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Digital Manufacturing & Design Technology

Digital Manufacturing & Design Technology

Whether you’re a high school graduate exploring manufacturing careers, or an operations manager hungry for an understanding of the newest manufacturing technologies, this specialization will provide a foundation in how digital advances are changing the landscape and capabilities of factories. Nine courses – developed with input from the manufacturing industry – touch on Industry 4.0 and its components, including digital manufacturing and design practices, the concept of the digital thread, the Internet of Things and Big Data.

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Practical Predictive Analytics: Models and Methods

Practical Predictive Analytics: Models and Methods

Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of practical and effective machine learning methods and concepts, and apply them to solve some real world problems. Learning Goals: After completing this course, you will be able to: 1.

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  • 7 hours
  • English
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Big Data

Big Data

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions. ********* Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive.

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  • English
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Data Engineering Capstone Project

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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  • 13 hours
  • English
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Serverless Data Processing with Dataflow

Serverless Data Processing with Dataflow

It is becoming harder and harder to maintain a technology stack that can keep up with the growing demands of a data-driven business. Every Big Data practitioner is familiar with the three V’s of Big Data: volume, velocity, and variety. What if there was a scale-proof technology that was designed to meet these demands? Enter Google Cloud Dataflow. Google Cloud Dataflow simplifies data processing by unifying batch & stream processing and providing a serverless experience that allows users to focus on analytics, not infrastructure.

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Applied Data Science

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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Python, Bash and SQL Essentials for Data Engineering

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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IBM Data Engineering

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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  • English
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Systems Biology and Biotechnology

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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Working with Big Data

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.

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  • 3 hours
  • English
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Python and Machine-Learning for Asset Management with Alternative Data Sets

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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  • 21 hours
  • English
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Foundations of mining non-structured medical data

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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  • 7 hours
  • English
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Azure Data Lake Storage Gen2 and Data Streaming Solution

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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  • 9 hours
  • English
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Scatter Plot for Data Scientists & Big Data Analysts-Visuals

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.

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  • 3 hours
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Fundamentals of Big Data

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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  • 12 hours
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Hot Topics in Criminal Justice

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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  • 19 hours
  • English
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A quick tour on Big Data and Business Intelligence

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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  • 7 hours
  • English
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Big Data Analysis with Scala and Spark (Scala 2 version)

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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  • 28 hours
  • English
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Software Architecture Patterns for Big Data

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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  • 49 hours
  • English
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Assessment for Learning

Assessment for Learning

For several decades now, assessment has become an increasingly pressing educational priority. Teacher and school accountability systems have come to be based on analysis of large-scale, standardized summative assessments. As a consequence, assessment now dominates most conversations about reform, particularly as a measure of teacher and school accountability for learner performance. Behind the often heated and at times ideologically gridlocked debate is a genuine challenge to address gaps in achievement between different demographically identifiable groups of students.

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  • 14 hours
  • English
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Data Engineering and Machine Learning using Spark

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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  • 8 hours
  • English
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Computer Simulations

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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  • 13 hours
  • English
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Fundamentals of Software Architecture for Big Data

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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  • 43 hours
  • English
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Security and Privacy for Big Data - Part 1

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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  • 1 hour
  • English
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ESG Data & Accountability

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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  • 20 hours
  • English
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