Generative AI for Business Leaders
Advertising with Meta
How Google does Machine Learning
دوراتنا
Robotics: Perception
How can robots perceive the world and their own movements so that they accomplish navigation and manipulation tasks? In this module, we will study how images and videos acquired by cameras mounted on robots are transformed into representations like features and optical flow. Such 2D representations allow us then to extract 3D information about where the camera is and in which direction the robot moves.
-
Course by
-
Self Paced
-
33 ساعات
-
الإنجليزية
Robotics: Estimation and Learning
How can robots determine their state and properties of the surrounding environment from noisy sensor measurements in time? In this module you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world. Specific topics that will be covered include probabilistic generative models, Bayesian filtering for localization and mapping.
-
Course by
-
Self Paced
-
15 ساعات
-
الإنجليزية
Deep Learning Applications for Computer Vision
In this course, you’ll be learning about Computer Vision as a field of study and research. First we’ll be exploring several Computer Vision tasks and suggested approaches, from the classic Computer Vision perspective. Then we’ll introduce Deep Learning methods and apply them to some of the same problems. We will analyze the results and discuss advantages and drawbacks of both types of methods. We'll use tutorials to let you explore hands-on some of the modern machine learning tools and software libraries.
-
Course by
-
Self Paced
-
23 ساعات
-
الإنجليزية
Object Localization with TensorFlow
Welcome to this 2 hour long guided project on creating and training an Object Localization model with TensorFlow. In this guided project, we are going to use TensorFlow's Keras API to create a convolutional neural network which will be trained to classify as well as localize emojis in images. Localization, in this context, means the position of the emojis in the images. This means that the network will have one input and two outputs. Think of this task as a simpler version of Object Detection.
-
Course by
-
Self Paced
-
3 ساعات
-
الإنجليزية
Deep Learning with PyTorch : Object Localization
Object Localization is the task of locating an instance of a particular object category in an image, typically by specifying a tightly cropped bounding box centered on the instance. In this 2-hour project-based course, you will be able to understand the Object Localization Dataset and you will write a custom dataset class for Image-bounding box dataset. Additionally, you will apply augmentation for localization task to augment images as well as its effect on bounding box. For localization task augmentation you will use albumentation library. We will plot the (image-bounding box) pair.
-
Course by
-
Self Paced
-
2 ساعات
-
الإنجليزية
Robot Localization with Python and Particle Filters
In this one hour long project-based course, you will tackle a real-world problem in robotics. We will be simulating a robot that can move around in an unknown environment, and have it discover its own location using only a terrain map and an elevation sensor. We will encounter some of the classic challenges that make robotics difficult: noisy sensor data, and imprecise movement. We will tackle these challenges with an artificial intelligence technique called a particle filter. By the end of this project, you will have coded a particle filter from scratch using Python and numpy.
-
Course by
-
Self Paced
-
4 ساعات
-
الإنجليزية
Advanced Search Engine Optimization Strategies
This course focuses on technical, mobile and social strategies for increasing site traffic. Learn how to build SEO for international audiences through content localization, global team alignment and optimizing for local search engines. Discover techniques to optimize mobile-friendly websites, get mobile apps discovered, and leverage social media to drive organic SEO traffic. You will also learn how to identify key SEO metrics and collect, interpret, validate, and report success to your clients and stakeholders.
-
Course by
-
Self Paced
-
25 ساعات
-
الإنجليزية
Advanced Computer Vision with TensorFlow
In this course, you will: a) Explore image classification, image segmentation, object localization, and object detection.
-
Course by
-
19 ساعات
-
الإنجليزية
Deep Learning with PyTorch : GradCAM
Gradient-weighted Class Activation Mapping (Grad-CAM), uses the class-specific gradient information flowing into the final convolutional layer of a CNN to produce a coarse localization map of the important regions in the image. In this 2-hour long project-based course, you will implement GradCAM on simple classification dataset. You will write a custom dataset class for Image-Classification dataset. Thereafter, you will create custom CNN architecture. Moreover, you are going to create train function and evaluator function which will be helpful to write the training loop.
-
Course by
-
Self Paced
-
3 ساعات
-
الإنجليزية
计算机辅助翻译原理与实践 Principles and Practice of Computer-Aided Translation
现代语言服务行业要求从业人员必须具有利用计算机及网络来使用各类技术辅助工具帮助其工作的能力，而不是仅仅学会几款狭义的计算机辅助翻译软件。 本课程主要讲授计算机辅助翻译技术的基础概念，学习多种计算机辅助翻译工具的使用方法，锻炼学生在技术环境下从事翻译工作等各类语言服务工作的能力，帮助学生理解信息化时代的语言服务工作。 课程完整涵盖现代语言服务的基本情况介绍、翻译技术基本概念、语言服务项目执行过程的信息环境与信息技术、如何利用电子辞典、网络资源及语料库工具辅助翻译工作、狭义和广义的计算机辅助翻译工具原理及实战演练、翻译内容质量评定、多人协同翻译项目、翻译管理等多方面的内容。作为翻译类专业学生的必修课程，本课程适合语言类专业学生学习。通过课程的学习，有助于学习者了解现代语言服务行业，增强各类计算机辅助翻译工具的使用技能，提高包括翻译工作在内的各类语言服务工作的效率。 该课程是“北大-德稻网络公开课程”中的一门，由北京大学与德稻教育联合提供。 本课程同时受到“语言能力协同创新计划”资助和支持。
-
Course by
-
Self Paced
-
صيني
Chemical Biology
Chemical biology is a burgeoning field that has rapidly risen to prominence. This surge of interest has been fuelled by chemical biology’s applicability to understanding critical processes in live cells or model organisms in real time. This success has arisen because chemical biology straddles a nexus between chemistry, biology, and physics. Thus, chemical biology can harness rapid chemistry to observe or perturb biological processes, that are in turn reported using physical assays, all in an otherwise unperturbed living entity.
-
Course by
-
Self Paced
-
21 ساعات
-
الإنجليزية
State Estimation and Localization for Self-Driving Cars
Welcome to State Estimation and Localization for Self-Driving Cars, the second course in University of Toronto’s Self-Driving Cars Specialization. We recommend you take the first course in the Specialization prior to taking this course. This course will introduce you to the different sensors and how we can use them for state estimation and localization in a self-driving car.
-
Course by
-
Self Paced
-
27 ساعات
-
الإنجليزية
Robotics: Aerial Robotics
How can we create agile micro aerial vehicles that are able to operate autonomously in cluttered indoor and outdoor environments? You will gain an introduction to the mechanics of flight and the design of quadrotor flying robots and will be able to develop dynamic models, derive controllers, and synthesize planners for operating in three dimensional environments. You will be exposed to the challenges of using noisy sensors for localization and maneuvering in complex, three-dimensional environments.
-
Course by
-
Self Paced
-
18 ساعات
-
الإنجليزية