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دوراتنا
Fundamentals of Scalable Data Science
Apache Spark is the de-facto standard for large scale data processing. This is the first course of a series of courses towards the IBM Advanced Data Science Specialization. We strongly believe that is is crucial for success to start learning a scalable data science platform since memory and CPU constraints are to most limiting factors when it comes to building advanced machine learning models.\n\nIn this course we teach you the fundamentals of Apache Spark using python and pyspark.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية
Applied AI with DeepLearning
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area
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Course by
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Self Paced
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25 ساعات
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الإنجليزية
Big Data Analysis with Scala and Spark
Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout.
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Course by
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Self Paced
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28 ساعات
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الإنجليزية
Functional Programming Principles in Scala
Functional programming is becoming increasingly widespread in industry. This trend is driven by the adoption of Scala as the main programming language for many applications. Scala fuses functional and object-oriented programming in a practical package. It interoperates seamlessly with both Java and Javascript. Scala is the implementation language of many important frameworks, including Apache Spark, Kafka, and Akka.
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Course by
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Self Paced
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56 ساعات
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الإنجليزية
Distributed Computing with Spark SQL
This course is all about big data. It’s for students with SQL experience that want to take the next step on their data journey by learning distributed computing using Apache Spark. Students will gain a thorough understanding of this open-source standard for working with large datasets. Students will gain an understanding of the fundamentals of data analysis using SQL on Spark, setting the foundation for how to combine data with advanced analytics at scale and in production environments.
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Course by
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14 ساعات
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الإنجليزية
Introduction to Big Data with Spark and Hadoop
This self-paced IBM course will teach you all about big data! You will become familiar with the characteristics of big data and its application in big data analytics. You will also gain hands-on experience with big data processing tools like Apache Hadoop and Apache Spark. Bernard Marr defines big data as the digital trace that we are generating in this digital era. You will start the course by understanding what big data is and exploring how insights from big data can be harnessed for a variety of use cases.
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Course by
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Self Paced
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24 ساعات
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الإنجليزية
Machine Learning with Spark on Google Cloud Dataproc
This is a self-paced lab that takes place in the Google Cloud console. In this lab you will learn how to implement logistic regression using a machine learning library for Apache Spark running on a Google Cloud Dataproc cluster to develop a model for data from a multivariable dataset.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Big Data Analytics
Learn key technologies and techniques, including R and Apache Spark, to analyse large-scale data sets to uncover valuable business information.
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Course by
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الإنجليزية
Use the Apache Spark Structured Streaming API with MongoDB
By the end of this project, you will use the Apache Spark Structured Streaming API with Python to stream data from two different sources, store a dataset in the MongoDB database, and join two datasets.
The Apache Spark Structured Streaming API is used to continuously stream data from various sources including the file system or a TCP/IP socket. One application is to continuously capture data from weather stations for historical purposes.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Data Engineering with MS Azure Synapse Apache Spark Pools
In this course, you will learn how to perform data engineering with Azure Synapse Apache Spark Pools, which enable you to boost the performance of big-data analytic applications by in-memory cluster computing. You will learn how to differentiate between Apache Spark, Azure Databricks, HDInsight, and SQL Pools and understand the use-cases of data-engineering with Apache Spark in Azure Synapse Analytics. You will also learn how to ingest data using Apache Spark Notebooks in Azure Synapse Analytics and transform data using DataFrames in Apache Spark Pools in Azure Synapse Analytics.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
AI Workflow: Enterprise Model Deployment
This is the fifth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. This course introduces you to an area that few data scientists are able to experience: Deploying models for use in large enterprises. Apache Spark is a very commonly used framework for running machine learning models. Best practices for using Spark will be covered in this course. Best practices for
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Course by
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Self Paced
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9 ساعات
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الإنجليزية
Building Realtime Pipelines in Cloud Data Fusion
This is a self-paced lab that takes place in the Google Cloud console. In addition to batch pipelines, Data Fusion also allows you to create real-time pipelines, that can process events as they are generated. Currently, realtime pipelines execute using Apache Spark Streaming on Cloud Dataproc clusters. In this lab, you will learn how to build a streaming pipeline using Data Fusion.
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Course by
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Self Paced
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2 ساعات
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الإنجليزية
Machine Learning with Apache Spark
Explore the exciting world of machine learning with this IBM course. Start by learning ML fundamentals before unlocking the power of Apache Spark to build and deploy ML models for data engineering applications. Dive into supervised and unsupervised learning techniques and discover the revolutionary possibilities of Generative AI through instructional readings and videos. Gain hands-on experience with Spark structured streaming, develop an understanding of data engineering and ML pipelines, and become proficient in evaluating ML models using SparkML.
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Course by
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Self Paced
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15 ساعات
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الإنجليزية
Apache Spark (TM) SQL for Data Analysts
Apache Spark is one of the most widely used technologies in big data analytics. In this course, you will learn how to leverage your existing SQL skills to start working with Spark immediately. You will also learn how to work with Delta Lake, a highly performant, open-source storage layer that brings reliability to data lakes. By the end of this course, you will be able to use Spark SQL and Delta Lake to ingest, transform, and query data to extract valuable insights that can be shared with your team.
