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Boost Your Career with a Master’s Degree in Computer Science


Learn the Latest Programming Technologies That Employers Want


Begin with 8-13 months of study on our U.S. campus. Study with expert faculty, top academics, and proven courses for personal growth.

Classroom instruction with masks and social distancing is safe and effective.


Internationals work for up to two years with a full-time paid training internship as a software developer in any company in the USA.


Finish your remaining courses via distance education during evenings and weekends while working at your internship position.


Graduate and receive a Master’s Degree in Computer Science. Congratulations!

Our Graduates Average Starting Salary is over $94,000

Starting salaries range from $70,000 to $130,000

Federal Student Loans are Available to Cover Your Costs

Low-interest federal student loans are available to cover tuition, housing, and meals, plus cash for expenses.

Study Career-Focused Courses with Practical Assignments

Standard Core Courses

  • This course provides a focused program for enhancing programming and analytical skills in five areas: problem-solving, data structures, object-oriented programming, the Java programming language, and the use of recursion in Java programs.

    These topics are of particular importance as a prerequisite for the courses in the graduate program in Computer Science.

    Topics include elements of Java programming, object-oriented design and implementation, data structures (including lists, stacks, queues, binary search trees, hash tables, and sets), the exception hierarchy, file i/o and streams, and JDBC. (4 credits) Prerequisite: For undergraduate students: CS 221; for graduate students: consent of the department faculty

  • This course presents the fundamental principles of object-oriented programming. Students will learn how to write reusable and better-maintained software, and integrate this knowledge with laboratory assignments and projects. Topics include: fundamental principles and models of object-oriented programming, UML class diagrams and design principles that promote re-usability and maintainability of software. (4 units)

  • This course considers the current methods and practices for good design of software systems. Topics include: software design patterns, frameworks, architectures, and designing systems to apply these multi-level abstractions. (2-4 credits) Prerequisite: CS 401 or consent of the department faculty.

  • This course presents methods for analyzing the efficiency of algorithms (including worst-case and average-case analysis) and introduces a variety of known, highly efficient algorithms. Analysis, design, and implementation of algorithms are given equal emphasis. Topics include searching and sorting, efficiency of operations on data structures (including lists, hashtables, balanced binary search trees, priority queues), graph algorithms, combinatorial algorithms, recurrence relations, Dynamic Programming, NP-complete problems, and some special topics as time allows. (Special topics include computational geometry, algorithms for cryptosystems, approximation, Big Data and parallel computing.)

  • This course focuses on teaching the principles and practices used when developing larger scale enterprise applications. We will examine the different architectural layers that are frequently used and different technologies associated with these layers, including Object Relational Mapping (ORM), Dependency Injection (DI), Aspect Oriented Programming (AOP), and integration with other applications through Web Services (RESTfull and SOAP), Messaging and remote method invocation. Must have a working knowledge of relational databases and SQL. If you do not have a strong course or good working knowledge of SQL you should sign up for CS422 DBMS before signing up for EA. (4 units)

  • Software Engineering is a course that introduces the student to best practices in software development through a software development methodology. Students have already had some experience in previous courses with the Object Oriented paradigm and have used some of the basic UML diagrams for purposes of modeling relationships between software objects. In Software Engineering, the student will develop skills in putting these tools together to produce robust, easily maintainable software. A software development methodology describes when and how OO concepts and UML diagrams should be used to accomplish the aim of building quality software. The course centers around a small project in which the principles discussed in the lecture format can be illustrated and applied. By the end of the course, the student will have a running application, built in accord with the high standards of the RUP (Rational Unified Process) development methodology.

  • This course focuses web applications in an enterprise setting. An enterprise application is a large software system designed to operate in a large organization such as a corporation or a government. Enterprise applications are complex, scalable, component-based, distributed and mission critical. This course, CS545, focuses on the front end or presentation layer of an enterprise web application. CS544 Enterprise Architecture is a companion course that focuses on the back end or business layer, including business logic, transactions, and persistence. CS472, Web Application Programming, is a prerequisite course that covers HTML, CSS, JavaScript, servlets and JSP.

    The course teaches principles and patterns that are general across platforms and frameworks. The course will examine and work with the two predominant Java web frameworks, Java Server Faces (JSF) and SpringMVC. JSF is a component based framework and is the official presentation framework specification for the Java Enterprise Edition technology stack. SpringMVC is part of the Core Spring framework and has become the most widely used Java web framework in recent years. (4 units) Prerequisite: CS 472 or consent of the department faculty.

  • This course provides a systematic introduction to programming interactive and dynamic web applications. The course is intended for individuals with little or no prior web application programming experience. This offering will use Java servlets and JSP for server side processing. The course will introduce HTML and CSS. JavaScript is a focus of the course, and is covered as a functional programming language including jQuery, Ajax, and JavaScript namespaces and modules. It is a prerequisite for the CS545 Web Application Architecture. It does not cover AngularJS or NodeJS, but the JavaScript covered here will prepare you to learn those technologies. (4 units)
    Prerequisite: CS 220 or CS 401 or consent of the department faculty.

