Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
The artificial intelligence (AI) revolution is transforming our world, and the demand for skilled professionals who can harness AI's power is on the rise. Artificial Intelligence, provided by Carnegie Mellon University’s School of Computer Science along with Emeritus, is a 10-week long online certification course that provides a comprehensive overview of the theory and practice of AI, with a focus on modern computational techniques for representing task-relevant information and making intelligent decisions. The Artificial Intelligence certification by Carnegie Mellon University’s School of Computer Science covers a wide range of topics, including machine learning, natural language processing, computer vision, and robotics.
With the help of Artificial Intelligence certification, you will gain practical experience by working on real-world projects, such as developing decision support systems for medical environments, recommender systems for ad targeting, and intelligent systems for autonomous work environments.
The skills learned in this course are applicable across a wide range of industries, including healthcare, finance, manufacturing, and transportation. By opting for the Artificial Intelligence certification course, you will be well-positioned to help organisations stay ahead of the technology curve and apply AI-powered solutions to real-world problems.
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The Highlights
- 10 weeks online course
- Offered by Carnegie Mellon University
- Case Studies
- Programming Assignments
- Problem-Based Learning
Programme Offerings
- Certificate of completion
- Online Classes
- Program exercises
- Knowledge checks
- Support team
- Discussion boards
- Crowdsourced Activities
- flexible schedule
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | CMU Pittsburgh |
Eligibility Criteria
Certification Qualifying Details
To obtain the Artificial Intelligence certification by Carnegie Mellon University’s School of Computer Science Executive & Professional Education, you must complete all ten modules of this course along with the assessments successfully.
What you will learn
After completing the Artificial Intelligence certification syllabus, you will learn how to represent the problem in a way that is understandable by AI algorithms and find methods for representing information and solving problems using symbols and numbers. You will be able to use algorithms to search through possible solutions and find the best one.
Upon completion of the Artificial Intelligence training, you will be able to understand how AI is used in areas such as healthcare, finance, and transportation. Additionally, you will be able to consider the potential benefits and risks of AI, as well as the social and ethical implications of its use.
Who it is for
The Artificial Intelligence certification course is designed for participants who want to learn more about emerging technologies, such as artificial intelligence (AI), and gain a deeper understanding of AI tools and techniques. This course is most useful for
Admission Details
To join the Artificial Intelligence classes, candidates can follow these steps:
Step 1: Go through the URL below: https://execonline.cs.cmu.edu/introduction-artificial-intelligence
Step 2: Fill out the relevant details
Step 3: Download the brochure
Step 4: Go through the course page and click on the Apply Now tab
Step 5: Fill out the application form online and pay the course fee
Application Details
You must complete the online application form online to enrol in the Artificial Intelligence online course.
The Syllabus
- Learn how search formalizes the process of looking for solutions to a problem.
- Evaluate the trade-offs and potential information that can be applied to different search problems, and gain an understanding of which algorithms to choose for which types of problems.
- Translate a problem from an English statement into something AI can understand by understanding options and formulating the states and actions in a way that is efficient for solving problems.
- Appreciate the complexity of going from an intuitive understanding of the state to something that the computer can understand/handle.
- Engage in activities to appreciate that not all problems are state/action transitions.
- Identify when the objective is to solve for a set of values, and apply strategies to accomplish this goal.
- Demonstrate familiarity with probabilistic approaches to AI, and implement algorithms to solve probabilistic sequential decision problems.
- Taking probabilities into account, consider models that can make more robust and valued decisions.
- Evaluate ML as a technique for finding patterns in data.
- Explore popular ML algorithms and their corresponding data requirements
- Appreciate the difficulty of finding or producing clean, usable mass data.
- Analyze tuning hyperparameters that affect model performance and evaluate and select models properly.
- Appreciate that randomized algorithms are typically not guaranteed to find optimal solutions within finite time; they often find very good solutions fairly efficiently compared to systematic search.
- Demonstrate the applicability of randomized search techniques and understand when such approaches are appropriate to use.
- Consider how AI systems can efficiently search through large quantities of text to answer user questions.
- Review popular approaches to systems that recommend items for human use, such as movies, restaurants, and news articles.
- Consider common approaches to integrating human feedback into AI systems.
- Review current trends and challenges in AI systems that interact with people
- Reflect on how reliably achieving complex tasks in dynamic environments is difficult and requires the careful integration of numerous AI techniques.
- Analyze and evaluate trade-offs in algorithmic and architectural techniques used to create intelligent autonomous agents that can handle complex, uncertain, and dynamic situations
CMU Pittsburgh Frequently Asked Questions (FAQ's)
What are the prerequisites for taking the Artificial Intelligence certification course?
This online course consists of ten modules that are covered in ten weeks with 8-10 hours of learning per week.
The career prospects for Artificial Intelligence professionals are very vast. You can opt to be AI Data Analyst, AI Developer, Software Developer, or Data Scientist.
You will receive lesson videos, programming assignments, weekly assessments, and knowledge checks.
This online course is available on Emeritus designed by Carnegie Mellon University’s School of Computer Science Executive & Professional Education.