Generative AI for Business Leaders
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How Google does Machine Learning
دوراتنا
Applied Data Science
This action-packed Specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. If you’re interested in pursuing a career in data science, and already have foundational skills or have completed the Introduction to Data Science Specialization, this program is for you! This 4-course Specialization will give you the tools you need to analyze data and make data driven business decisions leveraging computer science and statistical analysis.
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Course by
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Self Paced
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الإنجليزية
Python, Bash and SQL Essentials for Data Engineering
If you are interested in developing the skills needed to be a data engineer, the Python, Bash and SQL Essentials for Data Engineering Specialization is a great place to start. We live in a world that is driven by big data - from what we search online to the route we take to our favorite restaurant, and everything in between. Businesses and organizations use this data to make decisions that impact the ways in which we navigate our lives. How do engineers collect this data? How can this data be organized so that it can be appropriately analyzed?
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Course by
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Self Paced
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الإنجليزية
IBM Data Engineering
Prepare for a career in the high-growth field of data engineering. In this program, you’ll learn in-demand skills like Python, SQL, and Databases to get job-ready in less than 5 months. Data engineering is building systems to gather data, process and organize raw data into usable information.
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Course by
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Self Paced
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الإنجليزية
Systems Biology and Biotechnology
Design systems-level experiments using appropriate cutting edge techniques, collect big data, and analyze and interpret small and big data sets quantitatively. The Systems Biology Specialization covers the concepts and methodologies used in systems-level analysis of biomedical systems. Successful participants will learn how to use experimental, computational and mathematical methods in systems biology and how to design practical systems-level frameworks to address questions in a variety of biomedical fields.
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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
Python and Machine-Learning for Asset Management with Alternative Data Sets
Over-utilization of market and accounting data over the last few decades has led to portfolio crowding, mediocre performance and systemic risks, incentivizing financial institutions which are looking for an edge to quickly adopt alternative data as a substitute to traditional data. This course introduces the core concepts around alternative data, the most recent research in this area, as well as practical portfolio examples and actual applications.
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Course by
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Self Paced
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21 ساعات
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الإنجليزية
Foundations of mining non-structured medical data
Rare course alert! This course is very specific and very will give you the edge you need in your career! Learn all about the foundations of Big Data and the data that is being generated in the health domain and how the use of technology would help to integrate and exploit all those data to extract meaningful information that can be later used in different sectors of the health domain from physicians to management, from patients to caregivers, etc.
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Course by
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Self Paced
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7 ساعات
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الإنجليزية
Azure Data Lake Storage Gen2 and Data Streaming Solution
In this course, you will see how Azure Data Lake Storage can make processing Big Data analytical solutions more efficient and how easy it is to set up. You will also explore how it fits into common architectures, as well as the different methods of uploading the data to the data store. You will examine the myriad of security features that will ensure your data is secure. Learn the concepts of event processing and streaming data and how this applies to Azure Stream Analytics.
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Course by
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9 ساعات
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الإنجليزية
Scatter Plot for Data Scientists & Big Data Analysts-Visuals
This project gives you easy access to the invaluable learning techniques used by experts for visualization in statistics. We’ll learn about how to use wolfram language to draw curve in easiest way. We’ll also cover illustration and best practices shown by research to be most effective in helping you master plotting curves.
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Course by
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Self Paced
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3 ساعات
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الإنجليزية
Fundamentals of Big Data
Welcome to Fundamentals of Big Data, the fourth course of the Key Technologies of Data Analytics specialization. By enrolling in this course, you are taking the next step in your career in data analytics. This course is the fourth of a series that aims to prepare you for a role working in data analytics. In this course, you will be introduced to many of the core concepts of big data. You will learn about the primary systems used in big data. We’ll go through phases of a common big data life cycle.
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Course by
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Self Paced
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12 ساعات
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الإنجليزية
Hot Topics in Criminal Justice
The American criminal justice system is in need of reform. We incarcerate too many people. We pay insufficient attention to scientific advances that can help separate out the most and least culpable and dangerous. We grant the police far too much power to use force and technological surveillance. As a way of thinking about dealing with these problems, this course examines two over-arching issues: What should we do with people who have committed crime, and how should we identify who they are?
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Course by
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Self Paced
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19 ساعات
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الإنجليزية
A quick tour on Big Data and Business Intelligence
This course is devoted to beginners and practitioners of Big Data and AI fields. It will be a quick overview of some basic concepts that could be further elaborated by professionals. Ranging from CAP theorem to Turing assumption, we will provide a starting guide for diving in these fascinating topics.
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Course by
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Self Paced
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7 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
Software Architecture Patterns for Big Data
The course is intended for individuals looking to understand the architecture patterns necessary to take large software systems that make use of big data to production. You will transform big data prototypes into high quality tested production software. After measuring the performance characteristics of distributed systems, you will identify trouble areas and implement scalable solutions to improve performance.
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Course by
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Self Paced
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49 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
Computer Simulations
Big data and artificial intelligence get most of the press about computational social science, but maybe the most complex aspect of it refers to using computational tools to explore and develop social science theory. This course shows how computer simulations are being used to explore the realm of what is theoretically possible. Computer simulations allow us to study why societies are the way they are, and to dream about the world we would like to live in. This can be as intuitive as playing a video game.
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Course by
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Self Paced
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13 ساعات
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الإنجليزية
Fundamentals of Software Architecture for Big Data
The course is intended for individuals looking to understand the basics of software engineering as they relate to building large software systems that leverage big data. You will be introduced to software engineering concepts necessary to build and scale large, data intensive, distributed systems.
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Course by
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Self Paced
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43 ساعات
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الإنجليزية
Security and Privacy for Big Data - Part 1
Welcome to our comprehensive course focused on security within Big Data environments. This course aims to provide you with a deep understanding of cryptographic principles and equip you with the tools necessary to manage access controls effectively within any Big Data system.
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Course by
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Self Paced
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1 ساعات
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الإنجليزية
ESG Data & Accountability
In this course, we’ll introduce students with basic knowledge of traditional financial products to data-driven resources they can use to complement their fundamental analysis.
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Course by
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Self Paced
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20 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
Machine Learning Using SAS Viya
This course covers the theoretical foundation for different techniques associated with supervised machine learning models. In addition, a business case study is defined to guide participants through all steps of the analytical life cycle, from problem understanding to model deployment, through data preparation, feature selection, model training and validation, and model assessment. A series of demonstrations and exercises is used to reinforce the concepts and the analytical approach to solving business problems.
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Course by
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Self Paced
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34 ساعات
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الإنجليزية
Data Manipulation at Scale: Systems and Algorithms
Data analysis has replaced data acquisition as the bottleneck to evidence-based decision making --- we are drowning in it. Extracting knowledge from large, heterogeneous, and noisy datasets requires not only powerful computing resources, but the programming abstractions to use them effectively.
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Course by
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Self Paced
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20 ساعات
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الإنجليزية
Big-O Time Complexity in Python Code
In the field of data science, the volumes of data can be enormous, hence the term Big Data. It is essential that algorithms operating on these data sets operate as efficiently as possible. One measure used is called Big-…
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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
Big data and Language 1
In this course, students will understand characteristics of language through big data. Students will learn how to collect and analyze big data, and find linguistic features from the data. A number of approaches to the linguistic analysis of written and spoken texts will be discussed. The class will consist of lecture videos which are approximately 1 hour and a quiz for each week. There will be a final project which requires students to conduct research on text data and language.
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Course by
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Self Paced
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5 ساعات
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الإنجليزية