AI Engineer
AI Engineers build complex systems using foundation models, LLMs, and AI agents. You will learn how to design, build, and deploy AI systems.
Includes PyTorch, Streamlit, OpenAI, Hugging Face, and more.
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Skill level
IntermediateTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary20 hoursProjects
9Prerequisites
None
About this career path
Start your AI engineer career by mastering the complete lifecycle of AI systems—from building neural networks to deploying them in production. Learn to engineer neural networks using PyTorch, integrate large language models through APIs, and build interactive AI-powered applications with Streamlit. You’ll work with cutting-edge technologies like transformers, RAG systems, and AI agents while gaining practical experience in model evaluation, performance monitoring, and deployment best practices. By the end, you’ll have the skills to create reliable, production-ready AI systems that solve real-world problems.
Syllabus
16 units • 20 lessons • 9 projects • 19 quizzes- 1
Welcome to the AI Engineer Career Path
Discover what you will learn on your journey to becoming an AI Engineer!
- 2
Neural Network Architectures
Learn neural network architectures with PyTorch to build deep learning models for image, text, and sequential data tasks.
- 3
Introduction to AI Transformers
Learn about what transformers are (the T of GPT) and how to work with them using Hugging Face libraries
- 4
Finetuning Transformer Models
Master the art of LLM finetuning with LoRA, QLoRA, and Hugging Face. Learn how to prepare, train and optimize models for specific tasks efficiently.
- 5
AI Engineer Portfolio Project: Intent Classification
Demonstrate your ability to build an end-to-end AI engineering project for an NLP text classification task by finetuning a transformer-based model with LoRA.
- 6
Intro to OpenAI API
Explore OpenAI’s API and learn how to write more effective generative AI prompts that help improve your results.
- 7
OpenAI API Coding with Python
Leverage the OpenAI API within your Python code. Learn to import OpenAI modules, use chat completion methods, and craft effective prompts.
Certificate of completion available with Pro
Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.
Take your skills into the real world with projects
Practice new skills, connect concepts, and put it all together to create something of your own.- portfolio Project
Finetuning a Generative Language Model
Finetune a generative language model on the text of Mary Shelley's Frankenstein, using either QLoRA or performing a full finetune. - portfolio Project
Build an AI Agent for Travel Planning
Create an AI-powered trip planning application using Streamlit that demonstrates your skills in building agentic AI systems with tool calling, real-time data integration, and user feedback loops. - portfolio Project
Classifying Banking Intent from Customer Queries
This project demonstrates an end-to-end AI engineering project for an NLP task that involves building a classification system predicting banking intent from customer queries by comparing traditional neural networks with modern transformer-based models finetuned with LoRA.
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Earn a certificate of completion
Show your network you've done the work by earning a certificate of completion for each course or path you finish.- Show proofReceive a certificate that demonstrates you've completed a course or path.
- Build a collectionThe more courses and paths you complete, the more certificates you collect.
- Share with your networkEasily add certificates of completion to your LinkedIn profile to share your accomplishments.
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Job-readiness checkerBeta
See how well your skills and experience match the job postings you’re interested in. Our job-readiness checker uses artificial intelligence to show you what you need to work on to qualify for a role.Try it outEverything you need for a AI Engineer career
- Job-readiness checkerUse AI to evaluate how well your skills and experience meet the requirements of a job posting.Powered by AI
- Portfolio projectsApply what you're learning to create recruiter-ready projects for your portfolio.
- Interview simulatorUse AI to identify strengths and see how to improve your interviewing skills to land your dream tech job.Powered by AI
- Job listingsGet personalized job postings, connect with employers hiring tech talent, and easily apply for open roles.
Start your new career faster
Learn the skills
This expertly curated career path gives you all the knowledge and experience you need to start this career.Prep for interviews
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Related resources
- Article
How to Fine Tune Large Language Models (LLMs)
Learn how to fine tune large language models (LLMs) in Python with step-by-step examples, techniques, and best practices. - Article
Agentic AI vs Generative AI: Key Differences
Discover what is agentic AI vs generative AI, their key differences, and which one you should use. - Article
AI vs Generative AI: Understanding the Difference
Learn what is AI vs generative AI difference. Explore how each works, their key differences, and real-world use cases.
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