Artificial Intelligence Foundations: Machine Learning (LinkedIn Learning)

Machine learning is the most exciting branch of artificial intelligence. It allows systems to learn from data by identifying patterns and making decisions with little to no human intervention. In this course, you'll navigate the machine learning lifecycle by getting hands-on practice training your first machine learning model. Join instructor Kesha Williams as she explores widely adopted machine learning methods: supervised, unsupervised, and reinforcement. There's a focus on sourcing and preparing data and selecting the best learning algorithm for your project. After training a model, learn to evaluate model performance using standard metrics. Finally, Kesha shows you how to streamline the process by building a machine learning pipeline. If you’re looking to understand the machine learning lifecycle and the steps required to build systems, check out this course.

Deze cursus is enkel beschikbaar in het Engels. Als dit voor u geen probleem vormt, dien dan gerust uw aanvraag in.

This course is in French only. If this is not a problem for you, by all means go ahead and apply.

Introduction to Artificial Intelligence (LinkedIn Learning)

Course duration: 2,45h

Computer scientists are just a small slice of people working in artificial intelligence (AI). Most people working with AI are just like you. They’re professionals, teachers, and students who want to use AI to enhance their products, creativity, and career. AI has been around for over half a century. Despite huge advancements in predictive and generative AI, the core concepts of artificial intelligence are still accessible. This course is designed for project managers, product managers, directors, executives, and students starting a career in AI. First, learn what it means for a system to display “intelligence.” Then, explore the difference between classic predictive AI and newer generative AI. Next, you’ll get an overview of machine learning algorithms, artificial neural networks, foundation models, and deep learning. From the AI curious to the AI careerist, this course will help you get started with intelligent systems. This course is part of a Professional Certificate from Microsoft. This course is part of a Professional Certificate from Microsoft.

Topics include:
  • List the distinctions between symbolic systems and machine learning.
  • Identify challenges in natural language processing.
  • Define the various types of machine learning.
  • Explain the importance of algorithms in machine learning.
  • Determine conditions in which using artificial intelligence is appropriate.
  • Review the differences between artificial intelligence and machine learning that impact business decisions.

 

Programming Foundations: Artificial Intelligence (LinkedIn Learning)

Course duration: 1,26h

AI is driving innovation and efficiency in the tech industry. As businesses and organizations seek to leverage AI, there's a high demand for skilled professionals who can understand, develop, and ethically implement AI technologies. In this course, award-winning tech innovator and AI/ML leader Kesha Williams helps developers to upskill and merge their existing programming knowledge with AI competencies. Learn about the concept of artificial intelligence and how it revolutionizes traditional programming methodologies. Explore the tools you need to interpret, evaluate, and harness AI technologies effectively. Through Python code examples, get an introduction to the fundamental pillars of AI, including machine learning, neural networks, and computer vision, while addressing ethical considerations for responsible development. By the end of the course, you will be ready to tackle the technological challenges of today and tomorrow with confidence and creativity.

Topics include:
  • Upskill existing programming knowledge with AI competencies.
  • Interpret and evaluate AI technologies and their applications.
  • Gain hands-on experience with building, testing, and debugging AI models.
  • Learn practical Python programming skills for developing AI solutions.
  • Explore the use of key Python libraries essential for AI development.
  • Understand the ethical considerations and best practices in AI development.
  • Integrate AI with traditional programming approaches.
  • Inspire innovation and creativity in applying AI to solve real-world problems.

 

Responsible AI for Managers (LinkedIn Learning)

Course duration: 0,39h

As AI adoption in organizations evolves, managers need to ensure their teams are using AI responsibly. In this course, instructor Terri Horton shows you how to design and implement responsible AI practices and hold yourself and your team accountable as a manager. Explore the manager's role in responsible AI, in theory and in practice. Get an overview of the guiding principles of ethical AI and responsible AI in management. Terri offers insights on accountability—including data privacy, safety, and how to mitigate bias and risk—before covering key management practices during AI implementation such as decision-making, employee engagement, and psychological safety. Along the way, learn more about AI in action with real-world case examples drawn from business management. This course is part of a Professional Certificate from LinkedIn Learning.