AI Engineer Bootcamp

Summary

We have successfully delivered our first time Full Stack AI Engineer Bootcamp in UWA, all the videos, slides and demo code are uploaded to proper places.

We potentially will deliver this again in the coming years based on the feedback. And we also currently develop the Full Stack AI Engineer Bootcamp [Research Focus] version, current one is [Developer Focus] version, we will keep you posted.

At the same time, you can follow the recorded vidoes and slides, learn the key concepts by yourself, if you have problems, you still can contact us, we will support you through the learning progress.

Also if you have successfully made usage of the content you learned here, you can show us the evidence, we will issue you a completion certificate.

Schedules and Contents

• Starting from 2024.11.25

• The tutorial part takes three weeks, which ends 2024.12.13

• Every week, we aim for four days from Monday to Thursday, from 2pm to 4pm

• Every day from 4pm to 5pm can be a stretchable Q&A session

• In total, we will have 24 hours tutorial sessions, covers the 12 modules

• We will leave Friday as an optional QA and Discussion session also from 2pm to 4pm

• The mode will be hybrid, we will book a room, and you can also join online.

• From 12.16-12.20, you can try to build something, and we are available still for helping anything you need.

• Then you can enjoy the holiday, or use the holiday to change the world.

We want to get you job ready in this AI era.

We also want to build great teams during this progress, and advance AI capablity and ecosystem in Western Australia.

The location will be updated to CSSE: [ 207] Seminar Room, we will have power adaptor there so we can do pair programming.

Location: RBST: [ G16] Robert Street LT in UWA or Hybrid.

If you are interested and not yet on our list, please contact [email protected] or [email protected]

We will get you in.

Also, you can join our discord channel for discussion: https://discord.gg/TXBh4S2SV2

Module	Key Learning Components	Time	Labs	Slides/Video
Introduction	Overview of the program	11.25 2pm-4pm	Plan projects	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/introduction
Dev Environment Setup	• IDE & Tools Configuration • Terminal & Shell • Code Formatting • Development Workflows	11.25 2pm-4pm	• Setup VSCode • Configure Git • Shell scripting	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/introduction
Docker	• Container Basics • Docker Commands • Dockerfile • Docker Compose	11.26 2pm-4pm	• Build custom image • Multi-container apps • Network setup	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/docker
Agile & Git	• Branch Management • Pull Requests • Code Review • Collaboration	11.27 2pm-4pm	• Team workflow simulation • Merge conflict resolution • Git operations	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/git-github-and-agile
Introduction to RAG	How RAG works in two stages	11.28 2pm-4pm	Pratice a RAG with a website	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/introduction-to-rag
FullStack Intro	• Frontend-Backend Architecture • APIs • Databases • Deployment	11.28 2pm-4pm	• Build simple full-stack app • Deploy to cloud • API testing	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/full-stack-intro-demo-and-setup
Python Package Development	• Package Structure • Dependencies • Virtual Environments • ML Package Development	12.2 2pm-4pm	• Create Python package • Publish to PyPI • Package testing	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/python-package-development
Databases	• SQL Fundamentals • Graph DB • Vector DB • Query Optimization	12.3 2pm-4pm	• SQL database design • Neo4j implementation • Performance testing	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/databases
React	• Components • State Management • Hooks • Performance	12.4 2pm-4pm	• Build React app • State management • Component testing	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/react
Django	• MTV Architecture • URL Routing • ORM • RESTful Endpoints	12.5 2pm-4pm	• Build Django app • Database integration • Authentication	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/django
GraphQL	• Concepts • Setup • Compare with Restful • Performance	12.9 2pm-4pm	• GraphQL API design • Integration with React • Testing	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/graphql-and-hasura
Authentication	• JWT Implementation • Security Best Practices	12.10 2pm-4pm	• Implement auth system • OAuth integration • Security testing	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/authentication-and-authorization
DevOps	• CI/CD Pipelines • Infrastructure as Code • Deployment and Monitoring	12.11 2pm-4pm	• Setup CI/CD pipeline • Cloud deployment • Monitoring setup	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/deploy-and-ci-cd
Project Demo	End to end project implementation demonstration	12.12 2pm-4pm	Develop your own projects	https://tutorial.nlp-tlp.org/full-stack-ai-engineer-bootcamps/project-demo

Project-Driven Learning:

From Data to Real-World Applications

Transform your learning journey into tangible results by building a meaningful full-stack application. Choose your path and learn by doing:

Option 1: Build Applications for Social Good

Create impactful applications using Western Australia's government datasets from data.gov.au. Projects like map.findperth.com show how we can transform public data into valuable community services with the full stack tech we will deliver in this bootcamp. In this journey, you'll:

• Work with real government datasets

• Create data-driven insights and visualizations

• Build intuitive user interfaces

• Deploy applications that solve community needs

• Integrate AI/ML capabilities to enhance your solution

Option 2: Build Your Dream Project

Have an application idea you're passionate about? Perfect! We'll help transform your vision into reality while mastering the full technology stack. Your project becomes the perfect canvas for applying everything you learn.

What makes this journey special:

• Learn by building: Every concept is immediately applied to your project

• Modern tech stack: Master the latest web development technologies

• AI Integration: Enhance your application with cutting-edge AI/ML capabilities

• Portfolio-ready: Finish with a complete, deployed application that showcases your skills

• Real impact: Whether using public data or your own idea, build something that matters

Why call this "Full Stack AI Engineer" Bootcamp?

Short Answer:

This bootcamp focuses on developer skills because delivering real-world AI products requires strong software engineering foundations. The core mission is enabling you to build and deploy production-ready AI solutions.

Long Answer:

While we do cover modern AI concepts (RAG, Agents, LangChain, etc.), they're integrated within broader development modules. Our approach comes from real-world experience - knowing where and how these tools fit into production systems, rather than treating them as isolated technologies. Our long answer for this will be delivered during the bootcamp progress.

Industry Context:

Like many tech roles before it (Full Stack Developer, DevOps, Cloud Engineer, DevSecOps), "AI Engineer" is another title invented by HR and industry trends. But behind these titles lies a consistent truth: Companies need people who can get things done, whatever it takes.

What organizations really need are practitioners who can:

• Integrate AI into existing systems

• Deliver production-ready solutions

• Bridge the gap between AI capabilities and business needs

• Build scalable, maintainable architectures that combine traditional software with AI components

This bootcamp provides the comprehensive skillset needed to meet these real-world demands, focusing on practical implementation rather than just theoretical concepts.