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Book Reviews Book title: Digitisation Perspectives Type: book Author: Ruth Rikowski Year: 2010 Edition: 1st ISBN: 9460912982 Publisher: Sense Publishers Publisher's Description: This book examines various views and perspectives on digitisation. As Simon Tanner, Director Digital Consultancy, King's College London says in the Foreword: "Digitisation has become a cultural, scholastic, economic and political imperative and raises many issues for our consideration." Furthermore, that the book: "...seeks to address and answer some of the big questions of digitisation... It succeeds on many levels..." There are 22 contributors in the book, all experts in their fields. The book is divided into six parts: Part 1: 'Background and Overview to Digitisation and Digital Libraries' Part 2: 'Digitisation and Higher Education' Part 3: 'Digitisation and Inequalities' Part 4: 'Digital Libraries, Reference Services and Citation Indexing' Part 5: 'Digitisation of Rare, Valued and Scholarly Works' Part 6: 'Futuristic Developments of Digitisation' Topics covered include electronic theses, search engine technology, digitisation in Africa, citation indexing, reference services, the Scholarly Publishing and Academic Resources Coalition, new media and scholarly publishing. The final chapter explores virtual libraries, and poses some interesting questions for possible futures. The book will be of particular interest to information professionals, educators, librarians, academics and I.T. and knowledge experts. Ruth Rikowski concludes by indicating that: "...hopefully, the book will provide a source of inspiration for further research, leading to some more effective ways to proceed with the digitisation process. Also, that it will be possible to do this within a framework that can be used for good rather than ill, and for the benefit of many." Reviewer: Eric Jukes (Formerly of College of Haringey, Enfield and North East London) Book Rating: 5/5 Buy this book from Amazon  Review Summary

Use your smart phone to digitise your student's work and make an online assessment record. Use images, files or Videos from YouTube. Add comments and much more. You can also upload images of work through the website. Why not get your class to upload their own? Really excited about this! http://ictmagic.wikispaces.com/Planning+%26+Assessment

A useful site for creating online books and magazines. It's a get way to digitise your children's work to display online. http://ictmagic.wikispaces.com/ICT+%26+Web+Tools

Home > Data Science > How to learn Data Science in 2021? Data Science (DS) is a great, promising, and most demanding career. But are you confused about being a beginner and wanna know the Right Way to Learn DS? Technology is more into digitisation and due to this extensive transformation, huge data is expected to be produced in the coming future. To make use of such big data we need data scientists who can layout, design and filter the data in an organized way. All things considered, with a huge number of options available choosing the correct curriculum program and admission to the right institute is important. Besides all this, the course and institute to be suitable for your requirement are extremely difficult. While online courses are an incredible path for some to upskill, good opportunities from top colleges and universities are the platform for data scientists to test their knowledge in their field. Here are the five essential guidelines to turn into an expert in Data Science: Get a Data Science certificate or similar degree To get an opportunity as an entry-level data researcher, one would require a four-year certification in DS, math, insights and software engineering. Degrees can likewise give temporary job openings. All things considered if you have just secured a 4 yr certification in a different background through online e-courses or basic boot camps and workshops. The focus should be given to mastering the skills required for DS. Take a look at this course from AntWak on Data Engineering delivered by top global experts. Take comprehensive courses and devote time to learning You can become a top-class data researcher by taking a full course at a time. It will be the skill and instruments needed to turn into a data researcher, many critical projects and coaching help. A variety of such courses are available online that offer top to bottom analysis of subjects, for example, data scratching, AI, big data analysis and many more. To begin your learning

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