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Big Data Courses

186 Courses

California Institute of Technology XuetangX

网络与新媒体概论

网络与新媒体概论课程由江西服装学院提供，专门为应用型高校环境设计，旨在使学生掌握新媒体运营与营销技巧。课程利用最新案例来增强学生的技术理解力和营销思维，同时注重课程思政建设，增加了关于新媒体在社会主义民主政治建设中作用的内容，培养学生的媒介素养与价值观。 此课程通过XuetangX平台提供，分类于人工智能课程、大数据课程、数字营销课程、内容营销课程以及社.
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California Institute of Technology XuetangX

智能物流应用

通过本门课程的学习，学生能够了解智能物流的发展趋势，掌握智能物流的相关概念，掌握物联网，云计算，大数据，人工智能等关键技术的具体应用场景，掌握智能运输，智能配送和智能包装等相关知识，培养学生独立与协作工作的能力，提升学生自主学习的兴趣，锻炼学生通过自主学习掌握工作思路与方法的能力，切实提高学生的职业技能和处理实际问题的综合素质。 University: Xuet.
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California Institute of Technology XuetangX

Cloud Computing and Artificial Intelligence

This course covers the structure and possibilities of Cloud Computing, emphasizing the merging of data with AI services like IoT, key technologies in the Fourth Industrial Revolution. It also delves into the applications of big data processing through text analytics. Participants will gain an understanding and practical skills in the principles o.
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California Institute of Technology XuetangX

电子商务研究专题

While e-commerce is creating miracles, it is also constantly expanding its frontiers. This course takes the frontiers of the development of e-commerce as the object and discusses the evolutionary laws and ecology of e-commerce through specific topics, including two-sided market theory, long tail theory, Moore's law, Metcalfe's law, Davido's la.
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California Institute of Technology XuetangX

清华大学计算机科学与技术系六十周年系庆学术报告（四）大数据

作为清华大学计算机系成立六十周年的庆祝活动之一，该系列学术报告旨在通过邀请国内外学术界与产业界的知名学者和专家，进行专题演讲，介绍国际前沿的研究及产业动态，同时分享他们的战略思考与成果。在交流中找出不足，明确方向，以推动清华大学计算机学科的进一步发展。 六十周年系庆学术报告是一次学术盛宴，参与的演讲者均为各领域的大专家，包括图灵奖得主，以及中外国.
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California Institute of Technology XuetangX

技术创新简史

本课程深入探讨自18世纪的工业革命以来关键领域的技术变革，梳理前三次工业革命的历史经验。课程特别讲述技术创新人物与其对社会的影响，以及为何这些创新会发生的思想历程。从技术人文和社会历史的视角，启发学生对历次工业革命的深刻思考，引领对即将到来的第四次工业革命对人类社会影响的学习与讨论。
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California Institute of Technology XuetangX

Future Automobiles

In the era of global industrial technological reform, characterized by low-carbonization, electrification, intelligence, and connectivity, smart electric vehicles are pivotal as mobile connected nodes, smart mobile terminals, and intelligent energy storage solutions. These vehicles play a crucial role in smart transportation, cities, and energy.
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California Institute of Technology Udemy

Customer Intelligence and Analytics for Omni-Channel

Visit Udemy Master the art of omni-channel marketing through a comprehensive managerial perspective on artificial intelligence, technology, and data analytics. This Udemy course focuses on enhancing customer-centric engagement using cutting-edge strategies in AI and big data. Course Highlights: Gain insights into AI-driven customer intellig.
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California Institute of Technology Udemy

The Complete 5 Volume Series: If You Can Cook, You Can Code

Unlock the secrets of programming with the engaging course series, "If You Can Cook, You Can Code." This unique 5-in-1 bundle provides a beginner-friendly introduction to the world of computer science by drawing parallels to the art of cooking. Whether you're looking to grasp the fundamentals of programming, explore the vast realms of AI and Bi.
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California Institute of Technology ESSEC Business School

Bridging Data and Practice for Personalized Nutrition

Delve into the ethical considerations and applications of artificial intelligence (AI) in personalized nutrition with contributions from experts around the globe. This course reveals how big data and predictive algorithms are poised to revolutionize dietary recommendations. Participants will explore groundbreaking methods for collecting nutr.
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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!