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Big Data Courses

170 Courses

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 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 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 XuetangX

金融科技模式与创新

本课程提供对金融科技领域最新模式和创新技术的深入理解，涵盖区块链技术、人工智能在金融服务中的应用、数字支付系统及大数据分析等前沿话题。学生通过案例分析，实现理论与实践结合，掌握金融科技的实际应用和发展趋势。非常适合对金融科技有兴趣的学生，助力在领域内取得突破和发展。 开课平台：XuetangX 分类：人工智能课程, 机器学习课程, 大数据课程, 金融科技课程,.
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California Institute of Technology XuetangX

管理信息系统-大数据赋能与模式创新

课程教学设计 本课程的教学设计系统且完备，围绕“用好系统”和“造好系统”两个核心主题，分为十章，回答了管理信息系统的“是什么”（第1、2章）、“技术基础是什么”（第3-5章）、“有什么用”（第6章）、及“怎么用”（第9-10章）等问题。从管理和业务人员的视角，探讨如何建设系统（第7-8章），引入了管理信息系统与区块链、元宇宙的结合以及算法在数据洞察中的应用等新颖观点和技.
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California Institute of Technology XuetangX

大数据技术与应用

本课程以一系列大数据讲座为主线，突出实战性，激发学生学习兴趣和动力，促进学生理论与实践相结合，启发学生技术创新。注重结合应用实例融会贯通大数据中的理论方法和系统知识（平台、模块、工具），体会运用大数据技术解决实际问题的思路和效果。本课程兼顾信息类和非信息类学生。
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California Institute of Technology XuetangX

科技与社会

本课程以科技哲学和科学社会学交叉的视野思审视科学技术，特别是在马克思主义指导下，分析现代科技的本质特征和体系结构。同时，总结并概括科技发展的内在动力和发展模式，探索科技的社会功能，反思运行条件，以及社会治理关键问题。 通过学习本课程，学生将实现以下目标： 深刻理解科技发展与个人、社会、人类发展的紧密关联，全面认识科技的正面和负面影响。 初步掌握.
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California Institute of Technology XuetangX

智能社会中的知识产权法

在新文科建设背景下，本课程提供了一个独特的法学学习机会，以人工智能和法律为基础，专注于知识产权法。课程内容紧密跟随智能科技和社会的发展，通过理论与实践的结合，深入探讨智能社会对知识产权法的挑战和变革，同时回应社会热点问题和技术争议。 课程细分为八个章节：包括知识产权法视角下的人工智能、智能社会中的知识产权挑战、著作权法、商业秘密制度、专利法、.
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California Institute of Technology XuetangX

数据与智能技术应用

在数据成为新型生产要素的崭新时代，数据就像新时代的石油一样是重要的、驱动社会的动力和能源。如何让数据真正的为千行万业赋能，这是时代的需求和呼唼。一说到大数据和智能技术，很多非IT类专业出身的学习者往往感到“需要了解，可是太过高深”“零基础的小白，无处下手”。然而，在实际应用中，让专业的人做专业的事是关键。在各行业数智转型的时候，单靠IT出身的专业人士.
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California Institute of Technology Udemy

Big Data: Hadoop| MapReduce| Hive| Pig| NoSQL| Mahout| Oozie

Unlock the potential of Big Data with this expert-led course on Udemy. Dive into the world of Hadoop and its ecosystem, including HDFS, MapReduce, Hive, Pig, and NoSQL databases. Extend your skills further with Mahout for machine learning, Oozie for workflow scheduling, and Flume for data ingestion. Enhance your capabilities with practical ex.
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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!