Machine Learning & AI

Understanding the basic functionality of hardware, software, network, and database components is crucial in AI systems. This foundational knowledge is essential for effective implementation of AI solutions and engagement with the technologies.

This course introduces students to the ethical and safety issues arising from the use of Artificial Intelligence technologies, with an emphasis on Responsible AI and proactive solutions.

This course is designed to equip students with both the strategic and technical knowledge required to leverage AI in marketing.

Discover how to unlock the true power of AI by building your own marketing tools. In this hands-on webinar, you’ll learn how creating custom AI models—both on your own machine and online—can enhance your marketing strategies, protect your data, and give you the "superpowers" to control and customize AI to meet your unique needs.

This course focuses on the latest developments in AI/ML as applied to product development. The curriculum will prepare students for current, relevant, and industry-applicable topics.

Gain a robust understanding of deep learning through both theory and hands-on implementation, spanning domains such as computer vision, natural language processing (NLP) and graph data analysis. Explore neural network architectures, optimization techniques, and advanced models (CNNs, RNNs, GANs, GNNs). 

Join us for a comprehensive webinar exploring the role and evolution of artificial intelligence in the business world. We'll discuss real-world examples of AI's transformative impact on industries and address its current limitations and the irreplaceable value of human judgment.

This course covers AI fundamentals in finance, Python basics, financial libraries (Numpy, Pandas, etc.), and SQL. It includes machine learning concepts, supervised/unsupervised learning, reinforcement learning, and algorithmic trading, concluding with a real-world case study application.

This course immerses students in the world of generative artificial intelligence (GenAI) and covers high-level browser-based tools, emphasizing the Python code behind them.

This course covers data engineering fundamentals, including data collection, storage, processing, and analysis. It explores the entire data pipeline and the technologies used, preparing students to apply these skills to real-world use cases in analytics and machine learning.

Introduction to linear algebra: Systems of linear equations Matrix algebra Linear independence Subspaces, bases and dimension Orthogonality Least-squares methods Determinants Eigenvalues…

Learn machine learning origins, principles, and practical applications, as well as implementation via the Python programming language. Students will learn to train a model, evaluate its performance, and improve its performance.

Learn machine learning origins, principles, and practical applications, as well as implementation via the R programming language. Students will learn to train a model, evaluate its performance, and improve its performance.

How do you know if AI is the right solution for your product? This session introduces a practical framework to evaluate the feasibility of AI applications, aligning technical capabilities with user and business goals.

Harness cutting-edge AI technology without compromising your innovations. Join us for a transformative webinar that bridges the gap between artificial intelligence and intellectual property.