Best Online Masters Programs in Artificial Intelligence and Machine Learning

The online Artificial Intelligence master's program offered by Johns Hopkins University is an exceptional program designed for professionals looking to advance their careers in the field of AI. The curriculum is fully online and covers a range of topics in artificial intelligence, such as machine learning, natural language processing, robotics, and computer vision.

The curriculum also features a capstone project where students can use what they have learned to address issues in the real world. Students have access to cutting-edge facilities and software tools, and the curriculum is delivered by knowledgeable instructors who are authorities in the field. The program's unique features include opportunities for students to specialize in their education by choosing elective courses and working on collaborative projects with industry partners, giving them the skills and knowledge needed to succeed in the dynamic field of AI.

An online program leading to a Master of Engineering in Artificial Intelligence for Product Innovation is offered by Duke University's Pratt School of Engineering. This program is designed to provide students with a comprehensive understanding of AI and its applications. It is a 30-credit-hour program that can be completed entirely online Online or on-campus in as little as 12 months, providing students with flexibility and convenience. The program's curriculum includes foundational courses in AI and machine learning, as well as advanced topics such as computer vision and natural language processing.

One unique feature of the program is its focus on the ethical and social implications of AI, providing students with the knowledge to address complex issues related to AI. The program's cost is competitive and affordable, making it a great value for students looking to advance their careers in the field of AI. Students have the opportunity to work on real-world projects, allowing them to apply their knowledge in practical settings. The program's duration can vary based on the student's pace, with the average completion time being around two years.

The Computer Science Master's Degree - Machine Learning Track advance the knowledge of machine learning methods and applications might consider the Computer Science Master's Degree - Machine Learning Track. Machine learning is a fast developing field with several applications in a wide range of fields, including bioinformatics, fraud detection, intelligent systems, perception, finance, information retrieval, and other fields.

RFP: Course Development, Online Course in Machine Learning at Scale.

The Master of Information and Data Science program at the School of Information at UC Berkeley seeks proposals for a redeveloped online graduate course in Machine Learning at Scale.

The successful proposal will be accepted for development and offered in the MIDS online degree program.

The existing DATASCI 261. Machine Learning at Scale course was initially developed in 2015, and has been updated several times since then. With the emergence of new deep learning frameworks, and ongoing changes in machine learning approaches, strategies, and infrastructures, the course needs to be substantially updated to remain relevant to state of the art approaches in Scalable ML. Further information the current version of the course is available on request.

Developers should assume students will be proficient programmers in modern programming languages (e.g., Python), have basic familiarity with deep learning frameworks (e.g., PyTorch) and architectures (such as transformers).

Topics covered in the proposed course may include, but are not limited to: scalable ML paradigms such as map-reduce, auto-differentiation, and modular architectures implementation of machine learning algorithms in Apache Spark and PyTorch modern machine learning algorithms, architectures, and multi-task loss functions distributed parallel training and deep learning techniques such as skip connections and attention.

Possible learning objectives for such a course might include:.

Design stateless parallelizable implementations of machine learning algorithms.

Develop and deploy machine learning pipelines at scale in the cloud.

Understand and use automatic differentiation techniques in machine learning deployments.

The successful proposal will be accepted for development and offered in the MIDS online degree program. Since this is a fast-moving field, it is expected that the course contents will be continually revised.

Typically, MIDS courses have 1.5 hours of pre-recorded asynchronous lecture content per week, and 1.5 hours of live, online interactive class time per week.

The Master of Information and Data Science (MIDS) program is an innovative part-time fully online graduate professional degree program that trains data-savvy professionals and managers. The MIDS program is distinguished by its disciplinary breadth unlike other programs that focus on advanced mathematics and modeling alone, the MIDS degree provides students insights from social science and policy research, as well as statistics, computer science and engineering.

Qualifications for teaching this course including past similar courses. It should also include an assessment of whether the current course should be updated or fully overhauled. To make this assessment, the current course materials are available upon request. The current version of the course has a set of pre-recorded asynchronous lectures as well as a set of assignments. The successful applicant will be asked to review which portions should be retained or updated. We are open to partial or complete redevelopment of the course.

A brief description of assignments and how students will be assessed in the course (e.g., weekly work, final project, exam, etc., along with a breakdown of grading in the course) Note: fine details assignments are not needed until a proposal has been accepted.

