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ONLINE MASTER OF SCIENCE DEGREE INARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING

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Master's in Artificial Intelligence and Machine Learning PDF

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Design Technical Solutions That Solve Business Problems

The Master’s Degree in Artificial Intelligence (AI) and Machine Learning provides students with the core knowledge necessary to succeed in the fields of AI, machine learning, computer science, and software development. Learn how applying optimal system analysis and design can solve complex organization-wide issues. Some typical responsibilities of roles in this industry include:

 

Career Outlook

$105,590 MEDIAN SALARY According to the BLS, the average annual salary for software developers (with a bachelor’s degree) in 2018 was > $100k.

↑ 21% Employment of software developers is projected to grow 21 percent from 2018 to 2028, much faster than the average for all occupations.

AI OR MACHINE LEARNING ENGINEER/SCIENTIST, SOFTWARE DEVELOPER, SYSTEM ANALYST, INTELLIGENCE OR INTERACTION DESIGNER Some job titles commonly held by those who work in AI and machine learning.

$118,370 MEDIAN SALARY According to the BLS, the average annual salary for computer and information research scientists in 2018 was > $100k.

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ESTABLISH AND ACHIEVE OBJECTIVES USING TECHNIQUES ASSOCIATED WITH AI REASONING AND UNCERTAINTY.

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APPLY LOGIC, PROBABILITY ANALYSIS, AND MACHINE-LEARNING CONCEPTS TO PROBLEM-SOLVING INITIATIVES.

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ANALYZE SYSTEMS TO EFFECTIVELY MONITOR AND CONTROL DEVELOPMENT PROJECTS.

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USE BEST PRACTICES IN REGARD TO APPLICATIONS IN SPEECH RECOGNITION, DATA PROCESSING, DATA MINING, AND ROBOTIC CONTROL.

Watch a Quick 2-Minute Overview

This 2-minute overview video covers these points, and more:

  • Degree specialization options.
  • Career paths and industry employment options.
  • Program accreditation and endorsement details.

What will I learn in this degree program?

The online Master’s Degree in Artificial Intelligence and Machine Learning provides students with the knowledge required to thrive in roles that include programming, software development, artificial intelligence, and machine learning tasks. The curriculum will address the latest deep-learning libraries, such as Tensorflow, with a focus on proficiency in Python, as well as how these technologies can be applied in a variety of industries, including healthcare, manufacturing, oil/gas, and automotive.

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Learn Valuable Skills

This program is geared toward students who already possess technical acumen, and who see AI and machine learning as an exciting, innovative career path. Additional learning outcomes of this graduate program include:

  • Use principles and techniques associated with software development.
  • Apply artificial intelligence principles as needed for a given problem or scenario.
  • Apply machine learning principles to solve a specific problem or scenario.
  • Develop solutions that are capable of modeling human behavior.
  • Implement a solution that combines artificial intelligence and machine learning principles.
  • Evaluate the performance of applications in artificial intelligence and machine learning domains.

Courses in this Degree:

Classes Start Feb 8th

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Core Degree Courses (30 Credits)

