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دوراتنا
Digital Signal Processing 1: Basic Concepts and Algorithms
Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment. By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices. In this series of four courses, you will learn the fundamentals of Digital Signal Processing from the ground up.
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Course by
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التعلم الذاتي
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29 ساعات
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الإنجليزية
Computational Thinking & Block Programming in K-12 Education
In the 21st century, computational thinking is a skill critical for all the world's citizens. Computing and technology is impacting all our lives and everyone needs to know how to formulate problems and express their solutions such that a computer can carry it out. In this Specialization you will both learn several block-based languages, but using novel approaches designed to make learning programming easier. Covers most CSTA Algorithms & Programming Standards for Algorithms, Variables, Control, and Modularity: Levels 1-3A.
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Course by
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Self Paced
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الإنجليزية
Hyperparameter Tuning with Neural Network Intelligence
In this 2-hour long guided project, we will learn the basics of using Microsoft's Neural Network Intelligence (NNI) toolkit and will use it to run a Hyperparameter tuning experiment on a Neural Network. NNI is an open source, AutoML toolkit created by Microsoft which can help machine learning practitioners automate Feature engineering, Hyperparameter tuning, Neural Architecture search and Model compression. In this guided project, we are going to take a look at using NNI to perform hyperparameter tuning.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Creating Multi Task Models With Keras
In this 1 hour long guided project, you will learn to create and train multi-task, multi-output models with Keras. You will learn to use Keras' functional API to create a multi output model which will be trained to learn two different labels given the same input example. The model will have one input but two outputs. A few of the shallow layers will be shared between the two outputs, you will also use a ResNet style skip connection in the model. If you are familiar with Keras, you have probably come across examples of models that are trained to perform multiple tasks.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Modern Robotics, Course 3: Robot Dynamics
Do you want to know how robots work? Are you interested in robotics as a career? Are you willing to invest the effort to learn fundamental mathematical modeling techniques that are used in all subfields of robotics? If so, then the "Modern Robotics: Mechanics, Planning, and Control" specialization may be for you. This specialization, consisting of six short courses, is serious preparation for serious students who hope to work in the field of robotics or to undertake advanced study.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية
Applied Cryptography
This specialization is intended for the learners interested in or already pursuing a career in computer security or other cybersecurity-related fields. Through four courses, the learners will cover the security of information systems, information entropy, classical cryptographic algorithms, symmetric cryptography, asymmetric/public-key cryptography, hash functions, message authentication codes, digital signatures, key management and distribution, and other fundamental cryptographic primitives and protocols.
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Course by
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Self Paced
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الإنجليزية
Accelerated Computer Science Fundamentals
Topics covered by this Specialization include basic object-oriented programming, the analysis of asymptotic algorithmic run times, and the implementation of basic data structures including arrays, hash tables, linked lists, trees, heaps and graphs, as well as algorithms for traversals, rebalancing and shortest paths. This Specialization sequence is designed to help prospective applicants prepare for the flexible and affordable Online Master of Computer Science (MCS) and MCS in Data Science.
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Course by
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Self Paced
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الإنجليزية
Machine Learning: Algorithms in the Real World
This specialization is for professionals who have heard the buzz around machine learning and want to apply machine learning to data analysis and automation. Whether finance, medicine, engineering, business or other domains, this specialization will set you up to define, train, and maintain a successful machine learning application. After completing all four courses, you will have gone through the entire process of building a machine learning project.
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Course by
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Self Paced
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الإنجليزية
Statistical Mechanics: Algorithms and Computations
In this course you will learn a whole lot of modern physics (classical and quantum) from basic computer programs that you will download, generalize, or write from scratch, discuss, and then hand in. Join in if you are curious (but not necessarily knowledgeable) about algorithms, and about the deep insights into science that you can obtain by the algorithmic approach.
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Course by
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Self Paced
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16 ساعات
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الإنجليزية
Coding for Everyone: C and C++
This Specialization is intended for all programming enthusiasts, as well as beginners, computer and other scientists, and artificial intelligence enthusiasts seeking to develop their programming skills in the foundational languages of C and C++. Through the four courses — two in C, and two in C++ — you will cover the basics of programming in C and move on to the more advanced C++ semantics and syntax, which will prepare you to apply these skills to a number of higher-level problems using AI algorithms and Monte Carlo evaluation in complex games.
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Course by
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Self Paced
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الإنجليزية
Introduction to Business Analytics and Information Economics
This specialization targets learners who seek to understand the opportunities that data and analytics present for their organization and those interested in the value of and implications for data as an asset to their organization. Individuals who manage data and make decisions about how data can be leveraged in their organization will find this specialization of particular value. Businesses run on data, and data offers little value without analytics.
