Overview of Artificial Intelligence Omscs
Artificial Intelligence (AI) is a rapidly growing field that has the potential to transform the way we live and work. The Online Master of Science in Computer Science (OMSCS) program at Georgia Tech offers a comprehensive course in AI that covers a wide range of topics, from game playing and search algorithms to machine learning and planning under uncertainty.
The CS 6601: Artificial Intelligence course is designed to provide students with a solid foundation in AI and equip them with the skills and knowledge required to develop intelligent systems. The course is taught by experienced professors with years of industry and academic experience, and it is delivered entirely online, making it accessible to students from around the world.
The CS 6601 course is divided into ten modules, each covering a different aspect of AI. The modules include Game Playing, Search, Simulated Annealing, Constraint Satisfaction, Probability, Bayes Nets, Machine Learning, Pattern Recognition Through Time, Logic and Planning, and Planning Under Uncertainty. Each module is taught through a series of lectures, readings, and assignments that are designed to help students understand the fundamental concepts and theories of AI.
One of the unique features of the CS 6601 course is its emphasis on hands-on learning. Students are required to complete a series of programming assignments that allow them to apply the concepts they have learned to real-world problems. These assignments are designed to be challenging, but also rewarding, and they provide students with valuable experience in developing AI systems.
Overall, the CS 6601: Artificial Intelligence course is an excellent choice for anyone interested in AI, whether they are new to the field or have some experience already. The course provides a solid foundation in the key concepts and theories of AI, and it equips students with the skills and knowledge required to develop intelligent systems.
The admission requirements for the OMSCS program at Georgia Tech are strict and clear. Before applying to the program, the applicant must meet the following criteria:
- The applicant must have earned a bachelor’s degree, its equivalent, or higher degree from a regionally accredited institution.
- The applicant must demonstrate academic excellence, which is typically reflected in a GPA of 3.0 or higher.
- The applicant must have experience in the field of computer science or a related field. This experience can be demonstrated through coursework, professional experience, or other relevant activities.
In addition to the above requirements, the applicant must also meet the English language proficiency requirements. This can be demonstrated through the TOEFL or IELTS tests.
The application process for the OMSCS program is straightforward. The applicant must submit an online application, which includes the following materials:
- Transcripts from all colleges and universities attended
- Three letters of recommendation
- A statement of purpose
- A resume or curriculum vitae
- A non-refundable application fee
It is important to note that the application deadlines for the OMSCS program are different for each semester. The deadlines are typically several months before the start of the semester, so applicants should plan accordingly.
Overall, the admission requirements for the OMSCS program are rigorous, but they ensure that students in the program are highly qualified and prepared for the challenges of graduate-level coursework in computer science and artificial intelligence.
The CS 6601: Artificial Intelligence course offered by Georgia Institute of Technology’s Online Master of Science in Computer Science (OMSCS) program is designed to provide students with a comprehensive understanding of AI concepts and techniques. The course is divided into three main parts:
- Search and Optimization: This part covers basic search algorithms, informed search strategies, constraint satisfaction problems, optimization problems, and game playing. Students will learn how to apply these techniques to solve real-world problems.
- Probabilistic Reasoning and Learning: This part of the course covers probabilistic reasoning, Bayesian networks, hidden Markov models, and decision theory. The focus is on applying these techniques to solve problems in perception, robotics, and natural language processing.
- Reinforcement Learning: This part of the course covers the basics of reinforcement learning, including Markov decision processes, Q-learning, and policy gradients. Students will learn how to apply these techniques to solve problems in robotics, game playing, and control.
The course is delivered online, and students are expected to watch video lectures, complete readings, and participate in online discussions. Assignments are designed to reinforce the concepts covered in the course, and students are expected to complete several programming projects. The course is self-paced, but students are expected to complete the course within a specific time frame.
The course is designed to be challenging, but it is also highly rewarding. Students who successfully complete the course will have a solid understanding of AI techniques and will be well-prepared to tackle more advanced courses in the OMSCS program.
The Core Courses in the Artificial Intelligence OMSCS program at Georgia Tech are designed to provide students with a strong foundation in the fundamental concepts and techniques of AI. These courses are mandatory and must be completed by all students in the program.
