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Big Data Courses

207 Courses

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California Institute of Technology

Certificate in Data Science

Elevate your expertise in the evolving tech landscape with our Certificate in Data Science. Delve into the realm of data to uncover insights and forecast critical trends. This program is tailored for professionals aiming to build a robust data science foundation or considering further academic pursuits. Our comprehensive 21-credit Certificate.
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California Institute of Technology Indiana University

Industry 4.0 for business managers

The Fourth Industrial Revolution (I4.0) is here, impacting workers and businesses worldwide. Elevate your knowledge and skills with this Professional Certificate from a top-tier institution. Unlock new value through data, connectivity, real-time systems, and AI, discovering innovative applications and opportunities. This comprehensive course o.
provider edX
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California Institute of Technology Tecnológico de Monterrey

Inteligencia Artificial y Robótica

La robótica y la inteligencia artificial son esenciales para el éxito empresarial en diversas industrias. La automatización industrial representa una realidad actual. Según el Foro Económico Mundial, roles como Especialistas en Aprendizaje de Máquina, Científicos de Datos y Expertos en Inteligencia Artificial, con competencias en Big Data y cien.
provider edX
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California Institute of Technology Indiana University

Industry 4.0 for business managers

The ascent of Industry 4.0 marks a transformative era known as the Fourth Industrial Revolution, profoundly influencing professionals and businesses worldwide. Build your knowledge and expertise to thrive in this new era by completing the Professional Certificate from one of the world’s leading institutions. This program will reshape your approach.
provider edX
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California Institute of Technology Delft University of Technology

Data Skills for Artificial Intelligence

Data Skills for Artificial Intelligence - Delft University of Technology | edX Explore the intersection of data and Artificial Intelligence with this comprehensive MOOC series designed for aspiring data scientists, machine learning experts, and AI innovators. Presented by Delft University of Technology on edX, this program highlights the impor.
provider edX
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California Institute of Technology edX

Data Warehouse Engineering

Data Warehouse Engineers and Business Analysts are increasingly crucial as organizations rely more on data for operational support. Data warehousing has revolutionized how organizations perform business analysis and make strategic decisions. Massive data from various sources is accessible using SQL, formatted for analysis, reporting, and Business.
provider edX
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California Institute of Technology Indiana University

Business Excellence in a knowledge-driven Industry 4.0 world

In today’s digital society, the interconnected nature of our world becomes increasingly evident. By 2025, it's estimated there will be 175 zetabytes of digital resources available online, including data, software, and multimedia files. This explosion of digital assets, combined with cultivated social networks, facilitates significant collabo.
provider edX
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California Institute of Technology edX

SQL, ETL and BI Fundamentals

Unlock the potential of data to create Business Intelligence with our SQL, ETL, and BI Fundamentals Professional Certificate. Organizations rely on Data Warehousing Engineers, Data Analysts, and BI professionals to extract value from their data, creating a high demand for these skilled roles. Designed to equip you with essential skills and h.
provider edX
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California Institute of Technology Universitat Oberta de Catalunya

Data Analysis for Decision-Making

Data Analysis for Decision-Making - Professional Certificate Program Demand for data analysis skills in the U.S. is projected to rise by 21% over the next decade, vastly outpacing the overall labor market growth. Fields such as Data Science, Data Analytics, and Statistics are anticipated to expand by up to 34%. The World Economic Forum highlight.
provider edX
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California Institute of Technology edX

Google Cloud Computing Foundations

Google Cloud Computing Foundations is designed for individuals with little to no prior experience in cloud computing. This comprehensive program offers an introduction to fundamental concepts in cloud basics, big data, and machine learning, alongside insights into Google's role in this ecosystem. Upon completion of this course series, particip.
provider edX

Becoming a Big Data Analyst: A Step-by-Step

Big data analysis is a relatively new, but quite in-demand area of the labour market. The demand for data scientists is constantly growing. Big Data are data sets of very large size, which are also characterised by diversity and high update rate. A big data analyst is a specialist who identifies and investigates patterns in data using special software tools.

Overview of Big Data and AI

The generation and sharing of big data across devices is happening in almost every social sphere. Big Data is used by giants such as Google, Uber, IBM, Amazon to optimise customer experience, reduce the risk of fraud and data security threats. Big Data specialists after big data and ai courses are needed in: marketing, search technology, retail, social media, gaming, personalisation, speech technology, financial institutions and recommendation systems.

Skills You Will Gain

It is not necessary for an analyst to have a university degree in information technology. However, a Data Analyst must understand business processes, understand statistics, perform machine learning, and be able to work with tools.

Types of data analysis:

The duties of the analyst also include tasks on Business Inteligence (BI) and optimisation of processes in production. A specialist should know the methods of analysing business processes: SWOT, ABC, IDEF, BPMN, MTP, PDCA, EPC and others.

Basic Data Analyst skills:

Additionally, the analyst may use Apache Storm, Apache Kinesis, Apache Spark Streaming.

Big Data specialists need to be able to build graphical models using Bayesian and neural networks, clustering and types of analysis. A Data Scientist, Data Analyst or Data Engineer should be skilled in working with Data Lakes, as well as security and Data Governance. Becoming an expert will help you develop each of these skills in depth.

Why Learn Big Data and AI?

In the era of digital transformation, when the amount of data doubles every two years, the art of analysing and using it has become not just an important skill but also a key competitive advantage. In the different fields, traditionally based on knowledge and experience, big data and machine learning course opens new horizons. With the ability to analyse data in depth, we have a tool that allows us to not only respond to current educational needs, but also to predict them, adapting to changing realities faster than ever before.

Career Opportunities and Job Roles

Let's take a look at the main roles and vacancies in Big Data and Data Science.

Data Scientist

A Data Scientist is a specialist who analyses data and develops machine learning with big data to solve business problems. Key responsibilities include:

The Data Scientist should have a strong knowledge of statistics, programming and machine learning.

Data Engineer

The Data Engineer is responsible for building and maintaining the infrastructure for data processing. Key responsibilities include:

The Data Engineer plays a key role in ensuring that data is available and ready for analysis.

Big Data Engineer

The Big Data Engineer develops and maintains systems to process large amounts of data. Key responsibilities include:

The Big Data Engineer should have in-depth knowledge of distributed computing and big data.

Machine Learning Engineer

Machine Learning Engineer specialises in the design and implementation of machine learning models. Key responsibilities include:

The Machine Learning Engineer must have a strong knowledge of machine learning and programming.

Industry Demand

Big Data and AI are two rapidly developing fields that play a key role in today's world. Big Data refers to processing and analysing huge amounts of data that cannot be processed using traditional methods. Data Science, on the other hand, involves the use of statistical methods, machine learning and other technologies to extract knowledge and insights from data. These fields are of great importance to business, science and technology as they enable better informed decision-making and the development of innovative products and services!