Masters in Computer Science Curriculum

Our modern masters degree has a core curriculum and three specializations.

masters of computer science curriculum

About Our Masters in Computer Science Curriculum

Our Master’s of Science in Computer Science degree program is broken into two parts: a core, and an elective.

Students must complete the core curriculum before moving on to their chosen elective.

There are currently 3 elective specialisations available:

3 Elective Specializations

Software Engineering

Software engineering focuses on low-level programming, operating systems, and understanding at a fundamental level how a computer operates. From there, students move on to specialize in a modern programming language and can choose from C++, Rust, Go, or Java.

AI/Machine Learning Engineering

AI/Machine Learning engineering focuses on predictions, optimizing and improving the predictions, and early deep learning. Students will complete thesis or projects in Natural Language Processing, computer vision, and have the ability to customize their focus area within the AI/ML field.

Full Stack Development

Full Stack engineering focuses on both the front-end and back-end. Students gain skills and experiences in both, focusing on both modern languages and also common databases. Students also cover significant amounts of data structures and algorithms, and have the opportunity to build 5 significant full stack projects in addition to the Capstone.

Modern Languages, Tools, and Frameworks

Unlike other programs, we focus on modern technologies – we’re the only one to offer Rust or Go, for example. We’re always asking how to best prepare our students for industry, so industry analysis and trends inform our curriculum, not CS professors who’ve been out of industry for 20 years.

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A Curriculum Focused on Coding, not Exams

Our curriculum is focused on helping you develop advanced programming skills – and the only way to get better at coding is by doing it. In our programs, you should expect to write ~100K lines of code. And because projects undergo code review, you gain confidence that the code you write is (or isn’t) good quality and up to best practices.

Grading in Real-time

In a digital world, grading is completed faster than ever to allow student feedback to be returned and dissected quicker than in classrooms. Due to the online nature of our school, we have auto-grading and peer-reviewed assignments that are returned to students quicker than ever.

Peer Code Reviews

Students will review each other’s projects and code submitted to increase code quality and feedback skills. Our system is seamless and easy to use thanks to multiple integrated elements that reflect what engineers or developers would use in the workplace.These reviews are a great way for students to contribute to the learning community as a whole. By engaging in dual-sided review scenarios, you gain confidence in communicating by giving and receiving feedback from your peers.

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masters of computer science curriculum insight

Designed for Doers

Sitting in lectures is very often boring. Our curriculum reflects what happens in the workplace: you work on projects with deadlines, sometimes in groups; you give and receive code reviews; you write your own unit tests; you make architecture decisions, etc. Skeleton code is not provided, nor are unit tests or step-by-step instructions – because your boss won’t do this for you on the job! Our program is designed with industry engineers, for engineers who love coding and don’t want to sit in lectures for 2 years.

Courses Offered:

Advanced Algorithms

5 credits

An exploration into some of the major and most common advanced algorithms used in software engineering.

Advanced Applied Computer Science

30 credits

This is the capstone project. This course applies computer science principles and concepts previously covered in the curriculum and focuses on delivery of a finished software project or product.

Advanced Backend Development

5 credits

Focusing on larger scale projects in Java or Python, students dig into more complex software architecture and object-oriented programming.

Advanced Machine Learning

5 credits

This course dives into larger and more complex datasets, meaning more variables to take into account for building prediction models.

Applied Statistics

5 credits

This course is on applying knowledge about statistics and programming.

Backend Development (in multiple specializations)

5 credits

This course involves learning and becoming proficient in a common modern backend programming language (Java, Go, Rust, or Ruby).

Computer Systems and Their Fundamentals

5 credits

Explore the essential principles and mechanisms driving modern computer systems, including computer architecture, memory systems, storage technologies, operating systems, and networks, through hands-on experience

Data Structures

5 credits

Students will learn to design, implement, and analyze efficient data structures and algorithms that power diverse applications, while honing problem-solving skills through practical exercises and projects

Deep Learning for Computer Vision

5 credits

This course focuses on a thesis for the AI/ML specialization. Students must choose, research, then present about a specific application or subject within computer vision.

Deep Learning for Natural Language Processing

5 credits

This course involves contributing to an open-source project on NLP and requires reading and understanding existing code basis, logic, and NLP implementation.

Design and Analysis of Algorithms

5 credits

Immerse and explore algorithmic thinking,  algorithmic techniques, analyze their efficiency, and master strategies to develop optimized solutions for complex computational challenges.

 

Distributed Systems with High-Level System Design

5 credits

Unravel the principles, challenges, and cutting-edge techniques for building robust and scalable distributed systems in one of the leading programming languages in this area, Rust, while gaining hands-on experience in designing innovative solutions to real-world problems.