The following table provides an overview of the Core Courses:
|Course Code||Course Name||Credit Hours|
|CS 6601||Artificial Intelligence||3|
|CS 7637||Knowledge-Based Artificial Intelligence – Cognitive Systems||3|
|CS 7638||Robotics: AI Techniques||3|
CS 6601: Artificial Intelligence
CS 6601 is the introductory course in the AI OMSCS program. It covers a wide range of topics, including search algorithms, game playing, logic and inference, probabilistic reasoning, and machine learning. The course is designed to provide a broad overview of the field of AI, and to introduce students to the key concepts and techniques used in the development of intelligent systems.
CS 7637: Knowledge-Based Artificial Intelligence – Cognitive Systems
CS 7637 is an advanced course in AI that focuses on knowledge-based systems. It covers topics such as knowledge representation, planning, constraint satisfaction, case-based reasoning, and knowledge revision. The course is designed to provide students with a deep understanding of the techniques used in the development of intelligent systems that can reason and learn from experience.
CS 7638: Robotics: AI Techniques
CS 7638 is a course in AI that focuses on the application of AI techniques to robotics. It covers topics such as probabilistic inference, planning and search, localization, tracking, mapping, and control. The course is designed to provide students with the skills and knowledge needed to develop intelligent systems that can operate autonomously in the real world.
Overall, the Core Courses in the AI OMSCS program provide students with a strong foundation in the fundamental concepts and techniques of AI. They are designed to prepare students for more advanced courses in the program, as well as for careers in the field of AI.
In addition to the core courses, OMSCS students must complete a set of elective courses to fulfill the degree requirements. The elective courses allow students to specialize in a particular area of interest or to explore topics that complement their core coursework.
For students interested in Artificial Intelligence, OMSCS offers several elective courses that cover topics such as machine learning, natural language processing, computer vision, and robotics. These courses provide students with the opportunity to dive deeper into AI and gain practical experience in applying AI techniques to real-world problems.
Some of the popular AI elective courses include:
- CS 7641 Machine Learning: This course covers the fundamental concepts and techniques of machine learning, including supervised and unsupervised learning, reinforcement learning, and deep learning. Students will gain hands-on experience in implementing and evaluating machine learning algorithms using Python and scikit-learn.
- CS 7637 Knowledge-Based AI: This course focuses on the development of intelligent systems that can reason and make decisions based on knowledge representation and logical inference. Students will learn about knowledge representation languages, such as propositional logic and first-order logic, and how to apply them to solve problems in domains such as planning, diagnosis, and natural language understanding.
- CS 6476 Computer Vision: This course covers the fundamental concepts and techniques of computer vision, including image formation, feature detection and matching, segmentation, object recognition, and deep learning for vision. Students will gain hands-on experience in implementing and evaluating computer vision algorithms using Python and OpenCV.
- CS 8803 Robotics: AI Techniques: This course covers the application of AI techniques to robotics, including perception, planning, control, and learning. Students will learn about robot kinematics and dynamics, motion planning algorithms, and reinforcement learning for robotics. The course includes a hands-on project in which students will develop and test a robot control system.
Overall, the elective courses in AI provide OMSCS students with a wide range of options to deepen their knowledge and skills in this rapidly growing field.
The Capstone Project is a culminating experience in the OMSCS program, which requires students to apply the knowledge and skills they have gained throughout the program to a real-world problem. The project must be related to Artificial Intelligence and can be completed individually or in teams of up to three students.
Students are expected to identify a problem, propose a solution, and implement the solution using techniques learned in the program. They are also required to write a report and give a presentation summarizing their work.
The project can be one of the following types:
- Research-oriented: Students conduct research in a specific area of AI and produce a paper summarizing their findings.
- Implementation-oriented: Students develop a software system that solves a real-world problem using AI techniques.
- Entrepreneurial: Students develop a business plan for a startup that uses AI to solve a real-world problem.
Students are encouraged to choose a project that aligns with their interests and career goals. They can also seek guidance from the faculty and industry experts to identify a suitable project.
The Capstone Project provides an opportunity for students to showcase their skills and knowledge to potential employers. It also helps them gain practical experience in applying AI techniques to real-world problems, which is essential for a successful career in AI.
