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دوراتنا
Data Science Fundamentals for Data Analysts
In this course we're going to guide you through the fundamental building blocks of data science, one of the fastest-growing fields in the world!
With the help of our industry-leading data scientists, we’ve designed this course to build ready-to-apply data science skills in just 15 hours of learning. First, we’ll give you a quick introduction to data science - what it is and how it is used to solve real-world problems. For the rest of the course, we'll teach you the skills you need to apply foundational data science concepts and techniques to solve these real-world problems.
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Course by
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Self Paced
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19 ساعات
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الإنجليزية
Advanced Linear Models for Data Science 1: Least Squares
Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. This class is an introduction to least squares from a linear algebraic and mathematical perspective.
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Image Processing: Object Auto-tracking using Tracker
By the end of this project, you will be able to track two different objects easily using Tracker. You will be able to adjust video clip settings and make clips of it.Moreover, you will be able to calibrate your video and set up your coordinate axis. Learning such a skill can help you in your research projects at university or work. It is an added skill to your data analysis skills set that can give you a competitive edge in data science or computer vision career related opportunities. If you are an educator, it will help you to analyze real world physics problems with your students.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Introduction to Widgets for Data Science
In this 2-hour long project-based course, you will learn what are widgets, how they can used for data science work, types of widgets, linking multiple widgets, basic dashboards of widgets and creating child widgets.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
C Programming: Modular Programming and Memory Management - 3
Enhance your coding skills along your path to becoming a proficient C programmer with the essential concepts of functions and pointers. In this course you will be introduced to the concept of modular programming: that is, dividing up more complex tasks into manageable pieces. You will learn how to write your own functions (just like functions in mathematics for example).
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Course by
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Self Paced
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10 ساعات
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الإنجليزية
Python Packages for Data Science
How many times have you decided to learn a programming language but got stuck somewhere along the way, grew frustrated, and gave up? This specialization is designed for learners who have little or no programming experience but want to use Python as a tool to play with data. Now that you have mastered the fundamentals of Python and Python functions, you will turn your attention to Python packages specifically used for Data Science, such as Pandas, Numpy, Matplotlib, and Seaborn. Are you ready? Let's go! Logo image courtesy of Mourizal Zativa.
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Course by
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Self Paced
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20 ساعات
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الإنجليزية
Promote the Ethical Use of Data-Driven Technologies
The greatest risk in emerging technology is the perpetuation of bias in automated technologies dependent upon data sets. Solutions created with racial, gender or demographic bias, whether unintentional or not can perpetuate tragic inequities socially and economically. This is the first of five courses within the Certified Ethical Emerging Technologist (CEET) professional certificate and it is designed for learners seeking to advocate and promote the ethical use of data-driven technologies.
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Course by
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Self Paced
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21 ساعات
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الإنجليزية
Data Mining Pipeline
This course introduces the key steps involved in the data mining pipeline, including data understanding, data preprocessing, data warehousing, data modeling, interpretation and evaluation, and real-world applications. This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية
Microsoft Azure Machine Learning
Machine learning is at the core of artificial intelligence, and many modern applications and services depend on predictive machine learning models. Training a machine learning model is an iterative process that requires time and compute resources. Automated machine learning can help make it easier. In this course, you will learn how to use Azure Machine Learning to create and publish models without writing code. This course will help you prepare for Exam AI-900: Microsoft Azure AI Fundamentals.
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Course by
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Self Paced
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11 ساعات
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الإنجليزية
Cybersecurity for Data Science
This course aims to help anyone interested in data science understand the cybersecurity risks and the tools/techniques that can be used to mitigate those risks. We will cover the distinctions between confidentiality, integrity, and availability, introduce learners to relevant cybersecurity tools and techniques including cryptographic tools, software resources, and policies that will be essential to data science.
