[Coursera] Mechanical Engineering: Tiếp tục với loạt bài giới thiệu về các khóa học miễn phí của Coursera, Thư viện ĐH Công nghiệp Hà Nội xin giới thiệu đến Quý bạn đọc các khóa học về “Kỹ thuật Cơ khí” (Mechanical Engineering).

Nội dung đề cập đến tổng quan; mô hình chức năng của một hệ thống đào tạo trực tuyến; các vấn đề chuẩn hóa khi xây dựng hệ thống đào tạo trực tuyến; xây dựng một hệ thống đào tạo trực tuyến sử dụng công nghệ Web service; xây dựng một hệ thống đào tạo trực tuyến bằng công nghệ Web service dựa trên plat forrm J2EE.

The Team Learning Assistant (TLA) is a web-based set of tools that promotes effective classroom teaming for faculty and students alike.

Leading a Learning Revolution tells the compelling story of a learning revolution that took place within the U.S. Department of Defense. Written by practitioners who actually walked the walk, this account of the creation of Defense Acquisition University (DAU) provides a clear blueprint that others can follow. It shares, in detail, the best practices they developed, so that the thousands of training organizations worldwide striving to create premier corporate universities can catapult forward.

This best-selling text provides comprehensive coverage of general teaching methods and models.

Machine Learning with Python for Everyone brings together all they’ll need to succeed: a practical understanding of the machine learning process, accessible code, skills for implementing that process with Python and the scikit-learn library, and real expertise in using learning systems intelligently.

The book offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.

The book covers a broad array of topics not usually included in introductory machine learning texts, including supervised learning, Bayesian decision theory, parametric methods, semiparametric methods, nonparametric methods, multivariate analysis, hidden Markov models, reinforcement learning, kernel machines, graphical models, Bayesian estimation, and statistical testing.

With the help of this 3-in-1 guide, you will be given carefully sequenced Python Programming lessons that’ll maximize your understanding, and equip you with all the skills for real-life application

The book will appeal to a wide audience, including teacher educators; curriculum and materials developers; examination boards unfamiliar with the CEFR; university language departments and language centres responsible for developing their own curricula, teaching/learning approaches and assessment instruments; and policy-makers wanting to learn more about the implications of adopting the CEFR. It is a guidebook, a reference book and a workbook all in your hand.