The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events Specialist
Advance your skills up the technology curve to solve more complex problems using AI-driven solutions.
Download Brochure
March 27, 2025
10 weeks, online
8-10 hours per week
Participants report that enrolling in a program with colleagues fosters collaborative learning and amplifies their impact.
Please provide your details to get more information about the group-enrollment pricing.
The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events SpecialistFeeling the pinch from seismic disruptions across all lines of business, organizations are fast-tracking AI projects and are thirsty for solutions to their most pressing challenges. IDC forecasts the AI market will break the $500 billion mark by 2024. This signals that the race for AI-capable talent is on.
This program is designed to provide a comprehensive overview of AI in both theory and practice with a focus on modern computational techniques for representing task-relevant information and making intelligent decisions. As a participant, you’ll develop AI problem-solving skills that are applicable across a large range of information systems to help you and your organization stay competitive in this rapidly evolving landscape.
SOURCE: U.S. NEWS & WORLD REPORT
This 10-week online program is designed to provide software developers, data science professionals, and other professionals aiming to advance their technical AI skills, allowing them to solve more complex challenges and add more value to their organization.
Participants who complete the program will be prepared to:
Structured as an online program, content is shared via live and recorded faculty videos and office hours with learning facilitators.
Leverage search techniques as a really powerful AI tool to help you find a set of actions that would take you from a starting state to a goal state.
Learn to translate a problem from an English statement into something AI can understand as you construct state and action representations for complex search problems and describe how they affect search performance.
Formulate a problem as a set of constraints and an objective and apply relevant algorithms to find a solution efficiently. Identify when the objective is to solve for a set of values and apply strategies to accomplish this goal.
Consider that many aspects of the world are probabilistic and evaluate how to translate that in AI. Demonstrate familiarity with probabilistic approaches to AI and implement algorithms to solve probabilistic sequential decision problems.
Reflect on machine learning (ML) as a popular approach employed to help businesses understand their data. Evaluate ML as a technique for finding patterns in data and explore popular ML algorithms and their corresponding data requirements.
Consider the many nuances to training and evaluating ML algorithms and explore the various ideas to help train better ML models. Analyze tuning hyperparameters that affect model performance and evaluate models properly.
Recognize that real-world problems have state spaces that are infeasible to search systematically. Demonstrate the applicability of randomized search techniques and understand when such approaches are appropriate to use.
Evaluate information retrieval and other AI technology behind search engines, personal assistants, and other question answering systems. Analyze recommender systems as a common AI application utilized in movie or music selection or for items to purchase.
Appreciate that AI systems do not act in a vacuum; they are typically completing tasks for or with people. Consider common approaches to integrating human feedback into AI systems and review current trends and challenges in AI systems that interact with people.
Evaluate the emerging use of AI in systems that can operate autonomously. Reflect on how reliably achieving complex tasks in dynamic environments is difficult and requires the careful integration of numerous AI techniques.
Leverage search techniques as a really powerful AI tool to help you find a set of actions that would take you from a starting state to a goal state.
Consider the many nuances to training and evaluating ML algorithms and explore the various ideas to help train better ML models. Analyze tuning hyperparameters that affect model performance and evaluate models properly.
Learn to translate a problem from an English statement into something AI can understand as you construct state and action representations for complex search problems and describe how they affect search performance.
Recognize that real-world problems have state spaces that are infeasible to search systematically. Demonstrate the applicability of randomized search techniques and understand when such approaches are appropriate to use.
Formulate a problem as a set of constraints and an objective and apply relevant algorithms to find a solution efficiently. Identify when the objective is to solve for a set of values and apply strategies to accomplish this goal.
Evaluate information retrieval and other AI technology behind search engines, personal assistants, and other question answering systems. Analyze recommender systems as a common AI application utilized in movie or music selection or for items to purchase.
Consider that many aspects of the world are probabilistic and evaluate how to translate that in AI. Demonstrate familiarity with probabilistic approaches to AI and implement algorithms to solve probabilistic sequential decision problems.