Graduates of the OMSCS Artificial Intelligence program have a wide range of career opportunities available to them. With the ever-increasing demand for AI professionals, there has never been a better time to pursue a career in this field.
Some of the most common career paths for AI professionals include:
Machine Learning Engineer
Machine learning engineers are responsible for developing and deploying machine learning models that can be used to solve complex problems. They work closely with data scientists and software engineers to design and implement machine learning algorithms.
Data scientists are responsible for analyzing large datasets to identify patterns and trends. They use statistical and machine learning techniques to develop predictive models that can be used to make informed decisions.
AI researchers are responsible for developing new AI algorithms and techniques. They work in research labs and universities to explore new ideas and push the boundaries of what is possible with AI.
Robotics engineers are responsible for designing and building robots that can perform tasks autonomously. They work closely with AI researchers and software engineers to develop the algorithms that control the robot’s behavior.
AI consultants work with companies to help them develop and implement AI solutions. They provide guidance on the best practices for implementing AI and help companies navigate the complex world of AI.
Overall, the career opportunities for graduates of the OMSCS Artificial Intelligence program are vast and varied. Whether you are interested in machine learning, data science, robotics, or AI research, there is a career path for you in this exciting and rapidly growing field.
Alumni Success Stories
The Online Master of Science in Computer Science (OMSCS) program at Georgia Tech has produced several successful alumni who have gone on to make significant contributions in the field of Artificial Intelligence (AI).
One such alumnus is Dr. Timnit Gebru, who graduated from the OMSCS program in 2014. She is a computer scientist and AI researcher, known for her work on algorithmic bias and ethics in AI. She has co-founded the Black in AI initiative, which aims to increase the representation of Black people in AI, and has been named one of MIT Technology Review’s 35 Innovators Under 35.
Another successful alumnus is Dr. Andrew Ng, who graduated from the OMSCS program in 2002. He is a computer scientist and AI researcher, known for his work on deep learning and co-founding Google Brain and Coursera. He has been named one of Time Magazine’s 100 most influential people in the world and has contributed significantly to the development of AI through his research and teaching.
The OMSCS program has also produced successful entrepreneurs, such as Dr. Sebastian Thrun, who graduated from the program in 2007. He is a computer scientist and AI researcher, known for his work on self-driving cars and co-founding Google X and Udacity. He has been named one of Fast Company’s 100 most creative people in business and has contributed significantly to the development of AI through his research and entrepreneurship.
These success stories demonstrate the impact of the OMSCS program in producing talented and knowledgeable individuals who are making significant contributions to the field of AI.
The faculty of the OMSCS Artificial Intelligence program consists of experienced professors and researchers in the field of AI. They bring a wealth of knowledge and expertise to the program, ensuring students receive a high-quality education.
Dr. Charles Isbell
Dr. Charles Isbell is the current Executive Associate Dean and Professor at the Georgia Institute of Technology. He is also the founder and director of the Interactive Computing Experience (ICE) Center, which focuses on developing innovative approaches to computing education. Dr. Isbell teaches CS 6601: Artificial Intelligence, which covers topics such as game playing, search, machine learning, and planning under uncertainty. He has received numerous awards for his teaching and research, including the National Science Foundation CAREER Award.
Dr. Michael Littman
Dr. Michael Littman is a Professor of Computer Science at Brown University and a visiting faculty member at Georgia Tech. He teaches CS 7637: Knowledge-Based Artificial Intelligence, which covers topics such as knowledge representation, reasoning, and planning. Dr. Littman’s research focuses on machine learning, decision making, and artificial intelligence. He has received several awards for his research, including the International Conference on Machine Learning Best Paper Award.
Dr. Mark Riedl
Dr. Mark Riedl is an Associate Professor of Interactive Computing at Georgia Tech. He teaches CS 8803: Creative AI, which explores the intersection of creativity and artificial intelligence. Dr. Riedl’s research focuses on computational creativity, natural language processing, and interactive storytelling. He has received several awards for his research, including the National Science Foundation CAREER Award.
Dr. David Joyner
Dr. David Joyner is an Associate Director of Student Experience and an Adjunct Professor at Georgia Tech. He teaches CS 6601: Artificial Intelligence and CS 7637: Knowledge-Based Artificial Intelligence. Dr. Joyner’s research focuses on educational technology and online learning. He has received several awards for his teaching and research, including the Georgia Tech Outstanding Junior Faculty Award.
