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How analytics helps human resources in making decision towards data driven

In a highly competitive and dynamic business environment, HR role is no more limited to management of workforce. An intensely competitive marketplace demands that you play more roles than one. You have to be a critic, a qualified statistician and a keen observer of how your workforce functions in order to provide valuable insights and analytical input to keep your organization achieve its goals and objectives.  Data is the key to this strategy helping you manage your workforce efficiently and effectively. However, it is imperative to understand that having a large dataset is of little or no importance if you fail to utilise it properly. And the key to efficient utilisation is to first decode what is relevant and useful. But then the million dollar question is how you will find the time and resources to take advantage of the information at your command. This is where the importance of people analytics is realised. What is people analytics? People Analytics is not a passing fad.
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How is IoT Revolutionising Agriculture

When we think of IoT applications, growing crops or raising livestock are not the first visuals that come to our mind. According to Markets and Markets, the market for smart agriculture is likely to evolve up to $11.23 billion by the year 2022. The reason for this being farmers are getting more connected as they realise the potential of IoT technologies in allowing to minimise operational costs while still achieving better results. The examples include less water usage, lower livestock losses, and higher crops. Planning to pursue your career in the field of IoT? Join Introduction to IoT program from a reputed institution to learn the fundamentals and applications of the subject matter. The providers of IoT technology continue to create platforms that can communicate, process, and sense accurately measured environmental data to assist improve farm performance. There is a range of technologies behind these IoT platforms that embraces drones, LED lights, energy harvesting, tra
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How to Get Hands-On With Machine Learning

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Machine Learning is a new and exciting field of study that focuses on the development of computer programs that gives it the ability to think like humans and solve problems based on previous experiences.  A truly exciting technology, ML is currently being used in multiple fields and industries like entertainment, videos surveillance, spam filtering, online customer support, search engine result refining, Social Media services, etc. ML enables analysis of massive quantities of data allowing computers to tackle tasks on their own without a need for express commands. Jigsaw academy reviews and ratings will show you as to how this reputable online training institute helps you build your career in the field of Big Data, AI and ML. It is rightly said that best way to learn is to do it. In order to understand the full capabilities and abilities of Machine Learning (ML), you have to get hands-on with it, which is what exactly people interested a career in this fast-growing technol
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Machine Learning- How to Kickstart Your Learning Journey

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When it comes to pursuing a career in machine learning, it is not as simple as learning and getting ahead in their careers. Beginners are often baffled with innumerable learning resources out there. This guide tells precisely where to kick start your expertise towards ML. Step 1: Maths and Statistics The foremost thing is the skill to comprehending problems through a mathematical instinct. It is highly recommended starting with fundamentals in linear algebra, then slowly moving to calculus. It may be difficult to master them at the beginning but given the time and practice with working, these areas will be acquainted and comfortable to work on. Another important subject that follows math is statistics. For any ML algorithm to be understood clearly, statistics is crucial. Hence, fundamental knowledge in stats should be learnt hand in hand. Step 2. Programming For beginners, programming is sometimes appalling to learn. Obviously, it might be daunting and difficult
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Location: Bengaluru, Karnataka, India
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How to Get Your Data Scientist Career Started

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When people want to launch data science careers but haven't yet started, they're in a scenario that's understandably intimidating and full of ambiguity. However, when they follow mapped-out methods that help them get into the field, success becomes easier to visualize and attain. Here are a few steps to get started: 1. Talk to People in the Field                                                                                        Although it's good to read articles written by data science experts or watch YouTube videos of such people, it's best if aspiring data scientists can have head-on conversations with people presently in the field. Talking to people who are in the know and ready to share their experiences is vital. It could help a data scientist-to-be confirm that the career path is the right one for them or highlight why another job choice is more suitable. 2. Learn About Specializations Contrary to what some people may think,
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Location: Bengaluru, Karnataka, India
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Ethics Education in Data Science

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Data scientists in academia and industry are increasingly identifying the importance of incorporating ethics into data science curricula. Lately, a group of faculty and students assembled at New York University before the annual FAT* conference to discuss the potentials and challenges of teaching data science ethics, and to learn from one another’s experiences in the classroom. This post is the first of two which will encapsulate the discussions had at this workshop. There is common agreement that data science ethics should be taught, but less consensus about what its objectives should be or how they should be pursued. As the field is so promising, there is considerable room for groundbreaking thinking about what data science ethics ought to mean. In some respects, its goal may be the formation of “future citizens” of data science who are invested in the welfare of their communities and the world, and comprehend the social and political role of data science therein. However th
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Location: Bengaluru, Karnataka, India
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Top 5 Executive Data Science Courses in India

In a survey organized among 961 students across 18 cities of India, the top 5 executive data science programs have been revealed. The survey offered an instrumental insight into the data science learning of this country. How was it done? A dedicated online questionnaire was developed and the link was sent to over 30 schools offering data science programs, of which 21 retorted within the given time frame. The participants were requested to fill an elaborated form with four main parameters — course content, student experience, faculty, and other features like external collaboration. The Procedure of Information Collection Seven schools were rejected right away due to incomplete data, lack of supporting documents or non-fulfillment of eligibility criteria. The eligibility criteria for this ranking were:   The course should be an abiding program in data science/ analytics (at least 5 months), Should be executed by a university. Processing of Information In
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Location: Bengaluru, Karnataka, India
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