  • Your first course is specifically designed to establish the basis of how you can become a top performing computer science professional. The course is rooted in the practice of Transcendental Meditation which leads to fulfillment of your true potential. You will learn about the benefits of TM including the ability to solve complex problems by superior mental functioning enhancing creativity and “out of the box” thinking. The course will focus upon the principles which underpin peak performance in activity by developing an optimal mix of rest and activity. You will develop and experience an ideal daily routine which supports success in life. (2 units)

  • The goal of this course is to provide students with knowledge and skills in leadership, including communication skills as preparation for future leadership roles.

    By the end of this course, students will understand the answers to key questions regarding effective leadership, including the following:

    Are there ‘natural-born’ leaders?

    Do you have to have charisma to lead effectively?

    What one asset is required to be a leader?

    What is the difference between managing and leading?

    What are the many ‘intelligences’ required to lead in this era?

    What is ‘management malpractice’ and how does it lead to self-sabotage?

    Knowing that feedback is essential to the leading process, how do we get over the fear of giving and receiving it?

    What is the source of 80% of the problems found in the workplace?

    Is there scientific research available to assist the organization in improving it’s individual and team leadership skills?

    Guest speakers will include eminent entrepreneurs, computer scientists, philanthropists, Academics and other prominent leaders in society.

    (2 units)

Additional Course Options

  • Modern information processing is defined by vast repositories of data that cannot be handled by traditional database systems. This course covers latest technology developed and used by industry leaders to solve this problem in the most efficient way. Specific topics covered include MapReduce algorithms, MapReduce algorithm design patterns, HDFS, Hadoop cluster architecture, YARN, computing relative frequencies, secondary sorting, web crawling, inverted indexes and index compression, Spark algorithms and Scala . (4 units) Prerequisite: CS 435 Algorithms.

  • Big Data is the new natural resource: data is doubling every 12-18 months. This new Big Data Analytics course covers the fundamental concepts and tools for mining large diverse data sets to generate new insights. You will master the use of R language to create Wordcloud, Pagerank, Data Visualization, Decision Trees, Regression, Clustering, Neural Networks, and more. You will work with some large multi-million record datasets, and also mine Twitter feeds. You will learn Hadoop/MapReduce and Streaming Data concepts, and will explore other Apache Big Data Projects such as Spark, Flink, Kafka, Storm, Samza, NoSQL through individual research papers. You will work in groups on open projects from to compete for prize money by solving best-of-breed data-analytic challenges. You will also learn to use industry-leading IBM SPSS Modeler, and open-source data mining platforms. The #1 bestseller textbook used in this course is written by the instructor himself. The course will also use a wide range of video training materials from MIT, Coursera, Google, and elsewhere. (4 units) Prerequisite: Consent of the department faculty

  • In just a few short years, big data technologies have gone from the realm of hype to one of the core components of the new digital age. These technologies are very useful for transforming Information to Knowledge.

    The aim of the course is to add some really important tools in your arsenal to help you solve various big data problems. We’ll start with giving answers to questions like “What is Big Data? Why is it important or useful? How do you store this big data?” We’ll then study different tools and programming models from the big data technology stack which will help us to analyze the data. Topics include some of the projects in the Hadoop ecosystem such as MapReduce, Pig, Hive, Sqoop, Flume, HBase (NoSQL DB), Zookeeper and Apache Spark ecosystem projects. We’ll also cover an introduction to AWS and EMR. You’ll be mainly working with a single node Hadoop distribution of Cloudera. (4 units) (No prerequisites)

  • Database systems organize and retrieve information, allowing the user to access the desired information easily and efficiently. Topics include: relational data model; SQL; ER modeling; relational algebra; data normalization; transactions; objects in the database; data security and integrity; data warehousing, OLAP, and data mining; distributed databases; and study of a specific commercial database system. (4 units) Prerequisite: CS 401 or consent of the department faculty.

  • Machine Learning, the field of study that gives computers the ability to learn from data, is at the heart of almost every scientific discipline, and the study of generalization (that is, prediction) from data is the central topic of machine learning. This course gives a graduate-level introduction to machine learning and in-depth coverage of new and advanced methods in machine learning, as well as their underlying theory. It emphasizes approaches with practical relevance and discusses a number of recent applications of machine learning, such as Data Mining (in Big Data / Data Science, Data Analytics), Natural Language Processing, Computer Vision, Robotics, Bioinformatics and Text and Web data processing. Machine Learning is used in various industries including Financial Services, Oil & Gas, Health Care, Marketing & Advertising, Government, Internet and Internet of Things.

    This course covers a variety of learning paradigms, algorithms, theoretical results and applications. It uses basic concepts from artificial intelligence, information theory, statistics, and control theory insofar as they are relevant to machine learning. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines, decision tree, Bayesian learning & optimization); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control. Other topics include HMM (Hidden Markov Model), Evolutionary Computing, Deep Learning (With Neural Nets) and designing algorithms whose performance can be rigorously analyzed for fundamental machine learning problems. (Course not offered Spring 2021)

    An important part of the course is a group project. Major open source tools used for parallel, distributed and scalable machine learning will be briefly covered to help students doing the projects. (4 units) Prerequisite: None.