Foundations of Cloud Computing

5 credits

Explore the principles, technologies, and architecture underpinning cloud computing, understand various cloud service models and deployment strategies, and gain hands-on experience with leading cloud platforms, enabling you to design scalable, cost-effective, and resilient cloud-based solutions for modern businesses and applications.

Front End UI/UX Development

5 credits

This course focuses on learning to design and build multiple user interfaces for different D2C and B2B products built for mobile, web, and desktop.

Front-End Development

5 credits

Students gain proficiency in a modern front-end programming language (such as React.JS).

High Dimensional Data Analysis

5 credits

Explore cutting-edge methodologies, algorithms, and visualization techniques to effectively extract meaningful insights from complex datasets with numerous dimensions, and apply this knowledge to solve real-world problems across various domains

Introduction to Computer Programming Part 1

5 credits

Students delve deeper into modern programming languages, frameworks, and concepts that build upon concepts covered in Introduction to Problem Solving Part 1..

Introduction to Computer Programming Part 2

5 credits

Students have to combine concepts in programming and start focusing on software architecture, file structure, and breaking down large problems into smaller parts.

Introduction to Deep Learning

5 credits

This course offers an applied approach to deep learning, pushing the edges of machine learning into neural networks.

Introduction to Machine Learning

5 credits

This course delves into the foundational concepts, algorithms, and practical applications of machine learning, empowering you to build predictive models, extract valuable patterns from data, and revolutionize decision-making processes.

Introduction to Problem Solving

5 credits

Dive right into programming and solving problems of increasing complexity. Students must use abstraction, inference, and various debugging techniques.

Introduction to Problem Solving Techniques Part 2

5 credits

This course focuses on problem solving skills and techniques under time pressure and practicing technical interviews of increasing difficulty.

Low-Level Design and Design Patterns

5 credits

Explore the intricacies of designing efficient and maintainable software systems at a granular level, while mastering the application of industry-standard design patterns to solve complex programming challenges and create robust, scalable, and flexible software solutions.

Numerical Programming

5 credits

Learn to harness Python’s capabilities for scientific computing, numerical analysis, and data manipulation, equipping you with the skills to solve complex mathematical problems, simulate real-world scenarios, and optimize performance using various libraries and techniques.

Practical Software Engineering

5 credits

Add to your growing skillset with additional modern programming languages in backend engineering.

Relational Databases

5 credits

Gain a comprehensive understanding of database management systems, learn to design efficient and normalized relational schemas, master querying for data retrieval and manipulation, and explore advanced topics such as indexing, transaction management, and data integrity.

masters of computer science capstone

Thesis Project

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, Discover, JP Morgan Chase, etc.
  • Tech: Airbnb, Stripe, Blend, Twilio, etc.
  • Consulting: Deloitte, PwC, McKinsey, Accenture, etc.
  • Retail: Nike, Lululemon, Lowes, Home Depot, etc.

Capstone Project

Significant Part of Overall Grade

The capstone project counts towards 30 credits of your overall 90 credits for the program. This project can be a huge lift in your overall performance. In that respect, it will last for 8-12 weeks depending on the program in order to create a quality, solid piece of work.

The choice is yours

Similar to the thesis project, you will have some flexibility in choosing the topic of your capstone project, upon approval by Qwasar. The major requirement is that it is related to the industry that you want to go into. This project is a massive piece to put into your technical portfolio and will demonstrate why you are a perfect candidate for future jobs. You will have to build software and prove your abilities.

Car-to-Car Communication System

This system would ultimately reduce the need for stop signs. The idea is that certain cars would change speed to go through intersections more efficiently. Some would speed up while others slowed down, without anyone having to stop. In order for this to work, you would need to build algorithms and utilize network programming.

Download brochure for more detailed curriculum.

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msaters of computer science resourcefulness

Don't Expect Answers, Be Resourceful

In a real software job, your boss will not provide answers for you every time you get stuck. You are expected to figure things out and to do so efficiently.

At Qwasar, we do not provide answers to your questions all the time. Do not expect us to answer your questions like a professor or instructor would.

The point is that you learn how to become unstuck when you are stuck. You need to learn how to be resourceful, how to bring structure to a problem to solve it, and when and how to ask for help and feedback. This is VITAL to becoming a great software engineer or developer.

Great engineers are resourceful. The internet has plenty of resources for coding. The real skill is being able to use the tools and resources around you to solve today’s problems.

State of the Art Experiential Learning Platform

We use a leading experiential learning platform at Qwasar, designed by engineers for engineers. It empowers learners to take control of their learning, includes a gamified points system and economy, and features items such as:

  • IDE
  • Integrated Git system
  • Sophisticated peer code review system
  • Multi-level autocorrection system (called Gandalf)
  • Automatica code quality evaluator (called Gimli)
  • And much more (with more nerdy names!)
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Masters in Computer Science Curriculum

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Masters in Computer Science Curriculum

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Masters in Computer Science Curriculum

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