AI Applications Developer Course

Build software with embedded AI models, fine tuned models, RAGs, and vector databases.

AI Applications Developer

Course Overview

This course focuses on building software that embeds or uses generative AI models or available predictive AI models.

We focus on learning to customize models with fine tuning and using RAGs with vector databases.

Learners build multiple projects to finish with a strong portfolio of GenAI and LLM projects, ready to be shown to recruiters.

We'd recommend this course for:
- Industry professionals
- Software Engineers & Developers
- Computer Science grads
- Anyone with a good CS foundation looking for hands-on experience in Python
Required Pre-requisites
  1. Use the command line, use an IDE
  2. Use Git, and in a group setting with mains, branches
  3. Write, use, and be able to apply loops, functions, if statements, conditionals, in Python, or modern language (HTML/CSS doesn’t count)
  4. Ability to abstract and infer
  5. Basic understanding of memory and operating systems

AI Applications Developer

Course Curriculum

Introduction to LLMs & Prompt Engineering

Intermediate
  • Prompt engineering frameworks
  • GenAI Model comparison
  • LLM tokenization
  • Weights
  • Attention layers
  • Propogation

Fine Tuning Models

Intermediate
  • Gradient descent
  • Learning rate schedules
  • Loss function analysis
  • Convergence behavior
  • Neural networks
  • L2 Regularization
  • Dropout
  • Batch normalization
  • Data augmentation
  • Model behavior analysis and monitoring
  • Model evaluation: BLEU, ROUGE, METEOR, BERTscore, etc.
  • HuggingFace Transformers

RAGs, Orchestration

Advanced
  • Lang-Chain-based orchestration
  • FAISS, Chroma, Pinecone vector databases
  • Loading, splitting, embeddeding, and retrieving
  • Vector search integration
  • Application performance optimization
  • Rate limiting, JWT, and security
  • Observability (logging, Prometheus, Grafana)

End-to-End AI Development

Advanced
  • Building and deploying end-to-end AI applications
  • Choose, design, build and deploy a capstone project
  • Implement CI/CD with GitHub Actions
  • Deploy app with LLMs, embedded workflow, and vector DB
  • Optional: practice technical interviews for AI positions

Course Meetings

Morning Standup

Daily standup meetings are conducted to kick off the day, Learners share progress since last session, discuss roadblocks, and brainstorm solutions, fostering support and goal clarity. Facilitated by program managers, these meetings ensure everyone shares updates, mirroring industry practices.

Live Coding Sessions

As part of the group session, a learner will tackle a coding problem, sharing their thought process to the group, inviting discussion and alternative solutions.

Collaborative Coding Workshop

Students collaborate in small groups on unique timed coding challenges. Results are shared and then to reinforce their grasp of terminology and potential interview questions, a quick ‘Skills Check’ quiz is presented.

Weekly Technical Presentation

Explore industry-relevant technical subjects that are not typically addressed in projects. Activities range from individual presentations to  group work completing “new technology canvas” worksheets followed by brief presentations.

Engineering Case Studies

A case study is selected in advance that aligns with the program’s curriculum, learning objectives, and student expertise levels, ensuring a variety of topics. Following this, we engage in reading, analyzing, and discussing business challenges and data privacy issues, etc. fostering collaboration and diverse viewpoints.

Pair Programming Pods

A collaborative workspace where two learners work together on the same project. Partners can readily share ideas, solve problems, and learn from each other’s coding skills.

Stop Boring Online Courses!

All tracks use project-based learning, meaning you will spend most of your time coding. Manage your work and assignments in our proprietary learning platform that’s designed to reflect the working life of an engineer.
Expect to be assigned projects, coding exercises, and peer code reviews. Our platform includes:

  • Autocorrection system
  • Automatic code quality evaluator
  • Integrated development environment
  • Integrated Git system
  • Sophisticated peer code review system with IDE and Git all connected, gamified with points you earn and spend
  • Discord chat for each course

Join an

Outstanding

Learning Community!

Joining Qwasar is about joining a learning community. Learning on your own is hard, watching online videos can be boring, and sharing your learning journey (and certainly lots of jokes) with others is important.

Our platform and Discord chat, as well as our program meetings, are all about building and participating in the community.

When you join our programs, you have access to:

How Learning Works

What you will be doing throughout the program.

Projects

Exercises

Role Play

Gamification

Career Progression and Support

For intensive bootcamp learners, we provide career preparation and support. Qwasar has created a career support track and community called Technical Interview Preparation Program (TIPP), which students join in Season 2. This includes:

  • Interview Preparation and Practice
  • Data Structures and Algorithms Course
  • Resume and Profile Preparation
  • Technical Portfolio Development
  • Useful Resources
  • LinkedIn profile review
  • Resume critique

What Sets Us Apart

Silicon Valley Standards

We train to standards set by Silicon Valley for full stack developers. This means the level is much higher than that of bootcamps, and higher than that of CS or data science degrees. Your specialty is being an elite developer at a world-renown level.

Technical Skills & Knowledge

Thanks to the depth and breadth of our program curriculum, you acquire a level of technical skills and knowledge that learners in other programs or bootcamps simply never acquire.

Strong Python Skills

The vast majority of bootcamps don’t cover data structures or algorithms. CS degrees don’t cover hands-on application of theory or actually developing software architecture. We cover both and your strong back-end skills and experience with databases, data structures, and algorithms will set you apart from other candidates.

Depth of Portfolio

Learners develop a technical portfolio that has depth and shows the extent of their technical skills and ability to handle databases, deployments, and development. Neither bootcamps nor CS degrees offer this.

Explore our Modern Learning Model

With no lectures, we use a modern approach to learn that embraces technology!

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Student Experience vs. Others

How do Qwasar programs compare to other tech training options out there? Find out how we stack up.

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