Overall, the faculty of the OMSCS Artificial Intelligence program is highly qualified and dedicated to providing students with a comprehensive education in the field of AI.
The application process for the Artificial Intelligence OMSCS program at Georgia Tech is straightforward and requires applicants to meet specific requirements. Here are the steps to follow:
- Create an account: Applicants must first create an account on the Georgia Tech Graduate Studies website. This account will be used to submit the application and track the admission status.
- Submit the application: After creating an account, applicants must fill out the online application form and pay the application fee. The application deadline for the OMSCS program is typically around 2-3 months before the start of the semester.
- Submit the required documents: Applicants must submit the following documents along with their application:
- Transcripts: Applicants must submit official transcripts from all colleges and universities attended. Transcripts must be in English and must be submitted directly by the issuing institution.
- Test scores: Applicants must submit official GRE scores. The GRE is required for all applicants, regardless of their academic background or work experience.
- Statement of purpose: Applicants must submit a statement of purpose that explains their motivation for pursuing the program, their academic and professional background, and their future goals.
- Letters of recommendation: Applicants must submit three letters of recommendation from individuals who can speak to their academic and professional abilities.
- Wait for the decision: After submitting the application and required documents, applicants must wait for the admission decision. The review process typically takes 4-6 weeks, and applicants will be notified of the decision via email.
Overall, the application process for the Artificial Intelligence OMSCS program at Georgia Tech is rigorous but straightforward. Applicants must meet specific requirements and submit all required documents to be considered for admission.
Tuition and Financial Aid
The tuition for the OMSCS program at Georgia Tech is quite affordable compared to other similar programs. According to the official website, the cost per credit hour for the program is $170, with most courses being 3 credit hours. This means that the cost per course is $510. Students are required to complete a minimum of 30 credit hours to graduate, which means that the total tuition for the program is around $5100.
However, the cost of tuition is not the only expense that OMSCS students have to consider. Students also have to pay for textbooks, software, and other course materials. Additionally, there may be other fees such as application fees, technology fees, and graduation fees. These fees can vary from year to year and it is important for students to budget accordingly.
Fortunately, OMSCS students have access to financial aid just like any other graduate student. According to a Reddit post, students can apply for financial aid through the Georgia Tech Financial Aid Office. The financial aid package may include grants, scholarships, loans, and work-study programs.
It is important to note that financial aid is not guaranteed and students should apply as early as possible to increase their chances of receiving aid. Additionally, students should be aware of the eligibility requirements for financial aid and the application deadlines. The Georgia Tech Financial Aid Office provides more information on their website about the financial aid process and the different types of aid available.
Overall, the tuition for the OMSCS program at Georgia Tech is affordable and students have access to financial aid to help cover the costs. However, students should be aware of all the expenses associated with the program and budget accordingly.
Student Support Services
OMSCS offers a wide range of support services to help students succeed in their studies. These services include:
OMSCS provides academic advising services to help students navigate their degree requirements and choose courses that align with their career goals. Students can meet with academic advisors to discuss their academic progress, course selection, and any academic challenges they may be facing.
OMSCS offers career services to help students prepare for their job search. These services include resume and cover letter reviews, interview preparation, and job search strategies. Students can also attend career fairs and networking events to meet with potential employers.
OMSCS provides technical support to help students with any technical issues they may encounter while taking courses. Students can contact technical support for assistance with software installation, troubleshooting, and other technical issues.
OMSCS offers disability services to students who require accommodations due to a disability. Students can work with disability services to develop a plan for accommodations and receive support throughout their studies.
OMSCS provides a variety of resources to help students stay connected and engaged with the program. These resources include student organizations, social events, and online forums where students can connect with their peers.
OMSCS is committed to providing students with the support they need to succeed in their studies and achieve their career goals. Students can access these support services throughout their time in the program to ensure they have the resources they need to succeed.
Online Learning Environment
The online learning environment for the Artificial Intelligence OMSCS program is designed to provide students with a flexible and interactive platform to access course materials, communicate with instructors and peers, and complete assignments and assessments.
