Artificial intelligence (AI) is the simulation of human intelligence in machines that are programmed to think and act like humans. These machines are designed to be able to perform tasks that typically require human intelligence, such as learning, problem-solving, and decision-making.

AI has the potential to revolutionize many industries and has a wide range of applications, including in healthcare, finance, and transportation.

Check out our range of courses on AI and learn everything from the basics to more advanced concepts.

AI & Law

This four-week course explores the way in which the increasing use of artificially intelligent technologies (AI) affects the practice and administration of law defined in a broad sense. 

Introduction to AI in the Data Center

Python Project for AI & Application Development

This mini-course is intended to apply foundational Python skills by implementing different techniques to develop applications and AI-powered solutions.

Artificial Intelligence (AI) is no longer science fiction. It is rapidly permeating all industries and having a profound impact on virtually every aspect of our existence. Whether you are an executive, a leader, an industry professional, a researcher, or a student – understanding AI, its impact and its transformative potential for your organization and our society is of paramount importance.

This specialization is designed for those with little or no background in AI, whether you have a technology background or not, and does not require any programming skills. It is designed to give you a firm understanding of what is AI, its applications, and use cases across various industries. You will become acquainted with terms like machine learning, deep learning, and neural networks.

Furthermore, it will familiarize you with IBM Watson AI services that enable any business to quickly and easily employ pre-built AI smarts to their products and solutions. You will also learn about creating intelligent virtual assistants and how they can be leveraged in different scenarios.

By the end of this specialization, learners will have had hands-on interactions with several AI environments and applications and have built and deployed an AI-enabled chatbot on a website – without any coding. 

Building AI-Powered Chatbots without programming

Learn to create useful chatbots without the need to write any code. Leveraging IBM Watson’s Natural Language Processing capabilities, you’ll learn how to plan, implement, test, and deploy chatbots that delight your users, rather than frustrate them. 

This specialization will explain and describe the overall focus areas for business leaders considering AI-based solutions for business challenges.

The first course provides a business-oriented summary of technologies and basic concepts in AI.

The second will introduce the technologies and concepts in data science.

The third introduces the AI Ladder, which is a framework for understanding the work and processes that are necessary for the successful deployment of AI-based solutions. 

The AI Ladder: A Framework for Deploying AI in your Enterprise

Artificial intelligence (AI) is transforming our world. Whether you’re a student, a developer, or a technology consultant – understanding AI and knowing how to create AI-powered applications can give you an edge in your career. This Professional Certificate is designed to arm you with the skills to work as an AI developer.

This program will give you a firm understanding of AI technology, its applications, and its use cases. You will become familiar with concepts and tools like machine learning, data science, natural language processing, image classification, image processing, IBM Watson AI services, OpenCV, and APIs. Even if you have no programming background, through this Professional Certificate, you will learn practical Python skills to design, build, and deploy AI applications on the web. The courses will also enable you to apply pre-built AI smarts to your products and solutions.

Rather than create complex AI algorithms and interfaces from scratch, you’ll use IBM Watson AI services and APIs to create smart applications with minimal coding. By the end of this Professional Certificate, you will have completed several projects that showcase proficiency in applying AI and building AI-powered solutions.

In addition to earning a Professional Certificate from Coursera, you’ll also receive a digital badge from IBM recognizing your proficiency in applied AI. 

Building AI-Powered chatbots without programming

Building AI applications with Watson APIs

Artificial intelligence (AI) is revolutionizing entire industries, changing the way companies across sectors leverage data to make decisions. To stay competitive, organizations need qualified AI engineers who use cutting-edge methods like machine learning algorithms and deep learning neural networks to provide data-driven actionable intelligence for their businesses. This 6-course Professional Certificate is designed to equip you with the tools you need to succeed in your career as an AI or ML engineer.

You’ll master fundamental concepts of machine learning and deep learning, including supervised and unsupervised learning, using programming languages like Python. You’ll apply popular machine learning and deep learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow to industry problems involving object recognition, computer vision, image and video processing, text analytics, natural language processing (NLP), recommender systems, and other types of classifiers.

Through hands-on projects, you’ll gain essential data science skills scaling machine learning algorithms on big data using Apache Spark. You’ll build, train, and deploy different types of deep architectures, including convolutional neural networks, recurrent networks, and autoencoders.

In addition to earning a Professional Certificate from Coursera, you will also receive a digital badge from IBM recognizing your proficiency in AI engineering. 

Introduction to computer vision and image processing

 In this beginner-friendly course, you will understand computer vision and learn about its various applications across many industries.

AI Capstone project with deep learning

In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use a library of their choice to develop and test a deep learning model. They will load and pre-process data for a real problem, build the model and validate it.

This six-course specialization is designed to prepare you to take the certification examination for IBM AI Enterprise Workflow V1 Data Science Specialist. IBM AI Enterprise Workflow is a comprehensive, end-to-end process that enables data scientists to build AI solutions, starting with business priorities and working through to taking AI into production. The learning aims to elevate the skills of practicing data scientists by explicitly connecting business priorities to technical implementations, connecting machine learning to specialized AI use cases such as visual recognition and NLP, and connecting Python to IBM Cloud technologies. The videos, readings, and case studies in these courses are designed to guide you through your work as a data scientist at a hypothetical streaming media company.

Throughout this specialization, the focus will be on the practice of data science in large, modern enterprises. You will be guided through the use of enterprise-class tools on the IBM Cloud, tools that you will use to create, deploy and test machine learning models. Your favorite open-source tools, such a Jupyter notebooks, and Python libraries will be used extensively for data preparation and building models. Models will be deployed on the IBM Cloud using IBM Watson tooling that works seamlessly with open-source tools. After successfully completing this specialization, you will be ready to take the official IBM certification examination for the IBM AI Enterprise Workflow. 