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Course by
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Self Paced
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الإنجليزية
Unsupervised Text Classification for Marketing Analytics
Marketing data is often so big that humans cannot read or analyze a representative sample of it to understand what insights might lie within. In this course, learners use unsupervised deep learning to train algorithms to extract topics and insights from text data. Learners walk through a conceptual overview of unsupervised machine learning and dive into real-world datasets through instructor-led tutorials in Python. The course concludes with a major project. This course uses Jupyter Notebooks and the coding environment Google Colab, a browser-based Jupyter notebook environment.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
AI for Scientific Research
In the AI for Scientific Research specialization, we'll learn how to use AI in scientific situations to discover trends and patterns within datasets. Course 1 teaches a little bit about the Python language as it relates to data science. We'll share some existing libraries to help analyze your datasets. By the end of the course, you'll apply a classification model to predict the presence or absence of heart disease from a patient's health data.
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Course by
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Self Paced
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الإنجليزية
Unordered Data Structures
The Unordered Data Structures course covers the data structures and algorithms needed to implement hash tables, disjoint sets and graphs. These fundamental data structures are useful for unordered data. For example, a hash table provides immediate access to data indexed by an arbitrary key value, that could be a number (such as a memory address for cached memory), a URL (such as for a web cache) or a dictionary.
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Course by
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Self Paced
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21 ساعات
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الإنجليزية
Geometric Algorithms
Geometric algorithms are a category of computational methods used to solve problems related to geometric shapes and their properties. These algorithms deal with objects like points, lines, polygons, and other geometric figures. In many areas of computer science such as robotics, computer graphics, virtual reality, and geographic information systems, it is necessary to store, analyze, and create or manipulate spatial data.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Object Oriented Java Programming: Data Structures and Beyond
This Specialization covers intermediate topics in software development. You’ll learn object-oriented programming principles that will allow you to use Java to its full potential, and you’ll implement data structures and algorithms for organizing large amounts of data in a way that is both efficient and easy to work with. You’ll also practice critically evaluating your own code, and you’ll build technical communication skills that will help you prepare for job interviews and collaborative work as a software engineer.
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Course by
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Self Paced
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الإنجليزية
Employee Attrition Prediction Using Machine Learning
In this project-based course, we will build, train and test a machine learning model to predict employee attrition using features such as employee job satisfaction, distance from work, compensation and performance. We will explore two machine learning algorithms, namely: (1) logistic regression classifier model and (2) Extreme Gradient Boosted Trees (XG-Boost). This project could be effectively applied in any Human Resources department to predict which employees are more likely to quit based on their features.
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Course by
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3 ساعات
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الإنجليزية
Scikit-Learn to Solve Regression Machine Learning Problems
Hello everyone and welcome to this new hands-on project on Scikit-Learn for solving machine learning regression problems. In this project, we will learn how to build and train regression models using Scikit-Learn library. Scikit-learn is a free machine learning library developed for python. Scikit-learn offers several algorithms for classification, regression, and clustering. Several famous machine learning models are included such as support vector machines, random forests, gradient boosting, and k-means. This project is practical and directly applicable to many industries.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Matrix Methods
Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction. Optional examples using Python are used to illustrate the concepts and allow the learner to experiment with the algorithms.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Unsupervised Machine Learning for Customer Market Segmentation
In this hands-on guided project, we will train unsupervised machine learning algorithms to perform customer market segmentation. Market segmentation is crucial for marketers since it enables them to launch targeted ad marketing campaigns that are tailored to customer's specific needs.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Data Science Foundations: Data Structures and Algorithms
Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, searching, and indexing. …
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Course by
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Self Paced
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الإنجليزية
Java Programming and Software Engineering Fundamentals
Take your first step towards a career in software development with this introduction to Java—one of the most in-demand programming languages and the foundation of the Android operating system. Designed for beginners, this Specialization will teach you core programming concepts and equip you to write programs to solve complex problems. In addition, you will gain the foundational skills a software engineer needs to solve real-world problems, from designing algorithms to testing and debugging your programs.
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Course by
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Self Paced
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الإنجليزية
Packet Switching Networks and Algorithms
In this course, we deal with the general issues regarding packet switching networks. We discuss packet networks from two perspectives. One perspective involves external view of the network, and is concerned with services that the network provides to the transport layer that operates above it at the end systems. The second perspective is concerned with the internal operation of a network, including approaches directing information across the network, addressing and routing procedures, as well as congestion control inside the network.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Object-Oriented Programming in C++: Functions
This course is the third of five courses aiming to help you to become confident working in the object-oriented paradigm in the C++ language. This specialisation is for individuals who want to learn about objected oriented programming. It's an all-in-one package that will take you from the very fundamentals of C++, all the way to building a crypto-currency exchange platform. During the five courses, you will work with the instructor on a single project: a crypto-currency exchange platform.
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Course by
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Self Paced
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10 ساعات
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الإنجليزية
Meaningful Predictive Modeling
This course will help us to evaluate and compare the models we have developed in previous courses. So far we have developed techniques for regression and classification, but how low should the error of a classifier be (for example) before we decide that the classifier is "good enough"? Or how do we decide which of two regression algorithms is better? By the end of this course you will be familiar with diagnostic techniques that allow you to evaluate and compare classifiers, as well as performance measures that can be used in different regression and classification scenarios.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية