这些术语是什么意思？ 有什么区别？ (What do these terms mean? And what is the difference?)
Data Science and Artificial Intelligence are creating a lot of buzzes these days. But what do these terms mean? And what is the difference between them?
如今，数据科学和人工智能正在引起广泛关注。 但是这些术语是什么意思？ 它们之间有什么区别？
While the terms Data Science and Artificial Intelligence (AI) comes under the same domain and are inter-connected to each other, they have their specific applications and meaning.
虽然术语“数据科学”与“人工智能”(AI)属于同一领域，并且相互关联，但是它们具有特定的应用程序和含义。
There’s no slowing down the spread of AI and data science. Many big tech giants are extensively investing in these technologies.
不会减缓AI和数据科学的传播。 许多大型科技巨头正在对这些技术进行大量投资。 As per the recent survey, it is estimated that artificial intelligence could add $15.7 trillion to the global economy by 2030.根据最近的调查，到2030年，人工智能可以为全球经济增加15.7万亿美元。
Through this piece of writing, I will be explaining about the AI and data science concepts and their differences in detail. So, without wasting any more time, let’s get started!
通过本文，我将详细解释AI和数据科学的概念及其差异。 因此，在不浪费更多时间的情况下，让我们开始吧！
数据科学到底是什么？ (What Exactly is Data Science?)
Data science is an idea of bringing together information investigation and their associated strategies to understand the real wonders with data.
数据科学是将信息调查及其相关策略结合在一起以理解数据的真正奇迹的想法。
The need for data processing has increased significantly for industries after the explosion of large-scale data collected by them through various mediums of the Internet, such as laptops, smartphones, desktops, etc.
在行业通过互联网通过各种媒体(例如笔记本电脑，智能手机，台式机等)收集的大规模数据激增之后，对数据处理的需求已大大增加。 According to a Gartner report, 75% of the 10 million registered organizations in India are planning to invest in data science and machine learning.根据Gartner的报告，印度1000万注册组织中的75％计划投资于数据科学和机器学习。
Companies are now reliant on data to make any decisions related to almost everything about the organization. These decisions are used for better services and products, modifications, eliminating and adding various things, etc.
公司现在依靠数据来做出几乎与组织有关的所有决定。 这些决定用于更好的服务和产品，修改，消除和添加各种内容等。
And all this is possible only if you have a sufficient amount of data so that different algorithms can be applied to that data so that you get more accurate results.
只有拥有足够的数据量，并且可以对这些数据应用不同的算法，以便获得更准确的结果，所有这些都是可能的。
Data science has thus revolutionized almost all industries. Modern societies are all data-driven, and this is why data science has become an essential part of the contemporary world.
因此，数据科学彻底改变了几乎所有行业。 现代社会都是由数据驱动的，这就是为什么数据科学已成为当代世界的重要组成部分的原因。
Data science involves data extraction, manipulation, visualization, and maintenance of data to predict the occurrence of future events at various stages and processes.
数据科学涉及数据提取，操纵，可视化和数据维护，以预测各个阶段和过程中未来事件的发生。
人工智能：简介 (Artificial Intelligence: A brief introduction)
AI is just a computer capable of mimicking or imitating human thought or behavior. Within that, there is a subset known as machine learning that is now cultivating the most exciting part of AI.
AI只是一台能够模仿或模仿人类思想或行为的计算机。 在其中，有一个称为机器学习的子集正在培养AI最令人兴奋的部分。
By allowing computers to learn to solve problems on their own, machine learning has created a series of successes that once seemed almost impossible.
通过允许计算机学习自行解决问题，机器学习创造了一系列成功的经验，这些成功曾经几乎是不可能的。
In other words, AI can be defined as a collection of mathematical algorithms that make computers understand the relationships between different types and segments of data and to use this knowledge of connections to come to conclusions or make decisions. That can be accurate to a much higher degree.
换句话说，可以将AI定义为数学算法的集合，这些数学算法可以使计算机理解数据的不同类型和片段之间的关系，并使用对连接的了解来得出结论或做出决策。 这可能在更高程度上是准确的。
In short Artificial Intelligence has the universal field of “intelligent-seeming algorithms”, with machine learning currently being the leading frontier.
简而言之，人工智能具有“智能寻找算法”的普遍领域，其中机器学习目前是最前沿的领域。 According to a survey conducted by Intel, it is predicted that 70% of Indian companies will deploy AI-enabled solutions by the end of 2020.根据英特尔进行的一项调查，预计到2020年底，将有70％的印度公司部署支持AI的解决方案。
As you can see that there is a huge demand for AI, so it will be a great idea to contact machine learning companies in India if you want to integrate this technology.
如您所见，对AI的需求巨大，因此，如果您想集成该技术，最好与印度的机器学习公司联系。
数据科学与AI：有什么区别？ (Data Science Vs AI: What’s the difference?)
Although the terms Data Science and Artificial Intelligence can be related and interconnected, each of them is unique in its way and used for different purposes. Data science is a broad term, and machine learning falls within it.
尽管“数据科学”和“人工智能”这两个术语可以相互关联和相互联系，但它们各自的方式都是独特的，并用于不同的目的。 数据科学是一个广义术语，而机器学习属于其中。
Let us discuss some significant differences between AI and data science:
让我们讨论一下AI与数据科学之间的一些重大区别：
范围 (Scope)
Artificial intelligence is limited only to the implementation of the ML algorithm, while data science involves various underlying operations of data.
人工智能仅限于ML算法的实现，而数据科学涉及数据的各种基础操作。
资料类型 (Type of Data)
Artificial intelligence consists of standardized data in the form of vectors and embedding, but, on the other hand, data science will contain many different types of data such as structured, semi-structured, and unstructured data.
人工智能由矢量和嵌入形式的标准化数据组成，但是，另一方面，数据科学将包含许多不同类型的数据，例如结构化，半结构化和非结构化数据。
实用工具 (Utilities)
The utilities used in Artificial Intelligence are Mahout, Shogun, TensorFlow, PyTorch, Kaffe, Scikit-learn, and tools used in data science include Keras, SPSS, SAS, Python, R, etc.
人工智能中使用的实用工具是Mahout，Shogun，TensorFlow，PyTorch，Kaffe，Scikit-learn，而数据科学中使用的工具包括Keras，SPSS，SAS，Python，R等。
应用领域 (Applications)
Artificial intelligence applications are used in many fields such as the healthcare industry, transportation industry, robotics industry, automation industry, and manufacturing industries.
人工智能应用已用于许多领域，例如医疗保健行业，运输行业，机器人技术行业，自动化行业和制造业。
Data science applications are actively used in the field of search engines such as Google, Yahoo, Bing, including the Marketing sector, Banking, Advertising field, and many others.
数据科学应用程序在诸如Google，Yahoo，Bing之类的搜索引擎领域得到了积极的应用，包括市场部门，银行，广告领域以及许多其他领域。
处理 (Process)
In the process of artificial intelligence, predictions are made using predictive models. On the other hand, data science involves the operation of prediction, visualization, analysis, and data pre-processing.
在人工智能的过程中，使用预测模型进行预测。 另一方面，数据科学涉及预测，可视化，分析和数据预处理的操作。
技巧 (Techniques)
Artificial intelligence will use algorithms in computers to solve the problem, while data science involves many different methods of statistics.
人工智能将使用计算机中的算法来解决该问题，而数据科学则涉及许多不同的统计方法。
目的 (Purpose)
The primary objective of Artificial Intelligence is to automate the process and bring autonomy to the data model. But the primary goal of data science is to find patterns that are hidden in the data. They both have their aims and objectives which are different from each other.
人工智能的主要目标是使过程自动化并使数据模型具有自主性。 但是，数据科学的主要目标是找到隐藏在数据中的模式。 他们都有各自不同的目的和目标。
不同型号 (Different Models)
In Artificial Intelligence, models are created that are expected to resemble human comprehension and cognition. In data science, models are constructed to produce insights that are statistical for decision making.
在人工智能中，将创建类似于人类理解和认知的模型。 在数据科学中，模型被构造为产生可用于决策的统计见解。
科学加工程度 (Degree of Scientific Processing)
Artificial intelligence will use a much higher level of scientific processing than data science which uses less scientific processing.
相比数据科学，人工智能将使用较少的科学处理，从而将使用更高水平的科学处理。
底线 (Bottom Lines)
In this data science vs AI blog, we came to know that the two terms are used interchangeably. Artificial intelligence is yet to be discovered, but on the other hand, data science has already started making a significant change in the market. Data science converts data, which can be used for visualization and analysis.
在这个数据科学与AI博客中，我们知道这两个术语可以互换使用。 人工智能尚未发现，但另一方面，数据科学已经开始在市场上发生重大变化。 数据科学转换数据，可用于可视化和分析。
With the help of Artificial Intelligence, new products are created that are better than before, and it also brings autonomy by doing many things automatically. With the help of data science, data is analyzed, based on which careful business decisions are made that provide many benefits to companies.
在人工智能的帮助下，创造了比以前更好的新产品，并且通过自动执行许多操作也带来了自治。 借助数据科学，可以对数据进行分析，然后根据这些数据做出谨慎的业务决策，从而为公司带来许多好处。
If you want to implement these technologies into your services, then you must hire AI developers in India. They offer various AI learning solutions to businesses.
如果要在服务中实现这些技术，则必须在印度雇用AI开发人员。 他们为企业提供各种AI学习解决方案。