Artificial Intelligence

Advance your skills up the technology curve to solve more complex problems using AI-driven solutions.

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Course Dates

STARTS ON

January 31, 2023

Course Duration

DURATION

10 weeks, online
8-10 hours per week

Course Fee

PROGRAM FEE

US$2,500 US$2,125 or get US$250 off with a referral

Course Information Flexible payment available
Course Fee

For Your Team

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Unlock Your Potential

Invest in yourself and realize your potential. Emeritus is partnering with Carnegie Mellon University School of Computer Science Executive Education to bring you an opportunity to unlock career growth. Enroll before , and get 15% early registration benefit to set yourself up for professional success.

Application Details

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US$2,500 US$2,125

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Team-Based Learning Options

  • Enroll as a team or group and learn with your peers

  • Receive support and services

  • Inquire about special team/group pricing

  • ENROLL YOUR TEAM

    Emeritus works with leading companies to close critical skills gaps


    Our partners include

    JP Morgan
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Get the AI Skills to Advance Your Organization and Your Career

Feeling 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.

Carnegie Mellon University is ranked #1 in Artificial Intelligence Specialty and Graduate Programs for Computer Science

SOURCE: U.S. NEWS & WORLD REPORT

Key Outcomes

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:

  • Translate a problem from an English statement into something an AI-based system can understand.
  • Learn techniques that search for solutions in high-dimensional spaces, including randomized approaches to search.
  • Formulate a problem as a set of constraints and an objective, and apply the most appropriate algorithms to find an efficient solution.
  • Evaluate the implementation of recommender systems, search engines, personal assistants, and other AI technologies.
  • Analyze common approaches for integrating human feedback into AI systems and next-level thinking around human-computer interactions.
  • Evaluate the ethical and societal implications of the field of AI

Program Modules

Structured as an online program, content is shared via live and recorded faculty videos and office hours with learning facilitators.

Module 1:

Search

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.

Module 2:

State and Action Representation

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.

Module 3:

Constraint Satisfaction

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.

Module 4:

Probability and Markov Processes

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.

Module 5:

Machine Learning Models

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.

Module 6:

Practical Machine Learning

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.

Module 7:

Randomized Algorithms

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.

Module 8:

Common AI Applications

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.

Module 9:

Human-AI Interaction

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.

Module 10:

Autonomous Agents

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.

Module 1:

Search

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.

Module 6:

Practical Machine Learning

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.

Module 2:

State and Action Representation

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.

Module 7:

Randomized Algorithms

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.

Module 3:

Constraint Satisfaction

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.

Module 8:

Common AI Applications

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.

Module 4:

Probability and Markov Processes

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.

Module 9:

Human-AI Interaction

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.

Module 5:

Machine Learning Models

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.

Module 10:

Autonomous Agents

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.

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Program Experience

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Office Hours with Learning Facilitators

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Knowledge Checks

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Dedicated Program Support Team

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Case Studies

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Programming Assignments

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Discussion Boards

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Wikis/Crowdsourced Activities

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Scenario and Problem-based Learning

Who Should Attend

This program is designed for participants interested in expanding their technical understanding of AI principles and how to solve more complex problems using these tools and techniques. This program may be most suitable for the following:

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.

Program Faculty

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... More info

Faculty Member Reid Simmons

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... More info

Program Exercises

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:

  • Define a search problem and apply it to the Candy Grab game (defining game state and actions)
  • Use adversarial search and the minimax algorithm to identify a winning strategy for the Candy Grab game and rewarding players
  • Define variables, domains, and constraints in a Constraint Satisfaction Problem (CSP)
  • Run a search to find a solution to a CSP
  • Apply heuristics (Minimum Remaining Values (MRV) and Least Constraining Value (LCV)) to a CSP

Visual Case Study: Human-AI Interaction

As part of an original visual case study, you will deploy a new AI application for use in hospitals.

