Google Cloud's Introduction to Generative AI Learning Path is a free, comprehensive course tailored for non-technical professionals in tech-adjacent roles like sales, HR, marketing, and operations. The learning path, which takes approximately two hours to complete, offers a foundational understanding of generative AI concepts and applications.

This course prepares you for in-demand AI roles with a 13-course series covering deep architectures, machine learning, and deep learning using popular libraries like PyTorch and TensorFlow. Gain practical experience through hands-on labs and projects, and build a standout resume and portfolio. Enroll today!

AI in Healthcare explores the current and future applications of AI in healthcare, focusing on safe and ethical implementation. This specialization, with CME Accreditation, offers a unique Applied Learning Project where students analyze a patient's journey using a custom dataset.

Google Cloud's Introduction to Generative AI Learning Path is a free, comprehensive course tailored for non-technical professionals in tech-adjacent roles like sales, HR, marketing, and operations. The learning path, which takes approximately two hours to complete, offers a foundational understanding of generative AI concepts and applications.

CS50x is Harvard University's introduction to computer science and programming. This self-paced course covers topics like algorithms, data structures, and web development, using languages such as C, Python, JavaScript, SQL, and HTML/CSS. The course includes problem sets inspired by real-world domains and offers a certificate upon completion of 9 assignments and a final project.

This course aims to equip students with a holistic understanding of AI's role in business, providing them with practical skills, ethical considerations, and strategic thinking necessary for successful integration and innovation in the rapidly evolving landscape of AI technology.

What really is “artificial intelligence”? “Machine learning”? Let’s cut through the meaningless buzzwords, and talk the real talk.

Learn to build and apply deep learning models with PyTorch. Covering image and text tasks, advanced architectures, and Transformers. Start your journey now!

An introduction to data science with no coding involved.

Data science is becoming more and more valuable to the workplace and to the global economy. Learn how to use the practice of data science and the programming language R to transform your data into actionable insight.

Learn the machine learning lifecycle with instructor Kesha Williams, covering data preparation, algorithm selection, model training, evaluation, and pipeline building.

Launch your career as an AI Product Manager. Build in-demand product management and generative AI skills to get job ready in 6 months or less.

Learn how to build artificial intelligence-powered systems, products, and services in this non-credit, non-

Learn what Artificial Intelligence (AI) is by understanding its applications and key concepts including machine learning, deep learning and neural networks.

The goal of the AWS Machine Learning Engineer (MLE) Nanodegree program is to equip software developers/data scientists with the data science and machine learning skills required to build and deploy machine learning models in production using Amazon SageMaker. This program will focus on the latest best practices and capabilities that are enabled by Amazon SageMaker, including new model design/deployment features and case studies in which they can be applied to.

Learn Python, NumPy, Pandas, Matplotlib, PyTorch, and Linear Algebra—the foundations for building your own neural network.

Become a Machine Learning expert. Master the fundamentals of deep learning and break into AI. Recently updated with cutting-edge techniques!

#BreakIntoAI with Machine Learning Specialization. Master fundamental AI concepts and develop practical machine learning skills in the beginner-friendly, 3-course program by AI visionary Andrew Ng

An overview of AI training methodologies and their importance.