Elite Machine Learning Engineering Program

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

Machine Learning Engineer Program

About Our AI/Machine Learning Engineer Program

Qwasar’s AI/Machine Learning Engineer program focuses heavily on algorithms and the application and improvement of different types of algorithms with large and complex datasets. The program covers machine learning, data engineering, fundamentals in data structures and algorithms, and the basics of neural networks and deep learning. Our applied, elite program is entirely project-based, meaning learners develop a strong technical portfolio as well as desired hard and soft skills.

Overall, the program is designed to train learners to Silicon Valley standards in machine learning with an emphasis on applied algorithms, critical thinking, and extensive preparation for technical interviews and a technical portfolio.

Program Options Available

Full-time and part-time programs available remotely.

Remote Part-time Weekday

12-18 months

Tues/Thurs meetings

Pricing


Start dates:

07 Mar 2023

09 May 2023

11 Jul 2023

19 Sept 2023

31 Oct 2023

Remote Part-time Saturdays

12-18 months

Saturday meetings

Pricing


Start dates:

11 Mar 2023

13 May 2023

15 July 2023

23 Sept 2023

4 Nov 2023

Remote Full-time Weekdays

12 months

Mon – Fri meetings

Pricing


Start dates:

07 Mar 2023

09 May 2023

11 Jul 2023

19 Sept 2023

31 Oct 2023

  • Join a specific cohort
  • Virtual meetings 1-3x per day
  • Learn in a community
  • 100% hands-on learning
  • Accountability & motivation
  • Live coding sessions
  • Interviews with industry SWEs
  • Minimum 3-month commitment for each program option

Pricing/Program Costs

Qwasar programs are $2,400 in total and can be paid upfront or in monthly payments. The first two months are due after enrolling and before your start date. This is non-refundable.

Once enrolled in Qwasar programs, you will be sent an enrollment contract.

If you enroll on a part-time basis, you pay $100 per month until you gain an internship, apprenticeship, or employment, at which point you pay the final remaining sum up to a total of $2,400 which can be paid one-off or monthly at $200/mo.

If you’re full-time, you pay $200 per month until you gain an internship, apprenticeship, or employment, at which point you pay the final remaining sum up to a total of $2,400 which can be paid one-off or monthly at $200/mo. 

Prices are in US Dollars and are for learners in North America. Please see our pricing page for more information.

Machine Learning Engineering Program Curriculum

What you’ll cover throughout your learning journey. Direct entry to Seasons is available.

Machine Learning Engineer Program preseason

PRE-SEASON WEB

Cover basic software engineering principles: variables, functions, loop statements, if statements, basic algorithms and data structures. Begin using an IDE and the terminal. This track is the equivalent of a coding bootcamp.

Languages:
Python

Machine Learning Engineer Program season 1

SEASON 1 ARC 1

Cover fundamental computer programming concepts and learn the basics of C. Build a solid foundation in back-end programming including pointers, arrays, strings, algorithms, data structures, data types, and software architecture.

Languages:
C

Machine Learning Engineer Program season 2

SEASON 2 DATA SCIENCE

Learners move on to Python and the fundamentals of machine learning, covering regressions, training sets, structured vs unstructured data, and data collection, display, and storage. Learners also cover some of the cloud-based tools available for ML.

 

Track tech stack

Python
Pytorch
Jupyter

Machine Learning Engineer Program season 3

SEASON 3 AI/ML

Perhaps one of the more challenging tracks, learners dig into advanced machine learning algorithms, linear regression and classification, neural networks, logistic regression, optimization and performance, support vector machines, supervised vs unsupervised learning, Kaggle and large/complex data sets, reinforcement learning.

 

Track tech stack:

Python, Panda, Tensor Flow, Keras, Jupyter

Machine Learning Engineer Program season 4

SEASON 4 AI/ML

Learners complete a final program project that aligns with the industry in which they want to get a job. The project must be about 3 months in duration and of significant technical difficulty. Learners will also contribute to open source
projects from Kaggle.

 

Track tech stack:

Python, Panda, Tensor Flow, Keras, Jupyter

YOUR LEARNING JOURNEY

Learning Top Skills is Tough

Learning skills is like learning a sport, a musical instrument, or cooking: it takes time, learning by doing, trial and error, and lots of practice. NBA players don’t get good by watching lectures or videos. Skills-based learning at Qwasar is TOUGH.

DO NOT GIVE UP
The key to our programs is to not give up. No matter how difficult the problem is in front of you, do not give up. Great engineers do not give up but instead apply structured problem solving.

EARN AN ELITE CERTIFICATE
After your hard work and upon completing the program, learners will earn a certificate from Qwasar Silicon Valley for the Elite Machine Learning Engineering Program.

Machine Learning Engineer Program learning journey

How Learning Works

What you will be doing throughout the program.

Machine Learning Engineer Program projects

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

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

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

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 programs. 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.

innovative education model consulting
Elite Full Stack Development Program career support

Career Support

Our entire program is designed to make you a great candidate. 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

  • Complete 20-40 technical interview role plays
  • Better understand the interviewer perspective by living it
  • Complete HackerRank challenges
  • Practice answering behavioral interview questions

Resume and Profile Preparation

  • Technical resume help, review, and feedback
  • LinkedIn profile review and feedback
  • Resume and profile keyword suggestions
  • Resume format requirements for optimal application responses

Technical Portfolio Development

  • Develop a strong technical portfolio as you complete the progra
  • Review and publish your code for your resume’s portfolio

Useful Resources

  • Technical resume templates
  • Behavioral interview worksheet
  • “Tell me about yourself” 2-min pitch worksheet
  • Job application tracking system
  • TIPP community meetings and support
  • Access to unique hiring platforms with jobs from companies looking for candidates without a computer science degree

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.

Machine Learning Engineer Program what to expect

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:

"If you want to work as an AI engineer or on self-driving software, then you should attend Qwasar. No other program will train you with the skills, technical knowledge, depth and breadth of understanding, or technical interview skills that are required to get into such jobs."
Qwasar Student

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

Check Job Descriptions: Our Curriculum Aligns to Employer Demands

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

Here’s how we stack up:

 

Qwasar

Bootcamps

CS Degree

Hands-on experience designing and implementing data architecture, able to contribute to architecture discussions

X
(architecture provided)

Limited

Proven experience with programming languages/tools and working with large and complex data sets (Python or C++, PyTorch, Jupyter, Tensorflow,  etc.)

X

Depends by student

Proven experience with deep learning, algorithms and optimization

X

X

Experience with the data management lifecycle, i.e. collection, cleaning, storage, analysis, etc.

Limited

X

Proven using data to solve business challenges (choosing data, training models, analyzing algorithm options, proposing solutions)

X

 Limited

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

X (debugging not required)

X (debugging not required)

Habituated to collaborating to solve problems, pair programming, and communicating in-person and remotely

X

X

    

Application Process

To apply to our Machine Learning Engineering Program, expect the following steps:

Step 1: Submit your application online.

Step 2: We review your application.

Step 3: You will be invited to schedule a virtual interview.

Step 4: Following the interview, if accepted, you will be invited to enroll.

Step 5: You will receive an email with a link to the enrollment form.

Step 6: You complete the enrollment form.

 

Following a successful application and enrollment, you will be expected to attend orientation, virtually of course!

 

Student Brochure

Download a copy of our student brochure for detailed information about our program options, policies, and logistics.

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.