  • Immerse yourself in a simulated environment where you define considerations for an AI system interacting with humans, ensuring the deployment is both usable and explainable, transparent, fair, and ethical.
  • Explore various scenarios to support decision making as you build the AI application.
  • Present a business case to deploy this AI application at the end of the module.

Certificate

Example image of certificate that will be awarded after successful completion of this program

Certificate

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.

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Your 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.

The Carnegie Mellon School of Computer Science Executive Education learning experience

At Carnegie Mellon’s Executive Education Program in the School of Computer Science, we provide organizations and people access to the skills and tools necessary to solve real world technical problems by equipping the next generation of technology leaders with the experience, insights and novel solutions developed by our community of computer science experts. From custom training programs to online individualized learning, our cutting-edge programming — backed by faculty who pioneered the field — takes your skillset to the next level, giving you the tools to tackle your company’s next great technological challenge.

FAQs

  • How do I know if this program is right for me?

    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.


    Are there any prerequisites for this program?

    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 learner.success@emeritus.org for assistance.


    Note that, unless otherwise stated on the program web page, all programs are taught in English and proficiency in English is required.


    What is the typical class profile?

    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.


    What other dates will this program be offered in the future?

    Check back to this program web page or email us at learner.success@emeritus.org to inquire if future program dates or the timeline for future offerings have been confirmed yet.

  • How much time is required each week?

    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.



    How will my time be spent?

    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:



    • Engaging with recorded video lectures from faculty
    • Attending webinars and office hours, as per the specific program schedule
    • Reading or engaging with examples of core topics
    • Completing knowledge checks/quizzes and required activities
    • Engaging in moderated discussion groups with your peers
    • Completing your final project, if required

    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 contact us at learner.success@emeritus.org if you need further clarification on program activities.



    What is it like to learn online with the learning collaborator, Emeritus?

    More than 250,000 professionals globally, across 80 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.

    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.


    How do I interact with other program participants?

    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.

  • What are the requirements to earn the certificate?

    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 contact us at learner.success@emeritus.org if you need further clarification on any specific program requirements.


    What type of certificate will I receive?

    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.


    Can I get the hard copy of the certificate?

    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.


    Do I receive alumni status after completing this program?

    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.


    How long will I have access to the learning materials?

    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.

  • What equipment or technical requirements are there for this program?

    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.


    Do I need to be online to access the program content?

    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.

  • Can I still register if the registration deadline has passed?

    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.


    What is the program fee, and what forms of payment do you accept?

    The program fee is noted at the top of this program web page and usually referenced in the program brochure as well.

    • Flexible payment options are available (see details below as well as at the top of this program web page next to FEE).
    • Tuition assistance is available for participants who qualify. Please email learner.success@emeritus.org.

    What if I don’t have a credit card? Is there another method of payment accepted?

    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 at learner.success@emeritus.org for details.


    I was not able to use the discount code provided. Can you help?

    Yes! Please email us at learner.success@emeritus.org with the details of the program you are interested in, and we will assist you.


    How can I obtain an invoice for payment?

    Please email learner.success@emeritus.org with your invoicing requirements and the specific program you’re interested in enroling in.


    Is there an option to make flexible payments for this program?

    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.


    How can I obtain a W9 form?

    Please email us at learner.success@emeritus.org for assistance.

  • What is the policy on refunds and withdrawals?

    You may request a full refund within seven days of your payment or 14 days after the published start date of the program, whichever comes later. If your enrollment had previously been deferred, you will not be entitled to a refund. Partial (or pro-rated) refunds are not offered. All withdrawal and refund requests should be sent to admissions@emeritus.org.



    What is the policy on deferrals?

    After the published start date of the program, you have until the midpoint of the program to request to defer to a future cohort of the same program. A deferral request must be submitted along with a specified reason and explanation. Cohort changes may be made only once per enrollment and are subject to availability of other cohorts scheduled at our discretion. This will not be applicable for deferrals within the refund period, and the limit of one deferral per enrollment remains. All deferral requests should be sent to admissions@emeritus.org.

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