Learn Data with Bash Shell/ Linux: Project-based Learning, An animated course for learning data analytics and big data pre-processing with Bash shell scripting in Linux
- Created by Scientific Programmer
- 37 mins on-demand video
- 50 articles
- 13 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
- Have a coupon?
What you'll learn
- Use Bash to quickly sort, search, match, replace, clean and optimise various aspect of a data set
- Use bash in processing real-world data sets (included)
- Use Bash commands and scripting
- Use Regular Expressions (RegEX) in Bash
- Use AWK programming language commands to tweak and format data
- Use SED and GREP to quickly search in large-scale data sets
Description
Udemy Early Access Program Reviews (5 out of 5 Stars):
"This is one of the best course I have reviewed in Udemy. All the chapters are very useful. The instructor explained exactly what you need to use Bash as your data analysis tool in your pocket. I look forward more coursed from this Instructor. The instructor is very experienced, explanations are on point. Than you for creating a great course." - Tarique Syed
"The instructor was very engaging. Changed a boring, hard-to-understand tool into something usable and easy-to-use, all the while making it fun to learn." - Prat Ram
"Well done. Well - structured and explained course. Will definitely recommend the course to my course. From my point of view, everything was OK in the course." - Sem Milaserdov
"Overall, the course delivered what promised with a good resource for those who want to learn and do more. The course is filled with resource and the educator attached his own book on the subject for the learners." - Afshin Kalantari
"It's a very well organized course, from the background, basic Linux cli which everyone should be to build data processing scenarios. wonderful class." - Charley Guan
This beginner friendly course is specifically designed to show you how to use Bash commands and shell programming to handle textual data which can be a csv format data or systems log file. In this course you will learn Bash by doing projects.
However, you need to understand the fact that Bash may not the best way to handle all kinds of data! But there often comes a time when you are provided with a pure Bash environment, such as what you get in the common Linux based Super-computers and you just want an early result or view of the data before you drive into the real programming, using Python, R and SQL, SPSS, and so on. Expertise in these data-intensive languages also comes at the price of spending a lot of time on them.
In contrast, bash scripting is simple, easy to learn and perfect for mining textual data! Particularly if you deal with genomics, microarrays, social networks, life sciences, and so on. It can help you to quickly sort, search, match, replace, clean and optimise various aspect of your data, and you wouldn’t need to go through any tough learning curves. We strongly believe, learning and using Bash shell scripting should be the first step if you want to say, Hello Big Data!
This course starts with some practical bash-based flat file data mining projects involving:
University ranking data
Facebook data
AU Crime Data
(Data sets and documentations are provided at the end of each section)
If you haven’t used Bash before, feel free to skip the projects and get to the tutorials part (supporting materials: eBook). Read the tutorials and then come back to the projects again. The tutorial section will introduce with bash scripting, regular expressions, AWK, sed, grep and so on. Finally, it gives you a concise beginner friendly guide to the big data landscape including an overview of the critical Big Data tools such as HDFS, MapReduce, YARN, Flume, Hive and more. The course finishes with a near-complete list of references to all the relevant command line and Big data tools.
Who is the target audience?
- Students who want to learn Bash and the command line to improve their career prospects
- Researchers who want to add Bash and other command line tools to their bag of tricks
- Scientists who want to learn to explore and analyze the data that their lab generates
- Journalists who want to polish their reporting by analyzing publicly-available datasets
- Anyone wants to deal with Big Data
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