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دوراتنا
Introduction to Computer Science and Programming
The term “Computation” refers to the action performed by a computer. A computation can be a basic operation and it can also be a sophisticated computer simulation requiring a large amount of data and substantial resources. This course aims at introducing learners with no prior knowledge to the basic key concepts of computer science. By following the lectures and exercises of this course, you will gain an understanding of algorithms by programming using the language Ruby.
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الإنجليزية
Essentials of Genomics and Biomedical Informatics
This course presents clinicians and digital health enthusiasts with an overview of the data revolution in medicine and how to exploit it for research and in the clinic. The course will not make you a bioinformatician but will introduce the main concepts, tools, algorithms, and databases in this field.
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الإنجليزية
Data Structures & Algorithms III: AVL and 2-4 Trees, Divide and Conquer Algorithms
Learn more complex tree data structures, AVL and (2-4) trees. Investigate the balancing techniques found in both tree types. Implement these techniques in AVL operations. Explore sorting algorithms with simple iterative sorts, followed by Divide and Conquer algorithms. Use the course visualizations to understand the performance.
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الإنجليزية
Data Structures & Algorithms II: Binary Trees, Heaps, SkipLists and HashMaps
Become familiar with nonlinear and hierarchical data structures. Study various tree structures: Binary Trees, BSTs and Heaps. Understand tree operations and algorithms. Learn and implement HashMaps that utilize key-value pairs to store data. Explore probabilistic data structures like SkipLists. Course tools help visualize the structures and performance.
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الإنجليزية
Data Structures & Algorithms I: ArrayLists, LinkedLists, Stacks and Queues
Work with the principles of data storage in Arrays, ArrayLists & LinkedList nodes. Understand their operations and performance with visualizations. Implement low-level linear, linked data structures with recursive methods, and explore their edge cases. Extend these structures to the Abstract Data Types, Stacks, Queues and Deques.
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الإنجليزية
Computing in Python IV: Objects & Algorithms
Learn about recursion, search and sort algorithms, and object-oriented programming in Python.
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الإنجليزية
Autonomous Mobile Robots
Basic concepts and algorithms for locomotion, perception, and intelligent navigation.
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الإنجليزية
Linear Algebra Basics
Machine learning and data science are the most popular topics of research nowadays. They are applied in all the areas of engineering and sciences. Various machine learning tools provide a data-driven solution to various real-life problems. Basic knowledge of linear algebra is necessary to develop new algorithms for machine learning and data science. In this course, you will learn about the mathematical concepts related to linear algebra, which include vector spaces, subspaces, linear span, basis, and dimension.
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21 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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Self Paced
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10 ساعات
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الإنجليزية
Enterprise and Infrastructure Security
This course introduces a series of advanced and current topics in cyber security, many of which are especially relevant in modern enterprise and infrastructure settings. The basics of enterprise compliance frameworks are provided with introduction to NIST and PCI.
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15 ساعات
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الإنجليزية
Machine Learning: Theory and Hands-on Practice with Python
In the Machine Learning specialization, we will cover Supervised Learning, Unsupervised Learning, and the basics of Deep Learning. You will apply ML algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Starting with supervised learning, we will cover linear and logistic regression, KNN, Decision trees, ensembling methods such as Random Forest and Boosting, and kernel methods such as SVM. Then we turn our attention to unsupervised methods, including dimensionality reduction techniques (e.g., PCA), clustering, and recommender systems.
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الإنجليزية
Data Science at Scale
Learn scalable data management, evaluate big data technologies, and design effective visualizations. This Specialization covers intermediate topics in data science. You will gain hands-on experience with scalable SQL and NoSQL data management solutions, data mining algorithms, and practical statistical and machine learning concepts. You will also learn to visualize data and communicate results, and you’ll explore legal and ethical issues that arise in working with big data.
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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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الإنجليزية
Biology Meets Programming: Bioinformatics for Beginners
Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python.
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Self Paced
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19 ساعات
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الإنجليزية
ESG Investing: Financial Decisions in Flux
As ESG investing continues to evolve towards a global standard, certain initiatives such as the UN’s sustainable development goals, and the Paris Agreement on climate change, have already spurred significant changes across the financial markets. As the title of this specialization suggests, financial decisions by investors, as well as capital deployment by companies, organizations, and governments, have been shifting amid increasing attention to environmental, social, and governance-related concerns. By the end of this specialization, students with basic knowledge of traditional financial pr
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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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الإنجليزية
Deep Learning and Reinforcement Learning
This course introduces you to two of the most sought-after disciplines in Machine Learning: Deep Learning and Reinforcement Learning. Deep Learning is a subset of Machine Learning that has applications in both Supervised and Unsupervised Learning, and is frequently used to power most of the AI applications that we use on a daily basis. First you will learn about the theory behind Neural Networks, which are the basis of Deep Learning, as well as several modern architectures of Deep Learning.
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32 ساعات
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الإنجليزية
Big Data Fundamentals
Learn how big data is driving organisational change and essential analytical tools and techniques, including data mining and PageRank algorithms.
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الإنجليزية
Embedding Sensors and Motors
The courses in this specialization can also be taken for academic credit as ECEA 5340-5343, part of CU Boulder’s Master of Science in Electrical Engineering degree. Enroll here. Embedding Sensors and Motors will introduce you to the design of sensors and motors, and to methods that integrate them into embedded systems used in consumer and industrial products. You will gain hands-on experience with the technologies by building systems that take sensor or motor inputs, and then filter and evaluate the resulting data.
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الإنجليزية
Digital Signal Processing
This Specialization provides a full course in Digital Signal Processing, with a focus on audio processing and data transmission. You will start from the basic concepts of discrete-time signals and proceed to learn how to analyze data via the Fourier transform, how to manipulate data via digital filters and how to convert analog signals into digital format. Finally, you will also discover how to implement real-time DSP algorithms on a general-purpose microcontroller.
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الإنجليزية
Informed Clinical Decision Making using Deep Learning
This specialisation is for learners with experience in programming that are interested in expanding their skills in applying deep learning in Electronic Health Records and with a focus on how to translate their models into Clinical Decision Support Systems. The main areas that would explore are: Data mining of Clinical Databases: Ethics, MIMIC III database, International Classification of Disease System and definition of common clinical outcomes.
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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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الإنجليزية
Unsupervised Learning and Its Applications in Marketing
Welcome to the Unsupervised Learning and Its Applications in Marketing course! In this course, you will delve into the fascinating world of unsupervised machine learning and its relevance to the field of marketing. Unsupervised learning is a powerful approach that allows us to uncover hidden patterns and insights from vast amounts of historical data without the need for explicit labels or human intervention.
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Self Paced
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22 ساعات
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الإنجليزية
Introductory C Programming
This specialization develops strong programming fundamentals for learners who want to solve complex problems by writing computer programs. Through four courses, you will learn to develop algorithms in a systematic way and read and write the C code to implement them. This will prepare you to pursue a career in software development or other computational fields. Successful completion of this Specialization will be considered by admissions as a demonstration of your skill and enhance your master’s application to Duke’s Pratt School of Engineering.
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Self Paced
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الإنجليزية
Digital Marketing and Data Driven Analytics
Digital Marketing is the backbone element which uses platforms and digital technologies, such as any kind of device to maintain connected to the users. Once the users are part of this ecosystem, the companies convert this random data in accurate algorithms to improve the effectiveness of any marketing campaign.
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الإنجليزية