Big Data Courses

133 Courses

[A-Z] Visualización y Analítica de datos con Power BI

Estás invitado a descubrir el curso "A-Z Visualización y Analítica de datos con Power BI", ofrecido por Udemy. Este programa práctico y detallado está diseñado para brindarte una formación integral en la visualización de datos mediante Power BI, incluyendo conocimientos en Power Query, DAX (Data Analysis Expressions) y modelado de datos en el c.
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provider Udemy
pricing Paid Course
duration 23 hours
sessions On-Demand

Python für Data Science, Machine Learning & Visualization

Python für Data Science, Machine Learning & Visualisierung | Udemy Entdecken Sie die Welt von Data Science, Machine Learning und Datenvisualisierung mit Python! Dieser umfassende Kurs auf Udemy bietet Ihnen alle Werkzeuge, die Sie brauchen, um Datenanalysen durchzuführen und Ihre Kenntnisse im Bereich Machine Learning zu erweitern. L.
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provider Udemy
pricing Paid Course
duration 1 day 5 hours 18 minutes
sessions On-Demand

5 Courses - Master AWS, Analytics, Machine Learning, Bigdata

5 Courses - Master AWS, Analytics, Machine Learning, Bigdata | Udemy 5 Courses - Master AWS, Analytics, Machine Learning, Bigdata Embark on a comprehensive learning journey to master AWS, Analytics, Machine Learning, and Big Data. This curated package of 5 courses, available on Udemy, is designed to equip yo.
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provider Udemy
pricing Paid Course
duration 12 hours 11 minutes
sessions On-Demand

Financial Forecasting with Analytics Essential Training

Financial Forecasting with Analytics Essential Training Unlock the potential of Microsoft Excel with our comprehensive course on Financial Forecasting with Analytics Essential Training. Delve into the world of financial analytics and big data to create precise forecasts quickly and efficiently. Provider: LinkedIn Learning Categories: Big Data Co.
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provider LinkedIn Learning
pricing Free Trial Available
duration 1-2 hours
sessions On-Demand

Big Data: capstone project

Big Data: Capstone Project En el último curso de la Especialización en Big Data, el estudiante tendrá la oportunidad de aplicar algunas de las herramientas y métodos aprendidos en los cursos anteriores en un caso práctico. El objetivo de este Capstone Project es mostrar un ejemplo del trabajo que se realiza diariamente en el departamento de Cosmo.
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provider Coursera
pricing Free Online Course (Audit)
duration 13 hours
sessions On-Demand

Fundamentals of Analytics on AWS – Part 1

Fundamentals of Analytics on AWS – Part 1 This course is the first of two offerings designed to introduce learners to the current market trends in analytics. In Part 1, you will learn fundamental concepts such as types of analytics, the 5 V’s of big data, and the challenges associated with processing high volumes of data. This course also maps t.
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provider AWS Skill Builder
pricing Free Certificate
duration 2 hours
sessions On-Demand

Applied Python Data Engineering

Applied Python Data Engineering Learn how to use data engineering to leverage big data for business strategy, data analysis, or machine learning and AI. By completing this course series, you'll empower yourself with the knowledge and proficiency required to build efficient data pipelines, manage cutting-edge platforms like Hadoop, Spar.
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provider Coursera  Specialization
pricing Paid Course

Modeling Data Warehouse with Data Vault 2.0

Modeling Data Warehouse with Data Vault 2.0 Course - Udemy Join our comprehensive course on "Modeling Data Warehouse with Data Vault 2.0" offered by Udemy. This course dives into the essentials and fundamentals of Data Vault 2.0, integrated with Agile Methodology and Big Data principles. Perfect for anyone looking to enhance their skil.
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provider Udemy
pricing Paid Course
duration 5 hours 55 minutes
sessions On-Demand

Herramientas para el Análisis de Big Data

Herramientas para el Análisis de Big Data | Universidad de los Andes | edX Cuando se trata de herramientas para el análisis de datos, siempre tenemos las siguientes preguntas: ¿Cuál es la diferencia entre tantas herramientas que existen? ¿Cuál es la mejor? ¿Cuál debería aprender? Las funciones que realizan los científicos de datos incluyen la id.
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provider edX
pricing Free Online Course (Audit)
duration 4 weeks, 3-5 hours a week
sessions On-Demand

Introduction to FinTech

Introduction to FinTech Over the past decade, emerging technologies, paired with massive changes in regulations, have driven an unprecedented transformation of finance around the world. This process is happening more rapidly in China and Asia than anywhere else. This course is designed to explore FinTech fundamentals and help make sense of this.
provider edX
pricing Free Online Course (Audit)
duration 6 weeks, 1-3 hours a week
sessions On-Demand

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!