Concepts in data science would be training and education which are prerequisites for data science. These include a solid foundation in mathematics (statistics, probability, linear algebra, and calculus), programming, machine learning, and AI, and business analysis. Facts in data science will then be the textbook stuff involved in data science, such as the facts in mathematics and machine learning that you have to deeply understand to the point where you can teach it to other people. Facts involved should not be memorized as formal education has brainwashed us to do but should be comprehended at the atomic level, where you can translate jargon into an easier language for the masses to understand. Procedures involved are the fundamentals in data science -- business understanding, data acquisition, and preparing (mining and cleaning), deployment, modeling, and visualization.

The Elements of AI online course will be translated into all official languages of the European Union during 2020–2021. The initiative is part of Finland's Presidency of the Council of the EU and it was publicized during a meeting by European employment ministers in Brussels on 10 December 2019. The initiative is worth over 1,5 million euros. The Elements of AI online course is a creation of the University of Helsinki and Finnish technology firm Reaktor. The course is free and open to all, offering basic information on artificial intelligence without requiring previous knowledge of AI or coding.

During 2020-2021, Finland will provide European citizens with free access to an online course named'The Elements of AI'. The initiative, which aims to offer EU citizens free training in future skills, was made public in Brussels on 10 December 2019, in the margins of the meeting of the EU employment ministers. The course, already published in Finnish, English, Swedish and Estonia, will be made available in all the official EU languages soon, informed the Ministry of Economic Affairs and Employment. This initiative by the Finnish Presidency aims to respond to the challenges posed by the transformation of work and to reinforce the digital leadership of the EU. 'The Elements of AI' is a series of free online courses created by the University of Helsinki and the Finnish tech company Reaktor.

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The term "influencer marketing" may call to mind jet-setting travel vloggers on YouTube or cool gamer kids streaming on Twitch. However, there are also many influencers working in the business and marketing realm. Data science influencers educate and inform on the subject of the scientific approach to extracting insights from data for real-world applications. Here are eight of the data science thought leaders topping influencer discovery searches. Andrew Ng's credentials speak for themselves.

Interactive learning is the fastest way to explore a new technology. Because you're not just reading about it--you're also manipulating it in real time to discover how it works. In the past, companies had to set up complex environments and datasets for their teams to get their heads around cloud-based infrastructure and orchestration. O'Reilly interactive learning is powered by our recent acquisition of Katacoda. Try it yourself with unlimited access for 10 days--free.

Are you looking for Best Coursera Courses 2020? You can earn a Coursera Certificate with Coursera free courses by applying for Coursera scholarship and by doing Coursera paid courses. You are going to get a 7-day free trial on Coursera when you join and start your very first subscription to do a Coursera Specializations for free. If you do not cancel your free trial you will be automatically transferred to paid subscription on the 8th Day. You can continue your Coursera Classes either by using Coursera App on mobile or on any other devices. This course provides a broad introduction to machine learning, data mining, and statistical pattern recognition. Learn and launch your career in Data Science with these best Coursera courses. A nine-course introduction to data science developed and taught by leading instructors. Develop programs to gather, clean, analyze, and visualize data. You will get new insights into your data. Learn to apply data science methods and techniques, and acquire analytical skills. This program is designed to take beginner learners to job readiness in about eight months.

This free course is published by the Massachusetts Institute of Technology (MIT). This is a week-long, self-paced course that will introduce you to Deep Learning technology and many of its industrial applications, from translation algorithms to image and object recognition, game playing, and more.

Machine Learning Engineers earn on average $166,000 - become an ideal candidate with this course! Machine Learning Engineers earn on average $166,000 - become an ideal candidate with this course! Comment Policy: Please write your comments according to the topic of this page posting. Comments containing a link will not be displayed before approval.

Industrial control systems are critical to the operation of industrial facilities, especially for critical infrastructures, such as refineries, power gri ds, and transportation systems. Similar to other information systems, a significant threat to indust rial control systems is the attack from cyberspace--the offensive maneuvers launched by "anon ymous" in the digital world that target computer-based assets with the goal of compromising a system's functions or probing for information. Owing to the importance of industrial control systems, and the possibly devastating consequences of being attacked, significant endeavors have been attempted to secure industrial control systems from cyberattacks. Among them are intrusio n detection systems that serve as the first line of defense by monitoring and reporting potenti ally malicious activities. Classical machine-learning-based intrusion detection methods usua lly generate prediction models by learning modest-sized training samples all at once. Such approac h is not always applicable to industrial control systems, as industrial control systems must proces s continuous control commands with limited computational resources in a nonstop way. To satisf y such requirements, we propose using online learning to learn prediction models from the control ling data stream. W e introduce several state-of-the-art online learning algorithms categorical ly, and illustrate their efficacies on two typically used testbeds--power system and gas pipeline. Fur ther, we explore a new cost-sensitive online learning algorithm to solve the class-imbalance pro blem that is pervasive in industrial intrusion detection systems. Our experimental results ind icate that the proposed algorithm can achieve an overall improvement in the detection rate of cybe rattacks in industrial control systems. Modern industrial control systems are microprocessor-equ ipped devices and associated communication networks used to monitor and operate physica l equipment in the industrial environment.