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Course by
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Self Paced
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14 ساعات
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الإنجليزية
Microsoft Azure Databricks for Data Engineering
In this course, you will learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run large data engineering workloads in the cloud. You will discover the capabilities of Azure Databricks and the Apache Spark notebook for processing huge files. You will come to understand the Azure Databricks platform and identify the types of tasks well-suited for Apache Spark. You will also be introduced to the architecture of an Azure Databricks Spark Cluster and Spark Jobs.
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Course by
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Self Paced
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22 ساعات
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الإنجليزية
Data Engineering and Machine Learning using Spark
NOTE: This course is currently replaced with IBM Machine Learning with Apache Spark.
Further your data engineering career with this self-paced course about machine learning with Apache Spark! Organizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery and more to identify behaviors and preferences of prospects, clients, competitors, and others.
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Course by
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Self Paced
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8 ساعات
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الإنجليزية
Big Data Analysis with Scala and Spark (Scala 2 version)
Manipulating big data distributed over a cluster using functional concepts is rampant in industry, and is arguably one of the first widespread industrial uses of functional ideas. This is evidenced by the popularity of MapReduce and Hadoop, and most recently Apache Spark, a fast, in-memory distributed collections framework written in Scala. In this course, we'll see how the data parallel paradigm can be extended to the distributed case, using Spark throughout.
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Course by
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Self Paced
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28 ساعات
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الإنجليزية
Functional Programming Principles in Scala (Scala 2 version)
Functional programming is becoming increasingly widespread in industry. This trend is driven by the adoption of Scala as the main programming language for many applications. Scala fuses functional and object-oriented programming in a practical package. It interoperates seamlessly with both Java and Javascript. Scala is the implementation language of many important frameworks, including Apache Spark, Kafka, and Akka.
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Course by
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Self Paced
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45 ساعات
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الإنجليزية
Dataproc: Qwik Start - Console
This is a self-paced lab that takes place in the Google Cloud console. This lab shows you how to create a Google Cloud Dataproc cluster, run a simple Apache Spark job in the cluster, then modify the number of workers in the cluster, all from the gcloud Command Line. Watch these short videos, Dataproc: Qwik Start - Qwiklabs Preview and Run Spark and Hadoop Faster with Cloud Dataproc.
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Course by
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Self Paced
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1 ساعات
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الإنجليزية
Dataproc: Qwik Start - Command Line
This is a self-paced lab that takes place in the Google Cloud console. This lab shows you how to create a Google Cloud Dataproc cluster, run a simple Apache Spark job in the cluster, then modify the number of workers in the cluster, all from the gcloud Command Line. Watch these short videos, Dataproc: Qwik Start - Qwiklabs Preview and Run Spark and Hadoop Faster with Cloud Dataproc.
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Course by
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Self Paced
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الإنجليزية
Working with Big Data
By the end of this project, you will set up an environment for Big Data Development using Visual Studio Code, MongoDB and Apache Spark. You will then use the environment to process a large dataset from NOAA showing hourly precipitation rates for a ten year period from the state of Wisconsin.
MongoDB is a widely used NoSQL database well suited for very large datasets or Big Data. It is highly scalable and adaptable as well. Apache Spark is used for efficient in-memory processing of Big Data.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Learn SQL Basics for Data Science
This Specialization is intended for a learner with no previous coding experience seeking to develop SQL query fluency. Through four progressively more difficult SQL projects with data science applications, you will cover topics such as SQL basics, data wrangling, SQL analysis, AB testing, distributed computing using Apache Spark, Delta Lake and more.
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Course by
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Self Paced
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الإنجليزية
Data Engineering Capstone Project
Showcase your skills in this Data Engineering project! In this course you will apply a variety of data engineering skills and techniques you have learned as part of the previous courses in the IBM Data Engineering Professional Certificate. You will demonstrate your knowledge of Data Engineering by assuming the role of a Junior Data Engineer who has recently joined an organization and be presented with a real-world use case that requires architecting and implementing a data analytics platform. In this Capstone project you will complete numerous hands-on labs.
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Course by
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13 ساعات
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الإنجليزية
Functional Programming in Scala
Discover how to write elegant code that works the first time it is run. This Specialization provides a hands-on introduction to functional programming using the widespread programming language, Scala. It begins from the basic building blocks of the functional paradigm, first showing how to use these blocks to solve small problems, before building up to combining these concepts to architect larger functional programs.
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Course by
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Self Paced
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الإنجليزية
Data Processing with Azure
This Azure training course is designed to equip students with the knowledge need to process, store and analyze data for making informed business decisions. Through this Azure course, the student will understand what big data is along with the importance of big data analytics, which will improve the students mathematical and programming skills. Students will learn the most effective method of using essential analytical tools such as Python, R, and Apache Spark.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية