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Big Data Courses

170 Courses

California Institute of Technology XuetangX

信息素养-互联网+时代的学习与生活

在信息化促进工业化的背景下，大学生的信息能力需求增高。信息素养课程致力于培养学生的信息获取、鉴别与管理能力，提高其信息检索和独立解决问题的能力。 课程内容涵盖互联网时代的学习与生活、信息获取与鉴别、搜索引擎、信息技术新发展、学术和专利检索、信息存储与处理以及信息安全等多方面。 课程以线上进行，学生完成网络平台的视频学习、作业和测验，可在线与教师.
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California Institute of Technology XuetangX

万物互联

庄子曾言：“圣人者，原天地之美而达万物之理”。他通过对天地壮美的感受洞悉了宇宙万物的演化规律。随着科技的发展，感知设备能够更加智能地连接人与信息，把现实与数字世界无缝衔接，万物互联的新时代即将开启。我们的课程将引领你进入这个高能的万物互联时代。 课程沿时间线梳理万物互联的发展历程，深入讲解互联网的不同发展阶段，细致剖析万物互联的事物、数据、人员和流程.
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California Institute of Technology XuetangX

智能健康管理

智能健康管理是高等学校健康管理领域人才培养中的一门核心课程，旨在培养学生具有智能健康管理的基本知识以及实践能力。本课程通过课堂教学和课外讨论等环节，授课者从基本概念内涵入手，并结合健康档案数字化平台、可穿戴设备健康数据采集、互联网医院运营平台、养老机器人应用、婴儿体重预测、医学影像智能分析及传染病传播预测等应用场景设计课堂讨论案例。 通过本.
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California Institute of Technology XuetangX

数字素养与社会经济

本课程结合趣味科普，让学生从数据和技术的角度重新认识世界。从经济角度分析网红及其他现象，全面了解数字经济，具备大数据思维，提升数字素养。此为数字化社会的核心素养，是公民生存的基本能力，也是21世纪劳动者和消费者的关键技能。课程强调“双重”技能：数字技能和专业技能，避免成为数字时代的信息盲。 《数字素养与社会经济》课程分为数字经济的基础、经济模式、发展.
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California Institute of Technology XuetangX

长江商学院季波教授领衔：师生共话数字经济时代的创业机遇

大数据、人工智能、物联网、区块链、云计算等技术迅猛发展，正在改变我们的日常生活、学习与思考方式。数字化已成为时代不可逆转的趋势，是企业未来生存的关键。面对数字时代，哪些新商业模式可行？传统企业如何顺利完成数字化转型？如何把握数字经济时代的发展机遇？ 6月25日，学堂在线国际MBA中心推出“国际MBA中心师生圆桌对话”系列直播，首场聚焦数字经济时代的创业机遇.
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California Institute of Technology XuetangX

大学计算机基础（艺术类）

本课程专为艺术类高校设计，重点在于教授计算机基础知识，以适应当代技术发展并满足艺术类学生的特定需求。通过该课程，学生不仅能学习计算机基础知识和概念，还能掌握应用和操作技能。 课程内容依据教育部颁布的《计算机基础教学基本要求》，涵盖计算机领域的各个方面，包括计算机的发展及其应用、系统组成、操作系统基础、办公软件使用、网络及其应用、计算机前沿技术、信.
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California Institute of Technology XuetangX

Computer Fundamentals: Problem Solving Using Computational Thinking

The "Computer Fundamentals: Problem Solving Using Computational Thinking" course is designed to enhance students’ practical skills in addressing problems through computational thinking approaches. In today's world, marked by the rapid advancement of technologies like artificial intelligence, the Internet of Things, big data, and blockchain, the.
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California Institute of Technology XuetangX

E-Government

The E-Government course provides an in-depth look at electronic government, blending social governance, business environment, and engineering disciplines like big data and information systems. Aimed at developing interdisciplinary talents, it covers management and technology aspects. Starting with an overview of the evolution and significan.
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California Institute of Technology Udemy

Módulo Data Analytics, Business Intelligence y Visualización

Adéntrate en el mundo de los datos con el curso "Módulo Data Analytics, Business Intelligence y Visualización" ofrecido por Udemy. Este curso está diseñado para guiarte a través de un proyecto de datos completo, desde la captura inicial hasta la extracción de valiosos conocimientos y su visualización efectiva en la nube. A lo largo del curso,.
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California Institute of Technology Udemy

Modeling Data Warehouse with Data Vault 2.0

Immerse yourself in the foundational aspects of Data Vault 2.0, as this course takes you through the core principles of agile methodologies and big data management. Tailored for those with a keen interest in big data, project management, and data warehousing, this course offers an insightful journey into data modeling intricacies. Hosted on.
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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!