DevOps/Cloud Engineer Pathway

Launch yourself into DevOps/Cloud engineer jobs at top-tier tech companies with confidence, technical skills and a strong portfolio.

Machine Learning Engineer Program

About Our DevOps/Cloud Engineer Pathway

Qwasar’s DevOps/Cloud Engineer Pathway focuses on courses that cover architecture, infrastructure, monitoring, automation, and network programming, as well as strong fundamentals in data structures and algorithms. Our comprehensive set of courses are entirely project-based, meaning learners develop a strong technical portfolio using cloud technologies and scalable infrastructures as well as desired hard and soft skills.

Overall, our DevOps/Cloud Engineering Pathway is designed to train learners to become a DevOps/cloud engineer capable of working on enterprise-level infrastructure and who are unrelenting, dependable problem solvers.

machine learning program

Find the Pathway Option that Works For You

Full-time and part-time and flexible pathway options available remotely.

Part-time Professional Flex​

12-24 months

Monthly Sat. meetings

Study on a part-time basis with somewhat flexible options on course meetings. No project deadlines.

Start dates:

13 July 2024

14 Sept 2024

Intensive Bootcamps - Part Time

12-24 months

Tues/Thurs meetings

Study part-time in a highly structured intensive bootcamp. Attendance is required and projects have deadlines.

Start dates:

9 July 2024

10 Sept 2024

Intensive Bootcamps - Full Time​

9-12 months

Mon – Fri meetings

Study in a highly structured intensive bootcamp. Attendance is required and projects have deadlines.

Start dates:

9 July 2024

10 Sept 2024

  • Join a specific cohort
  • Virtual meetings 1-3x per day
  • Learn in a community
  • 100% hands-on learning
  • Accountability & motivation

  • Stack courses back to back
  • OR take breaks between courses
  • Duration estimates are based on back-to-back courses

Set Yourself on a Path for Top DevOps/Cloud Jobs

Companies are pretty clear about what they want in their candidates.

You should be asking the question, “How does our curriculum align with the job description of companies I want to work for one day?”
Here’s a list of companies or types or companies looking for candidates with the specific skill set and experience that aligns with this program’s curriculum:

  • Financial industry – Capital One, Wells Fargo, Federal Reserve, etc.
  • Automotive – Tesla, Lucid Motors, etc.
  • Defense: Lockheed Martin,
  • Leidos, Northrop Grumman, etc.
  • Tech: Adobe, Pinterest, Intel, Nintendo, etc.

Languages and Tools

Languages and tools covered throughout the AI/Machine learning engineer program:

DevOps/Cloud Engineer Pathway 1
DevOps/Cloud Engineer Pathway 2

DevOps/Cloud Engineering Program Curriculum

What you’ll cover throughout your learning journey.

Introduction to Programming

Begin to use and become familiar with everyday programming tools and terms – the terminal, the command line, Git, folders, filers and repositories

Cover the fundamentals of web programming and programming as a concept, including functions, variables, different types of variables, multiple variables, etc.

Build your first small project in Python and begin fundamentals of debugging and problem solving

Introduction to Problem Solving

Build a web scraper to collect information that can be used for finding an apartment, or buying concert tickets

  • Breakdown a large project into smaller, more manageable tasks and functions
  • Introduction to data lifecycle

    How Learning Works

    What you will be doing throughout the program.

    Machine Learning Engineer Program projects


    Each season has a series of projects to complete that last 1 day to up to 3 months. These are problems and challenges to build software based on certain requirements and restrictions.

    One example of a project would be to build a task-management software with tags, permissions, and a basic user interface.

    Machine Learning Engineer Program exercises


    Each week, participants will have 1-5 coding exercises to complete. These are accessed through our software and your code is auto-graded to ensure it’s is up to speed and functioning. This is part of the learning process. We have over 800 exercises in our library with thousands of test cases!

    Machine Learning Engineer Program role play


    We use role play to develop soft skills such as job negotiations or conflict resolution. We also use role play in technical interview practice where participants will both be the interviewee and the interviewer. This dual-sided perspective is unique to our program & helps build better interviewees.

    Machine Learning Engineer Program gamification


    Our system is gamified, meaning that you will earn and spend “Qpoints.” As you complete peer code reviews, you earn points and as you submit your projects for review, you will spend Qpoints.

    What Sets Us Apart

    Silicon Valley Standards

    We train to standards set by Silicon Valley for machine learning engineers. This means the level is much higher than that of bootcamps, and higher than that of CS degrees. Your specialty is being an elite engineer 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 Back-end 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 Technical 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.