  • CSC500 Principles of Programming
    This graduate course provides a detailed overview of fundamental programming, design and testing concepts. Students are introduced to programming constructs and learn how to plan and create basic programming applications. Students will develop applications using common programming structures, which include: conditional statements, switches, loops, iteration control structures, and arrays.
  • CSC501 Management for the Computer Science Professional
    In this course, students will be prepared to analyze organizational issues surrounding programming, network and software development, and propose the necessary solutions to address business needs. Students gain a detailed understanding of how to manage, oversee, plan and maintain technical personnel and resources. Students will also learn how to effectively relay technical information to all stakeholders in an organization. Topics include management principles for programmers and development specialists, technical communications, organizational leadership, risk management, project management, and systems maintenance. Students will prepare for cross-functional positions in team and industry settings in this course.
  • CSC502 Ethical Leadership in Software Development
    In this course, students will learn about the ethical considerations and issues programmers and software developers encounter in the workplace related to data, electronic communication, and information security. Students will evaluate and interpret current policies and regulations and formulate their own policies based on these models. Students will also discuss the implications for ethical decisions by technical professionals and leadership utilizing Case Studies and Problem-based learning. Students will learn best practices in ethical decision-making for the work place in this course. Prerequisite: CSC501
  • CSC505 Principles of Software Development
    This graduate course provides students with an integrated and detailed approach to programming and software development principles. Students will understand the purpose of object-oriented software topics and pertinent software development principles. Topics included for this course focus on core programming concepts, data structures, methods, classes, and software models.
  • CSC506 Design and Analysis of Algorithms
    This graduate course provides students with a foundational knowledge in the design and analysis of algorithms. Students will make use of appropriate data structures. Complexity and analysis of algorithms will be completed focusing on worst case and average case, lower bounds, NP-completeness, and recurrences. Students will explore the complexity of appropriate searching, sorting, and graphing algorithms. Prerequisite: CSC505 Principles of Software Development.
  • CSC507 Foundations of Operating Systems
    This graduate course provides students with a foundational knowledge in operating system concepts. Students will gain a detailed understanding of appropriate operating system constructs that involve OS abstractions and mechanisms. Students will also understand the constructs of multithreading and resource management in compute systems.
  • CSC510 Foundations of Artificial Intelligence
    This graduate course provides students with an understanding of principles associated with Artificial Intelligence (AI). Students will determine how to utilize structures to represent graphs associated in data exploration. Students will gain an understanding of how to efficiently apply knowledge representation and techniques associated with AI reasoning. Topics that students will explore include techniques efficiently applying game theory, integer programming, continuous optimization, and probability analysis.
  • CSC515 Foundations of Computer Vision
    This Graduate course provide students with foundational knowledge in the areas digital image construction and processing. Students will explore topics associated with image formation, image acquisition, and image geometry. The course will expose students to the techniques required to efficiently analyze images for representation in applicable context scenarios. Students will apply image processing techniques for filtering and edge detection for image deconstruction. Prerequisite: CSC525 Artificial Intelligence.
  • CSC525 Principles of Machine Learning
    This Graduate course provides students with an understanding of foundations concepts and theories in machine learning. Students will explore foundational topics that include: supervised and unsupervised learning, learning theory, reinforcement learning and adaptive control. Students will gain an understanding of applications of machine learning in areas of data mining, human computer interaction, natural language processing and computer vision. Prerequisite: CSC510 Artificial Intelligence.
  • CSC580 Applying Machine Learning and Neural Networks - Capstone
    This Graduate course provides students with an overview of appropriate theories and models that are used to represent neural networks. Students will gain foundational knowledge in developing constructs to evaluate and represent components associated with neural networks and learning algorithms. Topics for this course include propagation, feedforward networks, perceptrons, and self-organizing networks. Prerequisite: CSC510.

Note: Some Master of Science in Artificial Intelligence and Machine Learning students may also be required to take RES500 as part of their program if they have an undergraduate GPA below 3.00. In this case, the degree is 33 credits.

Prerequisites

Students applying for this degree must have taken an advanced course in Discrete Mathematics, and an advanced course in Probability and Statistics. Students who do not meet this requirement can seek admission with the program chair approval. Students admitted with approval from the program chair who did not meet the requirements will be required to take one or both of the following CSU Global pre-requisite course work or equivalent:

  • MTH350 Discrete Mathematics
    This online course provides an introduction to discrete math with a personalized learning approach designed for an Information Technology specialization. The main areas of study include combinatorics, sequences, logic and proofs, and graph theory. Assessments for this course will include discussions, mastery exercises, and critical thinking assignments with several IT-related applications. This course fulfills a general education mathematics requirement. Course not eligible for Prior Learning Assessment (PLA) credit.
  • MTH410 Quantitative Business Analysis
    This course provides students with skills to analyze data and apply concepts of statistical analysis and research in a business context. Students formulate conclusions from data using descriptive and inferential statistical methods and expand on knowledge of the underlying theory behind types of data, data sources, data organization, measures of central tendency and variation, probability, and probability distributions. (This course is also offered through SSA. Credits earned using this option will appear on transcripts with an “S” suffix.) Course not eligible for Prior Learning Assessment (PLA) credit.


To meet pre-requisite requirements for admission, students must complete the above coursework within 12 months of starting and maintain a 3.0 grade point average. Students should reference the provisional admissions policy in the university catalog for additional admission requirements.
 

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Why You Should Earn Your Online Master’s Degree

Earning your online master’s degree through CSU Global provides you with more than just the diploma you need to get noticed. With an emphasis on real world concepts and career-relevant skills, you get training and experience along with your credit hours. Additionally, CSU Global strives to make your education as affordable as possible. With our Tuition Guarantee, your tuition rate won’t increase over time! Instead, you’ll enjoy the same low rate for the duration of your enrollment at CSU Global.

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ACCELERATED COURSES

REGIONALLY ACCREDITED

Regional accreditation by the Higher Learning Commission (HLC) means your degree comes from a top quality, trusted university.

“GOLD SCHOOL” OF DISTINCTION

In Best Colleges’ Schools of Distinction standings, CSU Global earns one of only 15 gold rankings, out of more than 2,000 online degree programs.

TOP MILITARY-FRIENDLY ONLINE COLLEGE

Guide to Online Schools identifies CSU Global as one of the top military-friendly online institutions.

“The pride I have in achieving a Masters Degree from CSU Global provided me with the confidence to attain the career plan I had envisioned.”

SCOTT RYDER

Student

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