A description of course infrastructure needs (e.g., cloud credits, platforms like Databricks, datasets, etc.).

A list of which course content should be retained vs.

Designers should assume some resource constraints on course structure, such as limited cloud computing and GPU availability, and are encouraged to design using pedagogical strategies that make the most of campus resources and allow for scalability.

Strong preference will be given to course developers who are interested in continuing their association with the School of Information by applying to teach the developed course as a lecturer.

Course deliverables for accepted proposals will consist of well-designed, reusable presentation slides for async videos and for live classes, topic outlines and activities for classes, and assignments that exercise knowledge and skills learned in the course.

Compensation for course development will be offered via vendor payment from UC Berkeley. This is not a visa opportunity.

The Georgia Institute of Technology provides an online Master of Science in Computer Science program with a specialization in Machine Learning that is designed to impart a comprehensive understanding of machine learning algorithms, statistical modeling, and data analytics to students. The program requires 36 credits and can be completed on a part-time basis in two to three years. But, full-time students required 30 credits and will ne able to complete the program in 24 months.

Students will learn about topics such as supervised and unsupervised learning, natural language processing, and deep learning. The curriculum includes unique courses such as "Reinforcement Learning" and "Big Data for Health Informatics".

The program also offers students the opportunity to work on real-world projects and gain hands-on experience with machine learning tools and techniques. The cost of the program is relatively affordable compared to other similar programs, and it offers a prestigious education from a top-ranked university. Graduates of the program will be well-equipped to pursue careers in areas such as artificial intelligence, data science, and machine learning engineering.

Online Master of Engineering in Artificial Intelligence and Machine Learning.

The online Master of Engineering in Artificial Intelligence and Machine Learning is designed to provide students with an understanding of the advanced algorithms and computational methods that underpin artificial intelligence and machine learning technologies. The program covers a range of topics, including neural networks, natural language processing, computer vision, deep learning, robotics, and autonomous systems. In addition to technical skills, the program emphasizes ethical considerations and the societal impacts of AI technologies.

Graduates of this program are well-prepared for careers in various industries, including technology, finance, healthcare, and transportation. The program also lays a strong foundation for those interested in pursuing research or doctoral studies in these rapidly evolving fields.

The program consists of 10 courses (three credit hours each), totaling 30 required credit hours. Its online structure offers synchronous and asynchronous learning options. This gives students the flexibility to study at their convenience and from any location.

EMSE 6769 Machine Learning for Engineers:Theory and practice of machine learning, leveraging open-source frameworks to explore the ideas, algorithms, and techniques. (3 credit hours).

SEAS 6414 Python Applications in Data Analytics:Introduction to programming with Python with applications in Data Analytics including automating data cleaning, machine learning, text mining, time series analysis, anomaly detection, DoS attack detection, and spam detection. (3 credit hours).

SEAS 6510 Natural Language Processing with Deep Learning:Deep Learning for NLP. Recurrent Neural Networks (RNNs). Long Short-Term Memory (LSTM). Transformers in NLP. Text classification sentiment analysis. Sequence-to-sequence modeling. Attention mechanisms. Word embeddings representation. (3 credit hours).

SEAS 6515 Introduction to Computer Vision:Fundamentals of computer vision. Image processing techniques. Feature extraction methods. Object detection and recognition. Deep learning in computer vision. Convolutional Neural Networks (CNNs). Practical computer vision applications. (3 credit hours).

SEAS 6520 Autonomous Systems Robotics: Delves into the cutting-edge field of intelligent automation, exploring the design, development, and deployment of autonomous systems. Students engage in advanced studies on robotic systems, artificial intelligence algorithms, and sensor integration. (3 credit hours).

SEAS 6599 AI Capstone Project: Propose on a comprehensive AI project, applying acquired skills and knowledge from the program. Demonstrate mastery in AI through project completion and presentation. (3 credit hours).

SEAS 8550 AI, Security, Privacy, and Ethics:Technological basis of ethics in AI. Differentiating humans from machines in AI. Key topics in privacy and ethics of AI, including intrinsic bias and the significance of models. AI and individual responsibility. Addressing legal and regulatory issues. The Cornerstones of AI Security. (3 credit hours).

Students enroll in four 9-week sessions. Students may begin their studies in any of the five sessions.

Course details will be provided to students via email approximately one month prior to the start of classes.

