Data Science is the most revolutionary field in the tech industry these days! All companies, whether they are smaller businesses or tech giants, use data to understand market trends and retain their competitive edge. And since more and more companies are using data science, there is an increasing demand for data scientists! This article covers the best books to learn Data Science, both for people who are new to the field and those who just want to refresh their memory!
Each of these books is extremely popular and considered a gold standard in data science. First, you can check out the books for beginners that provide basic information about Data science in R and Python. There are also some books for experts that go deep into specific sub-categories in data science such as deep learning, data mining, etc. So without further ado, let’s see these books now!
Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the “sexiest job of the 21st century.” You’ll learn the important elements of data science. You’ll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You’ll have a solid foundation for future learning and applications in your work. With data science, you can do what you want to do, and do it better. This course covers the foundations of data science, data sourcing, coding, mathematics, and statistics.
⭐️ Course Contents ⭐️
⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science
⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:46)
⌨️ Part 3: Coding (2:32:42)
⌨️ Part 4: Mathematics (4:01:09)
⌨️ Part 5: Statistics (4:44:03)
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The origin of the article: https://www.youtube.com/watch?v=ua-CiDNNj30&list=PLWKjhJtqVAblfum5WiQblKPwIbqYXkDoC&index=7
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
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For this week’s data science career interview, we got in touch with Dr Suman Sanyal, Associate Professor of Computer Science and Engineering at NIIT University. In this interview, Dr Sanyal shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.
With industry-linkage, technology and research-driven seamless education, NIIT University has been recognised for addressing the growing demand for data science experts worldwide with its industry-ready courses. The university has recently introduced B.Tech in Data Science course, which aims to deploy data sets models to solve real-world problems. The programme provides industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.
“Students with skills that are aligned to new-age technology will be of huge value. The industry today wants young, ambitious students who have the know-how on how to get things done,” Sanyal said.
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If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.
In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.
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Data science is not just about mathematics, statistics, and coding. It is about using these tools to generate new insights, and about_ telling a great story_. When data analysis and great storytelling come together, they can help us understand how the world works, challenge our (mis)conceptions of reality, and inspire us to do better. Here is a quick overview of five accessible books that do precisely that.
By Hans Rosling, Anna Rosling Rönnlund, and Ola Rosling | 352 pages.
Known for a series of influential Ted Talks, Hans Rosling (1948–2017) and his co-authors are on a mission to challenge our misconceptions about the state of the world. The authors begin their book with the startling observation that our ideas about progress in the world are wrong across the board, whether it be poverty, education, or global health. We consistently over-estimate the levels of misery in the world, and under-estimate the progress that we’ve made over the past decades.
Our lives would become unmanageable if we were to approach every problem rationally and base every single decision on data
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The buzz around data science has sent many youngsters and professionals on an upskill/reskilling spree. Prof. Raghunathan Rengasamy, the acting head of Robert Bosch Centre for Data Science and AI, IIT Madras, believes data science knowledge will soon become a necessity.
IIT Madras has been one of India’s prestigious universities offering numerous courses in data science, machine learning, and artificial intelligence in partnership with many edtech startups. For this week’s data science career interview, Analytics India Magazine spoke to Prof. Rengasamy to understand his views on the data science education market.
With more than 15 years of experience, Prof. Rengasamy is currently heading RBCDSAI-IIT Madras and teaching at the department of chemical engineering. He has co-authored a series of review articles on condition monitoring and fault detection and diagnosis. He has also been the recipient of the Young Engineer Award for the year 2000 by the Indian National Academy of Engineering (INAE) for outstanding engineers under the age of 32.
Of late, Rengaswamy has been working on engineering applications of artificial intelligence and computational microfluidics. His research work has also led to the formation of a startup, SysEng LLC, in the US, funded through an NSF STTR grant.
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