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Course by
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Self Paced
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19 ساعات
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الإنجليزية
Essential Linear Algebra for Data Science
Are you interested in Data Science but lack the math background for it? Has math always been a tough subject that you tend to avoid? This course will teach you the most fundamental Linear Algebra that you will need for a career in Data Science without a ton of unnecessary proofs and concepts that you may never use.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Visualizing Data in the Tidyverse
Data visualization is a critical part of any data science project. Once data have been imported and wrangled into place, visualizing your data can help you get a handle on what’s going on in the data set. Similarly, once you’ve completed your analysis and are ready to present your findings, data visualizations are a highly effective way to communicate your results to others.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Executive Data Science Capstone
The Executive Data Science Capstone, the specialization’s culminating project, is an opportunity for people who have completed all four EDS courses to apply what they've learned to a real-world scenario developed in collaboration with Zillow, a data-driven online real estate and rental marketplace, and DataCamp, a web-based platform for data science programming. Your task will be to lead a virtual data science team and make key decisions along the way to demonstrate that you have what it takes to shepherd a complex analysis project from start to finish.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Developing AI Applications on Azure
This course introduces the concepts of Artificial Intelligence and Machine learning. We'll discuss machine learning types and tasks, and machine learning algorithms. You'll explore Python as a popular programming language for machine learning solutions, including using some scientific ecosystem packages which will help you implement machine learning. Next, this course introduces the machine learning tools available in Microsoft Azure. We'll review standardized approaches to data analytics and you'll receive specific guidance on Microsoft's Team Data Science Approach.
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Course by
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Self Paced
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16 ساعات
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الإنجليزية
Tools for Data Science
In order to be successful in Data Science, you need to be skilled with using tools that Data Science professionals employ as part of their jobs. This course teaches you about the popular tools in Data Science and how to use them. You will become familiar with the Data Scientist’s tool kit which includes: Libraries & Packages, Data Sets, Machine Learning Models, Kernels, as well as the various Open source, commercial, Big Data and Cloud-based tools. Work with Jupyter Notebooks, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio.
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Course by
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Self Paced
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18 ساعات
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الإنجليزية
Advanced Topics and Future Trends in Database Technologies
This course consists of four modules covering some of the more in-depth and advanced areas of database technologies, followed by a look at the future of database software and where the industry is heading. Advanced Topics and Future Trends in Database Technologies can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others.
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Course by
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Self Paced
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17 ساعات
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الإنجليزية
Machine Learning with PySpark: Customer Churn Analysis
This 90-minute guided-project, "Pyspark for Data Science: Customer Churn Prediction," is a comprehensive guided-project that teaches you how to use PySpark to build a machine learning model for predicting customer churn in a Telecommunications company. This guided-project covers a range of essential tasks, including data loading, exploratory data analysis, data preprocessing, feature preparation, model training, evaluation, and deployment, all using Pyspark.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Command Line Tools for Genomic Data Science
Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Python and Statistics for Financial Analysis
Course Overview: https://youtu.be/JgFV5qzAYno Python is now becoming the number 1 programming language for data science. Due to python’s simplicity and high readability, it is gaining its importance in the financial industry.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Application of Data Analysis in Business with R Programming
This Guided Project “Application of Data Analysis in Business with R Programming” is for the data science learners and enthusiasts of 2 hours long. The learners will learn to discover the underlying patterns and analyse the trends in data with Data Science functions.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Data Analysis and Interpretation Capstone
The Capstone project will allow you to continue to apply and refine the data analytic techniques learned from the previous courses in the Specialization to address an important issue in society. You will use real world data to complete a project with our industry and academic partners. For example, you can work with our industry partner, DRIVENDATA, to help them solve some of the world's biggest social challenges!
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
R Programming and Tidyverse Capstone Project
In this third and final course of the "Expressway to Data Science: R Programming and Tidyverse" specialization you will reinforce and display your R and tidyverse skills by completing an analysis of COVID-19 data! Here is a chance to apply your skills to a real-world dataset that has effected all of us. Throughout the capstone, you will import COVID-19 data; clean, tidy, and join datasets; and develop visualizations. You will also provide some analysis and interpretation to your results, preparing you for your journey into data science.
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Course by
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Self Paced
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10 ساعات
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الإنجليزية
Genomic Data Science and Clustering (Bioinformatics V)
How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world?
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Course by
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Self Paced
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10 ساعات
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الإنجليزية
BigQuery Soccer Data Ingestion
This is a self-paced lab that takes place in the Google Cloud console. Get started with sports data science by importing soccer data on matches, teams, players, and match events into BigQuery tables. Information access uses multiple formats, and BigQuery makes working with multiple data sources simple. In this lab you will get started with sports data science by importing external sports data sources into BigQuery tables. This will give you the basis for building more sophisticated analytics in subsequent labs.
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Course by
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Self Paced
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1 ساعات
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الإنجليزية
Finalize a Data Science Project
This course is designed for business professionals that want to learn how to gather results from previous stages of the data science project and present them to stakeholders. Learners will communicate the results of a model to stakeholders, be shown how to build a basic web app to demonstrate machine learning models and implement and test pipelines that automate the model training, tuning and deployment processes.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية