Formulating the Null and the alternate hypothesis for normality test; Choice of null hypothesis based on absence of action and the vice versa for alternate hypothesis; checking for normality in Minitab; interpreting the Q–Q plot; Comparing the computed'p' value with α (alpha) for taking the decision on whether or not to take the action; Step to performing the 1 sample Z test, selection of appropriate hypothesis in minitab.

Here is a list of the best courses in Data Science and Machine Learning from Udemy. Get these and other Udemy courses for $12, 90-95% off original price. Udemy.com is an online marketplace for learning, their data science content is updated regularly by the instructors who created good courses (filled with actionable tools) and bite-size lessons that help you cover defined topics at your own pace. Ready to be thrown into the deep end and learn the real problems a data scientist faces on a daily basis? Data Science management consultant Kirill Eremenko teaches this intense, best-selling course to over 23K students and counting.

The co-founder of online education platform Coursera has made it his mission to build talent for AI through his new project, deeplearning.ai. Andrew is preparing courses on deep-learning--advanced AI inspired by the human brain's neural networks--that will be available on Coursera. In an interview with ET's J Vignesh, the former chief scientist at Baidu also spoke about how technology disruption can help countries like India leapfrog and take a lead in the new world. Edited excerpts: How are we progressing towards the concept of singularity, or general intelligence, from sector-specific artificial intelligence? That is hard to project.

Ensuring stable, secure and reliable operations of the power grid is a primary concern for system operators [1]. Security assessment and control actions heavily rely on the accuracy of the assumed power system model and its parameters and of the estimated state [2]. Thus, inaccuracies in state estimation data or in the networked dynamic model can impact the assessment of the system stability and the efficacy of the corresponding control measures. In this paper, we explore the possibility to leverage the proliferation of Phasor Measurement Units (PMUs) that collect time synchronous data in a distributed way, for validating the assumed power system model and the current system state. In particular, our goal is to develop a data-efficient learning framework for performing an online reconstruction of the dynamic model using the minimal number of assumptions and exclusively relying on the PMU measurements. A number of recent works showed promising results in attacking this problem [3], [4], [5], [6], [7], [8], [9]. Here, we propose to extend the scope of existing works to the problem of extracting the dynamic state matrix from PMU measurements in a purely data-driven way, without assuming any knowledge of model parameters. We take advantage of the separation of scales that exists in the regime of ambient fluctuations around the steady state leading to power system dynamics excited by stochastic load variations.

Bill Gates proclaimed in a recent graduation ceremony, that artificial intelligence (AI), energy, and bio science are three most exciting and rewarding career choices today's young college graduates can choose from. I have come to believe strongly that some of the most important questions of our generation - related to sustainability, energy generation and distribution, transportation, access to basic amenities of life etc., are dependent on how intelligently we can mix the the first two branches of knowledge Mr. Gates mentions. I am a semiconductor professional with 8 years of post-PhD experience in a top technology company. I take pride in the fact that I work in the cross-section of physical electronics which directly contributes to the energy sector. I develop power semiconductor devices.

The study analyzes how the advancements in technology and its increased penetration in the education market, institutions have begun to experience a rapid change in the teaching delivery model. Governments over the world are concentrating on building up a computerized instruction condition through gifts and subsidizes, bringing about an expansion in the money related help for instructive foundations particularly those working in developing regions. This has helped numerous foundations to adjust to current and progressed instructive techniques. The 76-paged, comprehensive report added to the Education archive offers predictions and future prospects of the industry, including market size and share on account of risk factors, market trends and opportunities, pipeline products and technological innovations. NLP is the field of software engineering, counterfeit consciousness and computational semantics that are related with the collaborations amongst PCs and human.

One of the most common problems learners have when jumping into Machine Learning and Data Science is the steep learning curve, and when you add to this the complexity of learning programming languages like Python or R you can get demotivated and lose interest fast. In this course you will learn the basic concepts of machine learning using a visual tool. Where you can just drag drop machine learning algorithms and all other functionality hiding the ugliness of code, making it much more easier to grasp the fundamental concepts. I will "hand-hold" you as we build from scratch 2 different types of supervised machine learning algorithms used in the real world, across several industries and I will explain where and how they are used. The course will teach you those fundamental concepts by implementing practical exercises which are based on live examples.

Just to let you know, if you buy something featured here, Mashable might earn an affiliate commission. It's time to give that ol' brain of yours a thorough dusting-off, so to speak: Through the Full Neuro-Linguistic Programming (NLP) Diploma Course, you might be able to hack your way to an improved way of thinking. NLP, in case you haven't heard, is a set of rules and techniques designed to help you shape your personal psychology and achieve self-actualization. Some see it as pseudo-science, while others swear by it. Either way, the idea is that you can train your brain to eliminate phobias, tweak bad habits, and even gain a deeper understanding of others' body language -- skills that are beneficial in the workplace, your social life, and beyond.

I would recommend that you start with Introduction to Statistical Learning with R (usually shortened as ISLR). A lot of people have adapted the examples to Python if you google a bit and it's an excellent book that hides just enough complexity to not be overwhelming. Plus, once you have a good understanding of all of it, you can either graduate to the more extensive version (Elements of Statistical Learning, usually shortened as ESL) for a more rigorous treatment of the same thing, or choose to go for something different like Bishop's Pattern Recognition and Machine Learning. ISLR is free as a pdf and has a corresponding MOOC. ESL doesn't, but is also free on the author's website.

The programme has been created based on the experience of leading American and European universities, such as Stanford University (U.S.) and EPFL (Switzerland). Also taken into consideration when creating the faculty was the School of Data Analysis, which is one of the strongest postgraduate schools in the field of computer science in Russia. In the faculty, learning is based on practice and projects. National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communications, IT, mathematics, engineering, and more.