    Why Qwasar

    Why pay more, study less, and then spend 6-12 months trying to find a job (at a bootcamp or CS degree), when you could pay less, study more, and give yourself a much higher chance of gaining employment at (or before graduation)?

    Unlike others, our learning model is backed by significant learning science and the learning experience is rooted in learning by doing and in a learning community.

    Our employment rates are within 2 months of graduating, not 6 or 12, and most learners gain employment before they finish the curriculum.

    We’re way cheaper than other options, and offer flexible learning opportunities.

    We list some of the reasons why you should consider Qwasar:

    • Train to Silicon Valley standards
    • MUCH greater depth of fundamentals, data structures, algorithms
    • Freedom and flexibility in learning – i.e. time to learn what you don’t understand
    • Hugely diverse and welcoming learning community
    • Depth and breadth of languages, technical skills, and frameworks covered
    • Extensive technical interview, resume, and profile training/resources
    • Industry-leading coding and learning management platform
    • Access to alumni network for referrals to jobs

    Real Employer Partnerships and High Employment Rates

    Qwasar works directly with employers and hiring partners who recruit from our courses and pathways. Partners include LinkedIn, Capgemini, Workday, Claris, Accenture, Crowdstrike, and more.

    Many employers have reached out to us to recruit directly from our programs. Qwasar is recognized in industry for its superior programs, curriculum, and graduates, and as a result, our learners often have significantly better opportunities for recruitment into jobs, internships, and apprenticeships compared to bootcamp grads.

    As of June 2022, our programs have a 95% employment rate for learners who finish the program, with most learners gaining employment before they finish the program. The employment rate is calculated within 6 weeks of graduation, NOT 6-12 months after graduation.

    Machine Learning Engineer Program career support

    Award-Winning Program recently named our Elite Cloud Engineering Program one of the Top 10 Best Cloud Computing Bootcamps of 2021. We are so proud to offer industry-leading tech talent programs in cloud computing. Some of the criteria used by Intelligent were prerequisites needed, certificate upon completion, flexible schedule, and time to complete.

    What to Expect


    At Qwasar, you are responsible for your learning, just as you would be responsible for your work in a job. Problem-based learning involves finding, trying, and building solutions. With no single source of truth and no answers provided, it’s up to you to figure out how to make your code work, when and how to ask for help, and how to successfully build software in a team.

    DevOps/Cloud Engineer Pathway 3

    Attend an Information Session

    Join us for a session on what learning is like at Qwasar. Sign up to learn more about our program options and how each cohort works:

    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:

    • Group debugging sessions
    • Small group sessions
    • Virtual coworking rooms
    • Sophisticated peer code review system
    • Coding collaboration workshops and pair programming
    • Our lively Discord online chat (with a tech news section and a meme section)

    Transitioning Careers? Join the Club!

    Qwasar is a hive of career switchers. We have people who are or were: baristas, retail associates, medical assistants, accountants, professional musicians, biomedical researchers, teachers, finance directors, IT support professionals, network engineers, mechanical engineers, college students in non-technical fields, business analysts, writers, translators, and more.

    We also have career returners and veterans in the community.

    Chances are high that you’ve got transferable skills. Here’s an example we put together for people transitioning from accounting:

    A 6-Step Guide on How to Transition From Accounting to Tech
    DevOps/Cloud Engineer Pathway 4

    Check Job Descriptions: Our Curriculum Aligns to Employer Demands

    Our curriculum is based on what employers are looking for in cloud engineers.
    Other programs don’t cover the minimal level required by Tier 1 tech companies.

    Here’s how we stack up:




    CS Degree

    Good at structured problem solving to efficiently debug code and to anticipate potential problems



    Experience developing and managing CI/CD pipeline as well as automating testing



    Proficiency with UNIX/Linux systems



    Proven experience using cloud tools to design, deploy and maintain cloud-based systems and infrastructure (AWS/GCP/Azure, Kubernetes, Python, PostgreSQL, Redis, etc.)



    Experience in administration, installation, and configuration of a development environment



    Experience with VMs and containerization



    Strong communication and collaboration skills yet able to work independently



    Machine Learning Engineer Program shooting star

    Information Sessions

    Join us for a session on what learning is like at Qwasar. Sign up to learn more about our program options and how each cohort works.

    Machine Learning Engineer Program shooting star

    Qwasar vs. Others

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

    Machine Learning Engineer Program shooting star

    View Platform

    Software drives our programs and learners access one of the world’s most innovative learning platforms for tech talent training.