Difference between revisions of "Data Science"
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* [http://en.wikipedia.org/wiki/Data_science Data Science | Wikipedia] | * [http://en.wikipedia.org/wiki/Data_science Data Science | Wikipedia] | ||
* [http://towardsdatascience.com/introduction-to-statistics-e9d72d818745 Data science concepts you need to know! Part 1 | Michael Barber - Towards Data Science] | * [http://towardsdatascience.com/introduction-to-statistics-e9d72d818745 Data science concepts you need to know! Part 1 | Michael Barber - Towards Data Science] | ||
− | [http://www.datasciencecentral.com/profiles/blogs/data-fallacies-to-avoid-an-illustrated-collection-of-mistakes Data Fallacies to Avoid - An Illustrated Collection of Mistakes People Often Make When Analyzing Data - Tom Bransby] | + | * [http://www.datasciencecentral.com/profiles/blogs/data-fallacies-to-avoid-an-illustrated-collection-of-mistakes Data Fallacies to Avoid - An Illustrated Collection of Mistakes People Often Make When Analyzing Data - Tom Bransby] |
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+ | <b>Data Science in 60 Minutes | What Is Data Science | Neural Networks | Great Learning | ||
+ | </b><br>Data science is the most popular domain. All the companies are using the Data Science technique as it helps them to use their data and get insights from them. It has also become the most demanding job of the 21st century. Every organization is looking for candidates with knowledge of data science. Understanding all of this, we have come up with this 'Data Science in 60 Minutes' Tutorial. Data Science is the area of study which involves extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes. It helps you to discover hidden patterns from the raw data. The term Data Science has emerged because of the evolution of mathematical statistics, data analysis, and big data. It is an interdisciplinary field that allows you to extract knowledge from structured or unstructured data. Data science enables you to translate a business problem into a research project and then translate it back into a practical solution. It also uses the most powerful hardware, programming systems, and most efficient algorithms to solve the data-related problems. It is the future of artificial intelligence. In this tutorial, we have covered all the important topics such as What is Data Science, What are its features, When to use this technique, and much more. Visit Great Learning Academy, to get access to 80+ free courses with 1000+ hours of content on Data Science, Data Analytics, Artificial Intelligence, Big Data, Cloud, Management, Cybersecurity and many more. These are supplemented with free projects, assignments, datasets, quizzes. You can earn a certificate of completion at the end of the course for free. https://glacad.me/3duVMLE Get the free Great Learning App for a seamless experience, enrol for free courses and watch them offline by downloading them. http://glacad.me/3cSKlNl | ||
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+ | <youtube>r-uOLxNrNk8</youtube> | ||
+ | <b>Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn) | ||
+ | </b><br>Learn Data Analysis with Python in this comprehensive tutorial for beginners, with exercises included! Data Analysis has been around for a long time, but up until a few years ago, it was practiced using closed, expensive and limited tools like Excel or Tableau. Python, SQL and other open libraries have changed Data Analysis forever. In this tutorial you'll learn the whole process of Data Analysis: reading data from multiple sources (CSVs, SQL, Excel, etc), processing them using NumPy and Pandas, visualize them using Matplotlib and Seaborn and clean and process it to create reports. Additionally, we've included a thorough Jupyter Notebook tutorial, and a quick Python reference to refresh your programming skills. Check out all Data Science courses from RMOTR: https://rmotr.com | ||
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[http://towardsdatascience.com/the-what-where-and-how-of-data-science-6dda1af98671 The What, Where and How of Data Science | Iliya Valchanov] | [http://towardsdatascience.com/the-what-where-and-how-of-data-science-6dda1af98671 The What, Where and How of Data Science | Iliya Valchanov] | ||
https://cdn-images-1.medium.com/max/800/1*z5VIYRsdFI-b8WPVyFPeWQ.png | https://cdn-images-1.medium.com/max/800/1*z5VIYRsdFI-b8WPVyFPeWQ.png |
Revision as of 09:38, 7 September 2020
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- What is AI?
- AI Governance
- Data Science | Wikipedia
- Data science concepts you need to know! Part 1 | Michael Barber - Towards Data Science
- Data Fallacies to Avoid - An Illustrated Collection of Mistakes People Often Make When Analyzing Data - Tom Bransby
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The What, Where and How of Data Science | Iliya Valchanov