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.

machine learning program

Program Options Available

Full-time and part-time programs available remotely.

Remote Part-time Weekday

12-18 months

Tues/Thurs meetings

Pricing


Start dates:

7 May 2024

9 July 2024

10 Sept 2024

Remote Part-time Saturdays

12-18 months

Saturday meetings

Pricing


Start dates:

11 May 2024

13 July 2024

14 Sept 2024

Remote Full-time Weekdays

12 months

Mon – Fri meetings

Pricing


Start dates:

7 May 2024

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
  • Live coding sessions
  • Interviews with industry SWEs

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.

Set Yourself on a Path for Top Machine Learning 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, JP Morgan Chase, regional banks, etc.
  • Automotive – Tesla, Lucid Motors, Zoox, Ford, etc.
  • Healthcare – Glaxo-Smith Klein, Walgreens, etc.
  • Tech: Apple, Adobe, Google, Facebook, NVIDIA, PayPal, etc.
  • Consulting: Deloitte, PwC, McKinsey, Accenture, etc.

Languages and Tools

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

python
SQL
pytorch
jupyter
panda
keras
tensorflow
AI/Machine Learning Engineer Program 1
AI/Machine Learning Engineer Program 2

Machine Learning Engineering Program Curriculum

What you’ll cover throughout your learning journey.

Introduction to Web 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

Data Structures and Types

Understand the fundamental different kinds of data structures in programming and why they are important.

Understand and work with different data types in C to understand how a computer treats different types of data, how that affects memory.

Work with pointers to control computer memory allocation when using different data structures and types, making your programming more efficient.

Discover and work with arrays, a fundamental concept in programming that makes your code more efficient by streamlining data organization and use of variables.

Introduction to Backend Computer Programming

Take arrays and data structures to another level and begin using them to implement algorithms. Cover basic search algorithms vital for backend programming

Add greater complexity to data structures, types, arrays and pointers by combining them into one project where learners are responsible for logic design and the architecture of their functions, files, and folders

Uncover the importance of libraries in programming languages by building one of the most used libraries in coding. Students cover parsing, memory management, variable arguments, and error handling.

Introduction to Data Manipulation

  • Understand and practice data cleaning
  • Understand and practice data manipulation, including formatting and structuring for use
  • Work with SQL and CSV databases

Introduction to Data Science

  • Bootcamp Data Science
  • Cover intermediate statistics
  • Use Python to complete mathematical operations and visualizations of data
  • Use Pandas and MatPlotLib
  • Data lifecycle: load, process, visualize, and analyze data

Statistical Programming in Python

  • Data processing
  • Data display and visualization
  • Data analysis

Intermediate Data Management

  • Converting between database types
  • CSV to SQL
  • SQL to CSV
  • Data merging: merge two different databases into a single, standardized and clean database

Introduction to Machine Learning

  • Programming for linear regression
  • Algorithm optimization

Applied Data Science

  • Complete an end-to-end data science project, covering the entire data and software development lifecycles
  • Produce business recommendations based on business analysis and present findings to management committee

Applied Machine Learning

  • Complete an end-to-end machine learning project, focusing on applied regression and prediction models
  • Produce comprehensive algorithm that can be used in an application as a recommendation feature

Machine Learning and Fintech

  • Build an intermediate fraud detection model for large financial institution
  • Understand business implications of fraud detection, the financial costs associated with algorithm choices, and how your algorithm could improve the company’s bottom line
  • Build a mortgage evaluation model for a bank
  • Understand the risks associated with mortgages, especially false negatives or false positives, and the business model opportunities associated with improved predictions

Classification Models

  • Build advanced classification model using machine learning
  • Collect, process, and analyze data from different file formats to successfully train a classification model

Introduction to Deep Learning

  • Build an AI capable of solving a set of mathematical problems
  • Requires advanced machine learning and some deep learning
  • Large and complex dataset required

(Optional) Final Program Project

  • Learners can complete a final program project of their choice in computer vision, CUDA, TensorFlow, LLMs, or other related machine learning areas
  • Projects must be of significant difficulty and related to industry that the learner would like to work in

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 program skills

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.

Machine Learning Engineer Program career support
AI/Machine Learning Engineer Program 3

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 halfway into the program. 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 program
  • 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.

AI/Machine Learning Engineer Program 4

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
AI/Machine Learning Engineer Program 5

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

    
machine learning program application

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

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