Artificial intelligence (AI) has transformed industries around the world and has the potential to radically alter the field of healthcare. Imagine being able to analyze data on patient visits to the clinic, medications prescribed, lab tests, and procedures performed, as well as data outside the health system — such as social media, purchases made using credit cards, census records, Internet search activity logs that contain valuable health information, and you’ll get a sense of how AI could transform patient care and diagnoses.

In this specialization, we’ll discuss the current and future applications of AI in healthcare with the goal of learning to bring AI technologies into the clinic safely and ethically.

This specialization is designed for both healthcare providers and computer science professionals, offering insights to facilitate collaboration between the disciplines. 

Fundamentals of machine learning for healthcare

This course will introduce the fundamental concepts and principles of machine learning as it applies to medicine and healthcare. We will explore machine learning approaches, medical use cases, metrics unique to healthcare, as well as best practices for designing, building, and evaluating machine learning applications in healthcare.

This specialization is intended for anyone interested in preparing for the Certified AI-900 Microsoft Azure AI Fundamentals Exam. This program consists of 5 courses to help prepare you to take the certification exam.

You will acquire foundational knowledge of the core concepts related to artificial intelligence (AI) and the services in Microsoft Azure that can be used to create AI solutions. This program is an opportunity to demonstrate knowledge of common ML and AI workloads and how to implement them on Azure.

By the end of this program, you will be ready to take and sign-up for the AI-900 exam. The AI Fundamentals exam is an opportunity to demonstrate your knowledge of how to create AI solutions on Microsft Azure. Each course teaches you the core concepts and skills that are measured by the exam.

Azure AI Fundamentals can be used to prepare for other Azure role-based certifications like Azure Data Scientist Associate or Azure AI Engineer Associate, but it’s not a prerequisite for any of them. 

In the AI for Scientific Research specialization, we’ll learn how to use AI in scientific situations to discover trends and patterns within datasets.

Course 1 teaches a little bit about the Python language as it relates to data science. We’ll share some existing libraries to help analyze your datasets. By the end of the course, you’ll apply a classification model to predict the presence or absence of heart disease from a patient’s health data.

Course 2 covers the complete machine learning pipeline, from reading in, cleaning, and transforming data to running basic and advanced machine learning algorithms.

In the final project, we’ll apply our skills to compare different machine learning models in Python.

In Course 3, we will build on our knowledge of basic models and explore more advanced AI techniques. We’ll describe the differences between the two techniques and explore how they differ. Then, we’ll complete a project predicting similarities between health patients using random forests.

In Course 4, a capstone project course, we’ll compare genome sequences of COVID-19 mutations to identify potential areas a drug therapy can look to target.

By the end, you’ll be well on your way to discovering ways to combat disease with genome sequencing.

The Creativity and AI Specialization explores what it means to be creative in the 21st century. Through a hands-on approach, you will discover the creative potential of AI and learn design methods to expand your creative capacity.

These courses are designed for those with technical backgrounds who want to look at their fields from a new perspective and those in creative professions who want to better understand AI and its implications in their industries. 

As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations.

In this specialization, we will explore the rise of algorithms, fundamental issues of fairness and bias in machine learning, and basic concepts involved in the security and privacy of machine learning projects.

We’ll finish with a study of 3 projects that will allow you to put your new skills into action. 

This specialization will provide learners with the fundamentals of using Big Data, Artificial Intelligence, and Machine Learning and the various areas in which you can deploy them to support your business. You’ll cover the ethics and risks of AI, designing governance frameworks to fairly apply AI, and also cover people management in the fair design of HR functions within Machine Learning. You’ll also learn effective marketing strategies using data analytics, and how personalization can enhance and prolong the customer journey and lifecycle. Finally, you will hear from industry leaders who will provide you with insights into how AI and Big Data are revolutionizing the way we do business.

By the end of this specialization, you will be able to implement ethical AI strategies for people management and have a better understanding of the relationship between data analytics, artificial intelligence, and machine learning. You will leave this specialization with insight into how these tools can shape and influence how you manage your business. 

AI Strategy and Governance

Organizations in every industry are accelerating their use of artificial intelligence and machine learning to create innovative new products and systems. This requires professionals across a range of functions, not just strictly within the data science and data engineering teams, to understand when and how AI can be applied, to speak the language of data and analytics, and to be capable of working in cross-functional teams on machine learning projects.

This specialization provides a foundational understanding of how machine learning works and when and how it can be applied to solve problems. Learners will build skills in applying the data science process and industry best practices to lead machine learning projects, and develop competency in designing human-centered AI products which ensure privacy and ethical standards.

The courses in this specialization focus on the intuition behind these technologies, with no programming required, and merge theory with practical information including best practices from industry. Professionals and aspiring professionals from a diverse range of industries and functions, including product managers and product owners, engineering team leaders, executives, analysts, and others will find this program valuable.

Human Factors in AI

This is the third and final course of the AI Product Management Specialization by Duke University’s Pratt School of Engineering, which focuses on the critical human factors in developing AI-based products. 

AI is transforming the practice of medicine. It’s helping doctors diagnose patients more accurately, make predictions about patients’ future health, and recommend better treatments. This three-course Specialization will give you practical experience in applying machine learning to concrete problems in medicine.

These courses go beyond the foundations of deep learning to teach you the nuances of applying AI to medical use cases. If you are new to deep learning or want to get a deeper foundation of how neural networks work, we recommend taking the Deep Learning Specialization. 

AI for Medical Treatment

In Course 3, you will build a treatment effect predictor, apply model interpretation techniques, and use natural language processing to extract information from radiology reports.