automatique et informatique industriel

This all-encompassing course is a comprehensive journey into the world of Artificial Intelligence (AI). Designed for master's students in electrical engineering, it thoroughly explains AI, its applications, and the technologies that power it. Across nine meticulously structured lectures, participants will delve into the foundations of AI, explore advanced concepts, and discover its transformative potential in various industries.

Course Highlights:

• Lecture 1: Foundations of Artificial Intelligence
  Begin your journey with an introduction to AI, tracing its history, understanding its demand, exploring key applications, and categorizing its types and programming languages.

• Lecture 2: Introduction to Machine Learning (ML)
  Uncover the basics of ML, its necessity, core definitions, and the structured process that drives its success.

• Lecture 3: Types of Machine Learning
  Gain insights into supervised, unsupervised, and reinforcement learning, and explore the types of problems solvable using ML techniques.

• Lecture 4: Supervised Learning Algorithms
  Dive deep into algorithms such as Linear and Logistic Regression, Decision Trees, Random Forests, Naive Bayes, K-Nearest Neighbor (KNN), and Support Vector Machines (SVM).

• Lecture 5: Unsupervised Learning and Beyond
  Explore clustering techniques like K-means, delve into reinforcement learning, compare AI, ML, and Deep Learning, and examine the limitations of ML.

• Lecture 6: Deep Learning Fundamentals
  Learn about deep learning's working mechanisms, use cases, neural networks, backpropagation, and advanced models like recurrent and convolutional neural networks.

• Lecture 7-8: Fuzzy Logic
  Understand fuzzy logic principles and its role in decision-making processes, with practical examples to bridge theory and application.

• Lecture 9: AI in Engineering Applications
  Discover how AI is revolutionizing fields such as automatic and electrical engineering, showcasing its impact on real-world systems.

By the end of this course, participants will have developed a solid foundation in AI and its subfields, including machine learning, deep learning, and fuzzy logic. They will also gain practical insights into applying these concepts across various domains, preparing them for careers in AI and beyond.