Appreciate that AI systems do not act in a vacuum; they are typically completing tasks for or with people. Consider common approaches to integrating human feedback into AI systems and review current trends and challenges in AI systems that interact with people.
Reflect on machine learning (ML) as a popular approach employed to help businesses understand their data. Evaluate ML as a technique for finding patterns in data and explore popular ML algorithms and their corresponding data requirements.
Evaluate the emerging use of AI in systems that can operate autonomously. Reflect on how reliably achieving complex tasks in dynamic environments is difficult and requires the careful integration of numerous AI techniques.
Office Hours with Learning Facilitators
Knowledge Checks
Dedicated Program Support Team
Case Studies
Programming Assignments
Discussion Boards
Wikis/Crowdsourced Activities
Scenario and Problem-based Learning
Software Developers/Technology Professionals seeking to gain a foundational understanding of AI processes and apply them in their work.
Data Science Professionals looking to develop an understanding of modern computational techniques for developing AI-based solutions.
Other Professionals who want to develop decision support systems (such as medical support or recommender systems), plan and monitor AI systems, develop mixed initiatives, and bring humans into the AI loop.
PREREQUISITES: Functional knowledge of calculus, linear algebra, probability, and statistics is beneficial. Participants should also have a working-level knowledge of Python, algorithm design, and data structures.
Take a self-assessment test to verify your readiness for the math and Python content in this program.
Stephanie Rosenthal
Reid Simmons
Stephanie Rosenthal
Assistant Teaching Professor, Carnegie Mellon University School of Computer Science
Stephanie Rosenthal is an Assistant Teaching Professor at Carnegie Mellon University School of Computer Science. She has many years of experience in higher education, teaching robotics, artificial intelligence, and applied data analytics. Her practitioner experience includes industry and government, with organizations such as Microsoft, Intel, the Department of Defense, and a robotics startup. Her research on AI and human–computer interaction aim to improve the decision making and performance of intelligent systems. She holds a PhD in Computer Science from Carnegie Mellon University.
Reid Simmons
Research Professor and Director of the Bachelor Science in Artificial Intelligence (BSAI), Carnegie Mellon University, School of Computer Science
Reid Simmons is a Research Professor and Director of the BSAI at Carnegie Mellon University School of Computer Science. As head of the Reliable Autonomous Systems Lab, the research investigates developing reliable, highly autonomous systems (especially mobile robots) that operate in rich, uncertain environments. As well as being a research professor at CMU, he served as Program Director at the National Science Foundation, overseeing the National Robotics Initiative and Smart and Autonomous Systems programs. He has contributed to hundreds of publications related to AI and has several decades of research experience in the field. He holds a PhD in Artificial Intelligence from the Massachusetts Institute of Technology (MIT).
Throughout the program, you’ll have the opportunity to apply your understanding of the content by completing computational problems and evaluating AI applications and methods in the context of practical problems. Example exercises include:
Upon successful completion of the program, participants will receive a verified digital certificate of completion from Carnegie Mellon University School of Computer Science Executive Education. This is a training program and it is not eligible for academic credit.
Download BrochureYour digital certificate will be issued in your legal name and emailed to you at no additional cost, upon completion of the program, per the stipulated requirements. All certificate images are for illustrative purposes only and may be subject to change at the discretion of Carnegie Mellon University’s School of Computer Science Executive Education.
After reviewing the information on the program landing page, we recommend you submit the short form above to gain access to the program brochure, which includes more in-depth information. If you still have questions on whether this program is a good fit for you, please email learner.success@emeritus.org, and a dedicated program advisor will follow-up with you very shortly.
Some programs do have prerequisites, particularly the more technical ones. This information will be noted on the program landing page, as well as in the program brochure. If you are uncertain about program prerequisites and your capabilities, please email us at the ID mentioned above.
Note that, unless otherwise stated on the program web page, all programs are taught in English and proficiency in English is required.
More than 50 percent of our participants are from outside the United States. Class profiles vary from one cohort to the next, but, generally, our online certificates draw a highly diverse audience in terms of professional experience, industry, and geography — leading to a very rich peer learning and networking experience.
