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Master’s in Computer Science Curriculum

Explore courses and electives available.
Curriculum Overview MSCS
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 Options:
1
Backend Software Engineering
2
AI/Machine Learning Engineering
3
Full Stack Development
MSCS Electives
Choose the option that most interests you.
Back-end 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.
ML-heavy AI/Machine Learning
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.
Multi-language 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. Cover significant amounts of data structures and algorithms, and have the opportunity to build 5 significant full stack projects in addition to the Capstone.
Master’s in Computer Science Course Core & Electives
A list of courses available within the Core and respective Elective choices.
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.
Back End Development 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
Front End Ul/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 have to combine concepts in programming and start focusing on software architecture, file structure, and breaking down large problems into smaller parts.
Introduction to Computer Programming: Part 2 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 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 in Python 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
Research in Computer Science 5 credits
  • Complete a thesis project on a subject of your choice, subject to Qwasar approval
Choose and Complete a
Capstone Project
The capstone project counts towards 30 credits of your overall 90 credits for the program. This project will last for 8-12 weeks depending on the program in order to create a quality, solid piece of work.

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.
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Choose and Write Your Thesis
The thesis requirement at Qwasar will be to write a professional paper including a slide deck and a recorded presentation on your topic. This topic can be anything that interests you, but it will be subject to Qwasar approval. There are some restrictions on how wide the subject area of your topic can be. This project is worth 5 credits out of the total 90 for the program. This project will be both peer-reviewed and instructor-reviewed for a final grade.

Students are required to write a paper and produce a 20-minute presentation on their paper. Use of modern technology and tools is highly encouraged.
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MSCS Program 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.
Required Study Time
Our virtual library offers private breakout rooms for one-on-one conversations or focused group discussions. Whether working independently or in groups, respectful communication and active listening are prioritized.
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.
How Learning Works What you will be doing throughout the program.
Learn more
Projects
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.
Excercises
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 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!
Role Play
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.