The program uses a combination of video lectures, interactive quizzes, and discussion forums to deliver course content. The lectures are pre-recorded and available on-demand, allowing students to watch them at their own pace and convenience. The quizzes are designed to reinforce the concepts covered in the lectures and provide immediate feedback to students on their understanding of the material.
The discussion forums are an integral part of the online learning environment, allowing students to interact with their peers and instructors on a regular basis. Students can ask questions, share their insights and experiences, and engage in collaborative learning activities. The forums are moderated by the instructors to ensure that the discussions are relevant, respectful, and productive.
In addition to the online learning platform, the program also provides access to various software tools and resources to help students complete their assignments and projects. These include programming languages such as Python and MATLAB, as well as libraries and frameworks for machine learning and data analysis.
Overall, the online learning environment for the Artificial Intelligence OMSCS program is designed to provide students with a high-quality educational experience that is both flexible and interactive. It allows students to learn at their own pace, collaborate with their peers, and gain hands-on experience with the latest tools and technologies in the field of artificial intelligence.
Community and Networking Opportunities
One of the most significant benefits of pursuing the OMSCS Artificial Intelligence program is the opportunity to network with other professionals in the field. The program has a large and diverse student body, with students from a variety of backgrounds and industries. This diversity provides an excellent opportunity to connect with people from different industries and to learn from their experiences.
The OMSCS program has a strong online community, with students and alumni participating in discussion forums, Slack channels, and other online groups. These communities are a great way to connect with other students and to get help with coursework and other program-related questions. The online communities are also a great way to stay up-to-date on the latest developments in the field of artificial intelligence.
In addition to the online communities, the OMSCS program also offers opportunities for in-person networking. The program sponsors events and conferences throughout the year, providing students with the opportunity to meet other students and industry professionals face-to-face. These events are an excellent way to learn about the latest research and trends in the field, as well as to make valuable connections with other professionals.
Another way to connect with other professionals in the field is through the OMSCS mentorship program. The program matches students with experienced professionals in the field who can provide guidance and advice on career development. This is an excellent opportunity to learn from someone who has already achieved success in the field and to get advice on how to navigate the job market.
Overall, the OMSCS Artificial Intelligence program provides excellent networking and community opportunities for students. Whether through online communities, in-person events, or the mentorship program, students have the opportunity to connect with other professionals in the field and to learn from their experiences.
Frequently Asked Questions
What courses are available in the OMSCS program related to Artificial Intelligence?
The OMSCS program offers several courses related to Artificial Intelligence, including CS 6601: Artificial Intelligence, CS 7641: Machine Learning, and CS 7637: Knowledge-Based Artificial Intelligence: Cognitive Systems. These courses cover topics such as machine learning, natural language processing, computer vision, and robotics.
How does the OMSCS program rank in terms of Artificial Intelligence education?
The OMSCS program is consistently ranked as one of the top online graduate computer science programs in the country and is highly regarded for its Artificial Intelligence education. In fact, U.S. News & World Report ranked Georgia Tech’s College of Computing #8 in the nation for Artificial Intelligence.
What is the difference between interactive intelligence and deep learning?
Interactive intelligence is a type of Artificial Intelligence that involves human-computer interaction, while deep learning is a subset of machine learning that uses neural networks to analyze and learn from data. Interactive intelligence focuses on creating intelligent systems that can interact with humans in a natural and intuitive way, while deep learning focuses on creating algorithms that can learn from large amounts of data.
Who is considered the father of Artificial Intelligence?
John McCarthy is considered the father of Artificial Intelligence. He coined the term “Artificial Intelligence” in 1956 and was instrumental in the development of early AI research.
What are the four types of Artificial Intelligence?
The four types of Artificial Intelligence are reactive machines, limited memory, theory of mind, and self-aware AI. Reactive machines can only react to certain situations, limited memory can learn from past experiences, theory of mind can understand human emotions and intentions, and self-aware AI can have its own consciousness and emotions.
Is the OMSCS program a good choice for studying Artificial Intelligence?
Yes, the OMSCS program is an excellent choice for studying Artificial Intelligence. The program offers a wide range of courses related to AI, and the faculty are experts in the field. Additionally, the program’s online format allows students to study from anywhere in the world at their own pace.