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.

Gain the job-ready skills for an entry-level data analyst role through this Professional Certificate from IBM and position yourself competitively in the thriving job market for data analysts, which will see a 20% growth until 2028 (U.S. Bureau of Labor Statistics).

Power your data analyst career by learning the core principles of data analysis and gaining hands-on skills practice. You’ll work with a variety of data sources, project scenarios, and data analysis tools, including Excel, SQL, Python, Jupyter Notebooks, and Cognos Analytics, gaining practical experience with data manipulation and applying analytical techniques.

This Professional Certificate does not require any prior programming or statistical skills, and is suitable for learners with or without college degrees. All you need to get started is basic computer literacy, high school math, comfort working with numbers, willingness to learn, and a desire to enrich your profile with valuable skills.

Upon successful completion of this program, you’ll have analyzed real-world datasets, created interactive dashboards, and presented reports to share your findings, giving you the confidence and the portfolio to begin a career as an associate or junior data analyst. You’ll also build the foundation for other data disciplines such as data science or data engineering.

This program is ACE® recommended—when you complete, you can earn up to 12 college credits.

AI use cases and workloads continue to grow and diversify across vision, speech, recommender systems, and more. Intel offers an unparalleled development and deployment ecosystem combined with a heterogeneous portfolio of AI-optimized hardware. Intel's goal is to make it as seamless as possible to accelerate your developer journey from the edge to the cloud. Intel’s AI software portfolio includes order of magnitude optimizations for popular frameworks and tools for every stage of the AI workflow.

Explore practical tools to guide the moral design of AI systems.

Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. In this course, you’ll learn the basics of modern AI as well as some of the representative applications of AI. Along the way, we'll also cover the numerous applications and huge possibilities in the field of AI, which continues to expand human capability beyond our imagination.

In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. You will also demonstrate AI in action with a mini project.

This course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.

In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. You will also demonstrate AI in action with a mini project.

This course does not require any programming or computer science expertise and is designed to introduce the basics of AI to anyone whether you have a technical background or not.

Machine Learning is a first-class ticket to the most exciting careers in data analysis today. As data sources proliferate along with the computing power to process them, going straight to the data is one of the most straightforward ways to quickly gain insights and make predictions.

Machine learning brings together computer science and statistics to harness that predictive power. It’s a must-have skill for all aspiring data analysts and data scientists, or anyone else who wants to wrestle all that raw data into refined trends and predictions.

This is a class that will teach you the end-to-end process of investigating data through a machine learning lens. It will teach you how to extract and identify useful features that best represent your data, a few of the most important machine learning algorithms, and how to evaluate the performance of your machine learning algorithms.

This course is also a part of our Data Analyst Nanodegree.

This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML has become one of the hottest fields of study today, taken up by undergraduate and graduate students from more than 20 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects.

This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to concrete computational problems; understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering; and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective

The MSc in Computing (Artificial Intelligence and Machine Learning) is a taught postgraduate course aimed at students with a good academic degree who may not have studied computing exclusively but who have studied a considerable amount of computing already.

Applicants who want to become a specialist in a particular area of computing and who want to take a first crucial training step towards that goal are the natural target for this course. The expectation of graduates is that this course enables them to have rewarding careers as specialist in an area of Computing.

Each specialism has a flexible mix of breadth and depth, consisting of two or three compulsory modules as well as choices from a selection of core and optional modules.

This course is also a suitable preparation for PhD studies.

All applicants for this course must have taken computing courses that equate to two years of a computer science undergraduate programme. For further details, see the MSc Computing (AI and ML) entry requirements or our FAQs.

GISMA University of Applied Sciences MSc Data Science, AI and Digital Business programme offers a unique combination of technology and business which will help you keep advance into a future-oriented career in a global company or innovative start-up.

Digital technologies are omnipresent in today's society and business world. All areas of life are affected by a digital revolution which is evolving faster and faster. Artificial intelligence, 5G, Big Data, the Internet of Things, and Blockchain will disrupt traditional business models and change job roles in the industry.