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Big Data Courses

170 Courses

California Institute of Technology Udemy

Google Cloud (GCP) MasterClass 2024 : GCP for Beginner - Pro

Join the Google Cloud (GCP) MasterClass 2024: GCP for Beginner - Pro and master the essentials of Google Cloud Platform. Dive into the world of cloud computing, big data, and artificial intelligence with hands-on learning modules. This course is offered by Udemy and is perfect for individuals looking to enhance their skills in Artificial Intel.
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provider Udemy
pricing Paid Course
duration 1 day 7 hours 1 minute
sessions On-Demand
California Institute of Technology

Apache Spark Essential Training

Apache Spark Essential Training Apache Spark Essential Training Get up to speed with Spark, and discover how to leverage this powerful platform to efficiently and effectively work with big data. Categories: Machine Learning Courses, Big Data Courses, Data Analysis Courses, Apache Spark Courses
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California Institute of Technology AWS Skill Builder

Fundamentals of Analytics on AWS – Part 1 (Japanese)

Fundamentals of Analytics on AWS – Part 1 (Japanese) このコースは、受講者にアナリティクスの現在の市場動向を紹介することを目的とした 2 つのコースのうちの 1 つ目のコースです。第 1 部では、分析のタイプ、ビッグデータの 5 V、大量データの処理に関連する課題などの基本的な概念を学びます。また、このコースでは、ビッグデータの 5 V を分析用の AWS サービスにマ.
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California Institute of Technology FutureLearn

Big Data - Aligning Strategy, Analytics & Operations

Big Data - Aligning Strategy, Analytics & Operations Big data, if harnessed correctly, can help businesses use their data to make better decisions, streamline operations, and improve customer satisfaction. On this online microcredential, you’ll develop the essential skills and knowledge to successfully lead and deliver benefits from big data imple.
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California Institute of Technology Pluralsight

Exploring and Analyzing Data with QlikView 12

Title: Exploring and Analyzing Data with QlikView 12 Description: Analyze big data easier with our QlikView training. Join Pluralsight author Vitthal Srinivasan as he shows you best practices for analyzing data in QlikView. QlikView bills itself as a guided analytics tool, which helps extract insights from large datasets. It lives up to that bi.
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California Institute of Technology ThaiMOOC

การตัดสินใจโดยการขับเคลื่อนด้วยข้อมูล | Data - Driven Decision Making

การตัดสินใจโดยการขับเคลื่อนด้วยข้อมูล | Data - Driven Decision Making คำอธิบายรายวิชา: ความหมายของข้อมูล ข้อมูลขนาดใหญ่ ชนิดของข้อมูล โครงสร้างข้อมูล เทคนิคการวิเคราะห์ข้อมูล เครื่องมือในการแสดงผลข้อมูล เครื่องมือในการวิเคราะห์ข้อมูล หลักการในการตัดสินใจโดยขับเคลื่อนด้วยข้อมูล จำนวนชั่วโมงเรียนรู้: จำนวนชั่วโมงเรียนรู้ทั้งหมด 4 ชั่วโมงเรียนรู้.
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California Institute of Technology Coursera

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 involves building systems to gather, process, and organize raw data into usable information, and manage it effectively. The f.
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California Institute of Technology

Digital Transformation Tips

Digital Transformation Tips Learn how to best support the digital transformation efforts of your business. Get actionable tips for leveraging technology and planning for success. Categories: Artificial Intelligence Courses Machine Learning Courses Big Data Courses Digital Transformation Courses Cloud Computing Courses Internet of T.
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California Institute of Technology Pluralsight

Data: Executive Briefing

Data: Executive Briefing We all work with data, but often don’t consider the big picture. In this fast-paced, practical introduction, you will quickly get up to speed on multiple ideas, tools, and technologies around “data” in today’s business world. Every business role today needs to understand the core ideas, tools, and technologies their orga.
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provider Pluralsight
pricing Free Trial Available
duration 38 minutes
sessions On-Demand
California Institute of Technology Udemy

Python, Guía de inicio

Python, Guía de inicio | Udemy Domina los fundamentos de Python con nuestro curso "Python, Guía de inicio" en Udemy. Este curso es ideal para quienes desean crear aplicaciones en diversos campos como: Ciencia de datos Inteligencia Artificial (IA) Robótica Desarrollo web BigData Explora cómo Python puede convertirse en tu herramienta.
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provider Udemy
pricing Free Online Course
duration 1 hour 57 minutes
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!