Artificial Intelligence
offered by Carnegie Mellon University

Private University
140 acre campus
Estd. 1900

Artificial Intelligence
at
Carnegie Mellon University
Overview

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

Duration	10 weeks
Mode of learning	Online
Difficulty level	Intermediate
Official Website	Go to Website
Course Level	UG Certificate

Artificial Intelligence
at
Carnegie Mellon University
Highlights

Knowledge Checks
Discussion Boards
Wikis/Crowdsourced Activities
Visual Case Study: Human-AI Interaction
Programming Assignments
Scenario and Problem-based Learning

Artificial Intelligence
at
Carnegie Mellon University
Course details

Skills you will learn

English

Who should do this course?

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.

What are the course deliverables?

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

More about this course

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.

Artificial Intelligence
at
Carnegie Mellon University
Curriculum

Module 1: Search

Module 2: State and Action Representation

Module 3: Constraint Satisfaction

Module 4: Probability and Markov Processes

Module 5: Machine Learning Models

Module 6: Practical Machine Learning

Module 7: Randomized Algorithms

Module 8: Common AI Applications

Artificial Intelligence
at
Carnegie Mellon University
Faculty details

STEPHANIE ROSENTHAL

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.

Artificial Intelligence
at
Carnegie Mellon University
Entry Requirements

Eligibility criteria Up Arrow Icon

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.

Conditional Offer Up Arrow Icon

Yes
The Universities' Heinz College occasionally admit students to the program with condition(s) placed on their enrollment. A condition will be clearly stated within the admission offer letter.