Check back to this program web page or email us to inquire if future program dates or the timeline for future offerings have been confirmed yet.
Each program includes an estimated learner effort per week. This is referenced at the top of the program landing page under the Duration section, as well as in the program brochure, which you can obtain by submitting the short form at the top of this web page.
We have designed this program to fit into your current working life as efficiently as possible. Time will be spent among a variety of activities including:
The program is designed to be highly interactive while also allowing time for self-reflection and to demonstrate an understanding of the core topics through various active learning exercises. Please email us if you need further clarification on program activities.
More than 300,000 learners across 200 countries have chosen to advance their skills with Emeritus and its educational learning partners. In fact, 90 percent of the respondents of a recent survey across all our programs said that their learning outcomes were met or exceeded.
All the contents of the course would be made available to students at the commencement of the course. However, to ensure the program delivers the desired learning outcomes the students may appoint Emeritus to manage the delivery of the program in a cohort-based manner the cost of which is already included in the overall course fee of the course.
A dedicated program support team is available 24/5 (Monday to Friday) to answer questions about the learning platform, technical issues, or anything else that may affect your learning experience.
Peer learning adds substantially to the overall learning experience and is an important part of the program. You can connect and communicate with other participants through our learning platform.
Each program includes an estimated learner effort per week, so you can gauge what will be required before you enroll. This is referenced at the top of the program landing page under the Duration section, as well as in the program brochure, which you can obtain by submitting the short form at the top of this web page. All programs are designed to fit into your working life.
This program is scored as a pass or no-pass; participants must complete the required activities to pass and obtain the certificate of completion. Some programs include a final project submission or other assignments to obtain passing status. This information will be noted in the program brochure. Please email us if you need further clarification on any specific program requirements.
Upon successful completion of the program, you will receive a smart digital certificate. The smart digital certificate can be shared with friends, family, schools, or potential employers. You can use it on your cover letter, resume, and/or display it on your LinkedIn profile.
The digital certificate will be sent approximately two weeks after the program, once grading is complete.
No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social platforms such as LinkedIn, Facebook, and Twitter.
No, there is no alumni status granted for this program. In some cases, there are credits that count toward a higher level of certification. This information will be clearly noted in the program brochure.
You will have access to the online learning platform and all the videos and program materials for 12 months following the program start date. Access to the learning platform is restricted to registered participants per the terms of agreement.
Participants will need the latest version of their preferred browser to access the learning platform. In addition, Microsoft Office and a PDF viewer are required to access documents, spreadsheets, presentations, PDF files, and transcripts.
Yes, the learning platform is accessed via the internet, and video content is not available for download. However, you can download files of video transcripts, assignment templates, readings, etc. For maximum flexibility, you can access program content from a desktop, laptop, tablet, or mobile device.
Video lectures must be streamed via the internet, and any livestream webinars and office hours will require an internet connection. However, these sessions are always recorded, so you may view them later.
Yes, you can register up until seven days past the published start date of the program without missing any of the core program material or learnings.
The program fee is noted at the top of this program web page and usually referenced in the program brochure as well.
Yes, you can do the bank remittance in the program currency via wire transfer or debit card. Please contact your program advisor, or email us for details.
Yes! Please email us with the details of the program you are interested in, and we will assist you.
Please email us your invoicing requirements and the specific program you’re interested in enrolling in.
Yes, the flexible payment option allows a participant to pay the program fee in installments. This option is made available on the payment page and should be selected before submitting the payment.
Please connect with us via email for assistance.
Emeritus collects all program payments, provides learner enrollment and program support, and manages learning platform services.
Program fees for Emeritus programs with Carnegie Mellon University’s School of Computer Science Executive Education may not be paid for with (a) funds from the GI Bill, the Post-9/11 Educational Assistance Act of 2008, or similar types of military education funding benefits or (b) Title IV financial aid funds.
For the program refund and deferral policy, please click the link here.
Flexible payment options available.