Discover the fundamental concepts behind artificial intelligence (AI) and machine learning in this introductory course. Explore the various types of AI, examine ethical considerations, and delve into the key machine learning models that power modern AI systems. Whether your goal is to work directly with AI, strengthen your software development skills, or enhance your data science expertise, this course provides an essential foundation for success in the field.
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Experience of programming in Python Basic understanding of straight-line graphs, scatter plots, and the aim of a line of best fit to model the data
Arm is in Tier 3: good universities, respected companies, nonprofits and well-known teachers of our institution ranking (76/100).
This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performa…
Led by Andrew Ng, this course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (cluster…
Instructor: Prof. Erik Demaine, Dr. Jason Ku, Prof. Justin Solomon View the complete course: https://ocw.mit.edu/6-006S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63EdVPNLG3ToM6LaEUuStEY This course is an introduction to mathematical modeling of computational problems, as…
This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow;…
Instructor: Dennis Freeman, Kendra Pugh This course provides an integrated introduction to electrical engineering and computer science, including modern software engineering, linear systems analysis, electronic circuits, and decision-making. The lecture videos provide an overview of each topic, whi…
This course explores the world of Transformers and Large Language Models (LLMs). You will learn the evolution of NLP methods, the core components of the Transformer architecture, along with how they relate to LLMs as well as techniques to enhance model performance for real-world applications. Throu…
