108 Courses and Certifications

Stanford Courses & Certifications 2025

  • Ownership: Private
  • Estd. Year: 1885
  • Total Faculty: 4633
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Virtual Care with Presence

Offered by

Certificate

Virtual Care with Presence

1 Weeks
Expert
Free
How to Taper Patients Off of Chronic Opioid Therapy

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Certificate

How to Taper Patients Off of Chronic Opioid Therapy

1 Weeks
Expert
Free
SafetyQuest Level One QI Basics

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Certificate

SafetyQuest Level One QI Basics

1 Weeks
Expert
Free
SafetyQuest Level Three Implementing QI

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Certificate

SafetyQuest Level Three Implementing QI

1 Weeks
Expert
Free
SafetyQuest Level Two Moving Beyond QI Basics

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Certificate

SafetyQuest Level Two Moving Beyond QI Basics

1 Weeks
Expert
Free
Health Across the Gender Spectrum

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Certificate

Health Across the Gender Spectrum

1 Weeks
Expert
Free
Unconscious Bias in Medicine

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Certificate

Unconscious Bias in Medicine

1 Weeks
Expert
Free
Stanfords Short Course on Breastfeeding

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Certificate

Stanford's Short Course on Breastfeeding

1 Weeks
Beginner
AI in Healthcare Capstone

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Certificate

AI in Healthcare Capstone

AI in Healthcare Capstone will enable the student to have practical experience of the knowledge and skills acquired in the AI in Healthcare Specialization. The programme offered by Stanford University will provide the learners with an opportunity to look into the case of a patient who has respiratory symptoms and is under the care of a primary care provider due to the COVID19 concern. AI in Healthcare Capstone Certification Syllabus will provide the students with an understanding of applying artificial intelligence in healthcare. 

Provided by Coursera, the AI in Healthcare Capstone Certification Course can be completed within about 10 hours and the candidates will be provided with a certificate after the completion of the course. AI in Healthcare Capstone Certification by Coursera is the last course in the AI in Healthcare Specialization. 

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3 Hours
6,638
Skills Covered:
Knowledge of Artificial Intelligence
Probabilistic Graphical Models 1 Representation

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Certificate

Probabilistic Graphical Models 1: Representation

The Probabilistic Graphical Models 1: Representation course by Coursera is a part of the Probabilistic Graphical Models Specialization on the Coursera platform. Stanford University offers a certification course in association with Coursera.

The Probabilistic Graphical Models 1: Representation online course has a curriculum spread out over five weeks. The certification course will help you develop a deep understanding of the PGM framework by communicating perplex material with skill. Moreover, the online course primarily covers the fundamentals of Bayesian networks and Markov networks. 

Furthermore, the Probabilistic Graphical Models 1: Representation certification course promotes interaction and improvement with a comprehensive curriculum, intermittent assignments, and discussion boards. Candidates can self-assess using these mediums and grasp the course contents at their own pace. 

Finally, Coursera provides a certificate upon successful completion of the  Probabilistic Graphical Models 1: Representation course. The certificate can be added to the resume or shared on LinkedIn and other professional websites. Learners can also take a print out of the certificate.

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Expert
4,115
Skills Covered:
Machine learning
Probabilistic Graphical Models 2 Inference

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Certificate

Probabilistic Graphical Models 2: Inference

Probabilistic Graphical Models (PGMs) is considered to be a strong foundation for encrypting probability arrangement over composite domains. Hence, Probabilistic Graphical Models 2: Inference is drafted to address the questions related to probabilistic inference. This course depends upon the concepts from graph algorithms, probability theory, and machine learning. These concepts are the base for the advanced methods used in various applications like speech recognition, medical diagnosis, natural language processing, etc. These advanced methods are also essential tools in composing various machine learning problems.

In an order of three, Probabilistic Graphical Models 2: Inference is the second one. While the first course, focused on description, this course would address the question occurs in probabilistic inference or in other words use of PGM in answering the questions. PGM is described as a very high dimensional diffusion but its framework is drafted in such a way that it can answer the questions efficiently. The course introduces both approximate and accurate algorithms for the variety of inference tasks, and also talks over the application of each algorithm.

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Expert
4,115
Skills Covered:
Knowledge of Algorithms Knowledge of Monte Carlo Method
Probabilistic Graphical Models 3 Learning

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Certificate

Probabilistic Graphical Models 3: Learning

The Coursera Probabilistic Graphical Models 3: Learning certification course covers probabilistic graphical models, commonly known as PGMs. They are a rich framework used for encoding probability distributions over complex domains. They form the foundation of state-of-the-art methods in different applications such as speech recognition, natural language processing, medical diagnosis, image understanding, and many more. They are also instrumental in formulating many machine learning problems. 

The Probabilistic Graphical Models 3: Learning training is the third course in a series of three. Where the first course focused on representation, and the second focused on inference and the final course helps in addressing questions related to learning. The course discusses the main problems of parameter estimation in both directed and undirected models. 

Moreover, students can receive a course completion certificate for the Coursera Probabilistic Graphical Models 3: Learning programme. Candidates can attach the certificate to their LinkedIn profile or their resume/CV.

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Expert
4,115
Skills Covered:
Knowledge of Algorithms
Greedy Algorithms Minimum Spanning Trees and Dynamic Programming

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Certificate

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming is an online programme provided by Stanford University that will help the learners to have a solid understanding of greedy algorithms and dynamic programming.  Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming Certification Syllabus will walk the student through many concepts including scheduling, minimum spanning trees, knapsack, sequence alignment, and the like. 

Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming Certification Course, offered by Coursera, is an intermediate course that is the third in the four courses of Algorithms Specialization. Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming Certification by Coursera is structured in a fashion in which the students can decide the deadline on their own and can be completed within about 14 hours. 

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Intermediate
4,117
Skills Covered:
Programming skills Knowledge of Algorithms
Introduction to Healthcare

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Certificate

Introduction to Healthcare

This course is an 11 hours course that is designed in such a way that a beginner can also be able to understand the full concept of the programme. Introduction to Healthcare certification by Coursera is fully in online mode and provides the solution and strategy which can be implemented in the current system to make it more efficient and to improve the overall healthcare delivery.

The instructor of this course is Nigam Shah, who is an Associate Professor and Academic Director of AI in the Healthcare Specialization department at Stanford University. The other instructors are Laurence Baker and Mildred Cho who are associate professors at Standford University. Introduction to Healthcare certification is also provided by Standford University. In this course, you will also learn about the fundamentals of the U.S. healthcare system and the key components of it like hospitals, pharmaceuticals, insurance and finance arrangements, and healthcare management. This course also has an overall rating of 4.8 on the provider’s portal.

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Beginner
6,638
Stories of Infection

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Certificate

Stories of Infection

Stories of Infection is a 6 weeks long online certification course offered by Stanford University. This course is created by faculty from five different medical schools and supported by the Robert Wood Johnson Foundation and the Burke Family Foundation. This collaboration helped ensure that the course was comprehensive and up-to-date. 

The total duration of the Stories of Infection certification by Coursera is 11 hours with six modules. The course covers the microbiology and immunology of infectious diseases. This helps learners to understand the underlying causes of the diseases and how they are transmitted.

The videos in the Stories of Infection online course track the journey of each patient's illness from the start to the end. This allows learners to see how the disease progresses and how it is treated.

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Intermediate
Free
Skills Covered:
Knowledge of Microbiology

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