Tuition is $1,200 per credit hour for the 2024-2025 academic year. Tuition is billed at the beginning of each semester for the courses registered during that semester. A non-refundable tuition deposit of $495 is required when the applicant accepts admission. This deposit is applied to tuition and due the first semester. Our online graduate degree programs in engineering require no additional fees. We provide eBooks and software at no additional cost.

Hold a bachelor degree in engineering, computer science, mathematics, physics, or a closely related field from an accredited institution.

Applicants with less than a 2.7 GPA may also apply and may be accepted conditionally based on a holistic review of application materials.

Grade of C or better in one course in college-level calculus and one course in college-level statistics. Special Topics: Quantitative Methods in Engineering Management, during the first year of graduate study.

Apply for AdmissionThere is no application fee for any GW online engineering program.

In an essay of 250 words or less, describe your academic objectives, research interests, and career plans. Also, discuss any other related qualifications not already mentioned, such as collegiate, professional, or community activities.

Official Transcripts: Official transcripts are required from all institutions where a degree was earned.

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A Course Load Made for You, by You.

With just a handful of core courses and a variety of electives to choose from, the program allows you to build a course load based on the AI topics that interest you most and align with your professional goals.

Artificial intelligence is quickly infiltrating every industry. Soon, some form of AI will touch nearly all aspects of daily life. than ever, we need professionals who have the skills to create and implement AI solutions that are both highly effective and ethical.

The Master of Engineering in Applied Artificial Intelligence program available online through the Stevens Institute of Technology is tailor-made for students seeking to enhance their expertise in AI and its practical implementation across diverse domains. The program requires 30 credits and can be completed on a full-time or part-time basis with an online and offline option in 18 months.

Through the program, students will learn about machine learning, deep learning, natural language processing, and computer vision. The curriculum includes unique courses such as "Robotics and Autonomous Systems" and "Human-Centered AI". The program also offers students the opportunity to work on real-world projects and gain hands-on experience with AI tools and techniques. The cost of the program varies depending on the student's residency and whether they are enrolled full-time or part-time. Graduates of the program will be well-prepared to pursue careers in areas such as data science, software engineering, and AI-related fields.

The University of San Diego’s Master of Science in Applied Artificial Intelligence (MS-AAI) is a fully online program designed to be completed in about 20 months, requiring 30 credit hours. This program dives deep into advanced topics like machine learning, neural networks, and AI applications, while also focusing on the ethical dimensions and social impacts of AI.

A unique aspect of the program is the Capstone Project, where students collaborate with peers, instructors, and industry partners on a substantial project that showcases their AI expertise. The curriculum is structured into five semesters, with each semester featuring two courses that last seven weeks, allowing students to focus deeply on one course at a time.

What sets this program apart is its strong emphasis on ethics, social responsibility, and practical applications of AI. It’s one of the few programs in the country that offers a completely online AI degree. The courses are taught by seasoned AI professionals who bring real-world experience to their teaching.

The University of San Diego’s MS-AAI program is accredited both regionally and nationally, which is beneficial for financial aid and credit transfers. It's especially suited for those with backgrounds in science, mathematics, engineering, healthcare, statistics, or technology, and it provides a solid blend of technical skills and practical knowledge, developed in close collaboration with industry and government experts.

The features of the University of San Diego’s MS-AAI program are:

• This is a fully online program.
• The duration of the program is 20 months.
• The program requires a total of 30 credit hours to be completed.
• Rigorous curriculum that includes machine learning, neural networks, and AI applications.
• Strong focus on ethical implications and social impact of AI technologies.
• Accredited by The WASC Senior College and University Commission.

The online Master of Science in Artificial Intelligence & Machine Learning offered by Drexel University is an exceptional program that provides students with a comprehensive understanding of AI and machine learning. With 45 credit hours, this program can be completed entirely online within 2 to 6 years. The program covers a range of subjects, including deep learning, computer vision, natural language processing, machine learning techniques, and ethical issues in AI development.

Additionally, the curriculum gives students the option to further concentrate their studies by selecting elective courses in data science, cybersecurity, or robotics. One unique feature of this program is the opportunity for students to work on real-world projects, which will enable them to apply their knowledge and skills to solve practical problems. During the program, students get the opportunity to study with knowledgeable professors and use cutting-edge hardware and software.