  • The importance of Mobile device programming has emerged over the recent years as a new domain in software development. This course prepares the students to develop applications that run on mobile devices such as an IPhone, IPad or Android phone. This is a rapidly developing market. Course focuses on installing, developing, testing, and distributing mobile applications. At the end of this course students are able to develop an app for the platforms covered, simulate them, test them on the real device and finally publish on the app store to make availability to the users. (4 units) Prerequisite: CS472 or consent of the department faculty.

  • In this course you will learn the Reactive Programming Architecture of SPA (Single Page Web Applications) along with all the necessary skills to build a full Modern Web Application. Technologies include: NodeJS, ExpressJS, TypeScript, AngularJS2, Firebase and NoSQL databases (MongoDB). The course will cover:

    • How the C++ V8 engine and asynchronous code work in Node and the Node event loop.
    • How to structure your code for reuse and build Restful API using modules and ExpressJS.
    • How NoSQL databases work: Mongo Shell, Aggregation framework, Replica Sets, Clustering, Shards, Mongoose ORM.
    • Deep understanding of how Angular (backed by Google) works, Change Detection, Reactive RxJs programming with Observables and Subjects, The Shadow DOM, Zones, Modules and Components, Custom Directives and Pipes, Services and Dependency Injection, Angular Compiler, JIT and AOF Compilation, Forms (Template Driven and Data Driven), Data Binding, Routing, Guards and Route Protection, HTTP client, JWT JSON Web Token Authentication.

    (4 units)

  • The standard processor for all new computers is now a multi-core processor, which has the potential to execute programs much more quickly. However, to utilize this potential, a programmer must have some knowledge of parallel programming techniques. During this course, students will spend most of their time writing and debugging parallel programs. The expected outcome will be to develop a new level of practical programming skill. This skill will not only be useful for programming of multi-core processors, but also operating systems programming and distributed database programming. The software tools used during this course include Microsoft Visual C/C++, Java multithreading library, and OpenMP threading standard. (4 units) Prerequisite: Knowledge of computer programming using Java, C, or C++.

  • In this course we will look at the techniques, principles and patterns of how to design flexible, scalable, testable and resilient software systems using microservices. We will study how we can split up large applications into smaller microservices that are easier to build and other advantages compared to monolithic enterprise applications. A distributed microservice architecture also gives many challenges. We will study these challenges and how to address them. Topics of this course are architectural styles, integration techniques and patterns, domain driven design, event driven architecture and reactive programming. (4 credits). (No prerequisites)

  • In this practicum course, students perform computer-related tasks in a technical professional position. The tasks performed may be in the design and development of new systems or the application of existing systems for specific purposes. Practicum job descriptions are formulated by the employer and the student, and require approval in advance by one of the graduate faculty of the department, in consultation with the practicum supervisor where the student is placed. (This course is primarily for students in the internship or cooperative programs.) (0.5-1 unit per block – may be repeated.)

  • In honor of 50 years of MIU education, the Computer Science Department is happy to initiate our new Golden Jubilee ComPro Tech Talks series.

    This monthly series is being organized and moderated by Professor Renuka Mohanraj.

    Talks are available at

    All are welcome to see our latest recorded Tech Talk, from Saturday, April 23rd:

    MIU ComPro students Quoc Vinh Pham and Jialei Zhang presented a technical webinar, “Image and Video Synthesis using GAN & Deep Learning”.

    Generative adversarial networks (GANs) are algorithmic architectures that use two neural networks, pitting one against the other (thus the “adversarial”) in order to generate new, synthetic instances of data that can pass for real data. They are used widely in image generation, video generation, and voice generation.

Want to Become a Full Stack Javascript Developer?

If you prefer to focus on Javascript to become a full-stack developer visit the Master’s in Software Development program website >

MIU is the 2nd Largest Computer Science Master’s Program in the U.S.

1.  University of Southern California
2.  Maharishi University of Management (renamed Maharishi International University in 2019)
3.  Columbia University in the City of New York
4.  University of Illinois at Urbana-Champaign
5.  Stanford University

6. Arizona State University-Tempe
7. University of California-San Diego
8. Illinois Institute of Technology
9. Massachusetts Institute of Technology
10. Stevens Institute of Technology
11. North Carolina State University at Raleigh
12. Cornell University
13. University of Illinois at Chicago
14. University of Massachusetts-Amherst
15. University of Illinois at Springfield
16. University of North Carolina at Charlotte
Source: (7-10-2020)

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Maharishi International University

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  • Career Focused Master’s Degree Program

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  • Average Starting Salary $94,000 per year

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with Fortune 500 Companies and Leading Businesses

“MIU is the best place to come because the courses are based on cutting-edge technologies”

“MIU is the best place to come because the courses are based on cutting-edge technologies.”

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