability.

• Coursera
• 1 hour 11 minutes
• Self-Paced
• Paid Course

Coursera Career Certificate

Eyes on AI - Computer Vision Engineering

Master computer vision engineering by building, optimizing, and deploying AI systems for real-world applications like autonomous vehicles and medical imaging using PyTorch and MLOps practices.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 4 courses

Defending Against AI-Driven Phishing and Social Engineering

Master AI-driven phishing defense through hands-on simulation tools like SniperPhish and PentestGPT, plus network anomaly detection using machine learning techniques.

• Coursera
• 3 hours 30 minutes
• Self-Paced
• Paid Course

Packt

Build with LLMs: Prompt Engineering & Real AI Projects

Master prompt engineering and build real AI projects, covering LLM core concepts, tokenization, few-shot prompting, and chain-of-thought techniques to create an AI-powered Git commit message generator.

• Coursera
• 8 hours 11 minutes
• Self-Paced
• Paid Course

Prompt Engineering for AI Text Generation

Master prompt engineering techniques to optimize AI text generation tools for business communication, content creation, and workflow efficiency in just 5 hours.

• Coursera
• 4 hours 55 minutes
• Self-Paced
• Paid Course

Packt

AI Engineering and Deployment

Master TensorFlow, CNNs, RNNs, and AI agent frameworks like AutoGPT to build, deploy, and scale ML models with ethical considerations for real-world applications.

• Coursera
• 8 hours 58 minutes
• Self-Paced
• Paid Course

Packt

Generative AI & Prompt Engineering for Design & Content

Master generative AI and prompt engineering to transform content creation, design visuals, automate workflows, and scale multimedia campaigns using Canva, Adobe Firefly, and Runway ML.

• Coursera
• 6 hours
• Self-Paced
• Paid Course

Coursera

Advancing Your Career in AI and Machine Learning Engineering

Unlock strategies to advance your AI and ML engineering career, from building a portfolio and resume to navigating interviews and exploring roles in MLOps, AI systems, and applied machine learning.

• Coursera
• 14 minutes
• Self-Paced
• Paid Course

LearnKartS

Integrate AI Models in n8n: Prompt Engineering & Outputs

Embed OpenAI, Claude, Gemini, and Ollama into n8n workflows. Master prompt engineering, structured outputs, email automation, and local LLM setup to build self-running AI systems.

• Coursera
• 3 weeks, 2 hours a week
• Self-Paced
• Paid Course

Coursera Career Certificate

Pixels, Waveforms & Words: Engineering Multimodal AI Systems

Master the full engineering stack for multimodal AI systems—processing images, audio, and text together—using PyTorch, TensorFlow, and OpenCV to build, evaluate, and deploy production-ready solutions.

• Coursera
• 4 weeks, 10 hours/week
• Self-Paced
• Paid Course
• 12 courses

Pragmatic AI Labs

AI-Powered Analytics and Performance Engineering

Master building AI-powered analytics pipelines on AWS using Amazon Bedrock, Lambda benchmarking, and Amazon Q for BI, including Rust integration, cost optimization, and natural language SQL queries.

• Coursera
• 3 hours 32 minutes
• Self-Paced
• Paid Course