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AI Applications with Watson

AI Applications with Watson

Turbocharge your chatbot's IQ and AI capabilities with IBM Watson Discovery and powered by Watson Assistant. Learn to use and program tools and assitant services such as Tone Analyzer and Personality Insights to build queries, extract information big data repositories.

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Big Data, Hadoop, and Spark Basics

Big Data, Hadoop, and Spark Basics

This course provides foundational big data practitioner knowledge and analytical skills using popular big data tools, including Hadoop and Spark. Learn and practice your big data skills hands-on.

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Big Data Technology Capstone Project

Big Data Technology Capstone Project

The Big Data Technology Capstone Project will allow you to apply the techniques and theory you have gained from the four courses in this MicroMasters program to a medium-scale project.

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Unix Tools: Data, Software and Production Engineering

Unix Tools: Data, Software and Production Engineering

Grow from being a Unix novice to Unix wizard status! Process big data, analyze software code, run DevOps tasks and excel in your everyday job through the amazing power of the Unix shell and command-line tools.

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Big Data for Agri-Food: Principles and Tools

Big Data for Agri-Food: Principles and Tools

As the big data era unfolds, developments in sensor and information technologies are evolving quickly. As a result, science and businesses are yielding enormous amounts of data. Ideally this data provides valuable insights for decision-making in real time. But processing data the traditional way is no longer possible. Join Wageningen University & Research, #1 university Animal Sciences and Agriculture, and learn how to best handle big data sets. Enrol now.

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IoT Programming and Big Data

IoT Programming and Big Data

Learn how to apply software solutions for different systems and Big Data needs to your IoT designs.

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Big Data Fundamentals

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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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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Big-O Time Complexity in Python Code

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.

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  • 2 hours
  • English
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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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Apache Spark (TM) SQL for Data Analysts

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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  • 14 hours
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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
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Big Data Science with the BD2K-LINCS Data Coordination and Integration Center

Big Data Science with the BD2K-LINCS Data Coordination and Integration Center

The Library of Integrative Network-based Cellular Signatures (LINCS) was an NIH Common Fund program that lasted for 10 years from 2012-2021. The idea behind the LINCS program was to perturb different types of human cells with many different types of perturbations such as drugs and other small molecules, genetic manipulations such as single gene knockdown, knockout, or overexpression, manipulation of the extracellular microenvironment conditions, for example, growing cells on different surfaces, and more.

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  • 9 hours
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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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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
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Machine Learning y Regresión con PySpark. Guía paso a paso

Machine Learning y Regresión con PySpark. Guía paso a paso

Es un curso práctico y efectivo para aprender a generar modelos de regresión (Machine Learning) con PySpark en un entorno de Big Data.

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  • Spanish
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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
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Big Data Analytics

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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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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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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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
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Data Science with NumPy, Sets, and Dictionaries

Data Science with NumPy, Sets, and Dictionaries

Become proficient in NumPy, a fundamental Python package crucial for careers in data science. This comprehensive course is tailored to novice programmers aspiring to become data scientists, software developers, data analysts, machine learning engineers, data engineers, or database administrators. Starting with foundational computer science concepts, such as object-oriented programming and data organization using sets and dictionaries, you'll progress to more intricate data structures like arrays, vectors, and matrices.

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  • 31 hours
  • English
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Population Health: Responsible Data Analysis

Population Health: Responsible Data Analysis

In most areas of health, data is being used to make important decisions. As a health population manager, you will have the opportunity to use data to answer interesting questions. In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population. First, you will learn how to obtain, safely gather, clean and explore data.

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  • 20 hours
  • English
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Digital Governance

Digital Governance

Big data, artificial intelligence, machine learning, autonomous cars, chatbots, just a few terms that have become a part of our professional legal and political vocabulary. Emerging technologies and technological advancement have confronted us in our daily practice and will continue to do so in the future. Whether we’re buying something online, taking part in an election, or chatting with friends across the globe. Technology is here and it is here to stay.

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  • 28 hours
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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
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