LII:Big Data Analytics - Revision history

Shawndouglas: Updated

2024-05-13T14:10:09Z

Updated

← Older revision		Revision as of 14:10, 13 May 2024
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	'''Publication date''': 2024		'''Publication date''': 2024

	This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $199. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort. Access to the class began ~~January 2,~~ 2024, and the free audit track is open until ~~March 12~~.		This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $199. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort. Access to the class began in May 2024, and the free audit track is open until July 22.

	The edX course description:		The edX course description:
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	===The course===		===The course===
	[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class began ~~January 2,~~ 2024, and the free audit track is open until ~~March 12~~.		[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class began in May 2024, and the free audit track is open until July 22.

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	[[Category:LII:Courses]]		[[Category:LII:Courses]]

Shawndouglas: Updated

2024-01-02T16:07:20Z

Updated

← Older revision		Revision as of 16:07, 2 January 2024
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	'''License for content''': Unknown		'''License for content''': Unknown

	'''Publication date''': ~~2023~~		'''Publication date''': 2024

	This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $199. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort.		This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $199. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort. Access to the class began January 2, 2024, and the free audit track is open until March 12.

	The edX course description:		The edX course description:
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	===The course===		===The course===
	[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class began ~~in the spring of 2023~~, and the free audit track is open until ~~August 21, 2023~~.		[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class began January 2, 2024, and the free audit track is open until March 12.

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	[[Category:LII:Courses]]		[[Category:LII:Courses]]

Shawndouglas: Updated

2023-06-12T17:17:54Z

Updated

← Older revision		Revision as of 17:17, 12 June 2023
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	'''License for content''': Unknown		'''License for content''': Unknown

	'''Publication date''': ~~2022~~		'''Publication date''': 2023

	This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $199. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort.		This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $199. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort.
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	===The course===		===The course===
	[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class began in the ~~fall~~ of ~~2022~~, and the free audit track is open until ~~January 23~~, 2023.		[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class began in the spring of 2023, and the free audit track is open until August 21, 2023.

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	[[Category:LII:Courses]]		[[Category:LII:Courses]]

Shawndouglas: Updated due to website changes

2022-11-14T18:06:22Z

Updated due to website changes

← Older revision		Revision as of 18:06, 14 November 2022
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	'''License for content''': Unknown		'''License for content''': Unknown

	'''Publication date''': ~~2021~~		'''Publication date''': 2022

	This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $199. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort.		This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $199. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort.
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	The edX course description:		The edX course description:

	"Gain essential skills in today’s digital age to store, process and ~~analyse~~ data to inform business decisions.		"Gain essential skills in today’s digital age to store, process and analyze data to inform business decisions.

	In this course, part of the Big Data MicroMasters program, you will develop your knowledge of big data analytics and enhance your programming and mathematical skills. You will learn to use essential analytic tools such as Apache Spark and R.		In this course, part of the Big Data MicroMasters program, you will develop your knowledge of big data analytics and enhance your programming and mathematical skills. You will learn to use essential analytic tools such as Apache Spark and R.
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	===The course===		===The course===
	[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class is ~~scheduled to begin June 7~~.		[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class began in the fall of 2022, and the free audit track is open until January 23, 2023.

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	[[Category:LII:Courses]]		[[Category:LII:Courses]]

Shawndouglas: Cats

2022-02-09T19:53:49Z

Cats

← Older revision		Revision as of 19:53, 9 February 2022
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Shawndouglas: Tweak

2021-06-07T19:09:03Z

Tweak

← Older revision		Revision as of 19:09, 7 June 2021
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	'''About the authors'''		'''About the authors'''

	Three instructors (Mitchell, Tuke, and Suter) are affiliated with this course in some fashion. To learn more about each instructor, go to the [https://www.edx.org/course/big-data-analytics edX course page] and click on the name of each instructor.		Three instructors (Mitchell, Tuke, and Suter) are affiliated with this course in some fashion. To learn more about each instructor, go to the [https://www.edx.org/course/big-data-analytics-2 edX course page] and click on the name of each instructor.

	==General layout and contents of the course==		==General layout and contents of the course==
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	===The course===		===The course===
	[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class is scheduled to begin ~~April 12~~.		[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class is scheduled to begin June 7.

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Shawndouglas: /* General layout and contents of the course */

2021-04-12T22:19:25Z

General layout and contents of the course

← Older revision		Revision as of 22:19, 12 April 2021
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	===The course===		===The course===
	[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class is scheduled to begin ~~February 28~~.		[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class is scheduled to begin April 12.

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Shawndouglas: /* The course */

2021-01-11T19:11:05Z

The course

← Older revision		Revision as of 19:11, 11 January 2021
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	===The course===		===The course===
	[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class is ~~sheduled~~ to begin February 28.		[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class is scheduled to begin February 28.

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Shawndouglas: Tweaks

2021-01-11T19:10:02Z

Tweaks

← Older revision		Revision as of 19:10, 11 January 2021
Line 6:		Line 6:
	'''License for content''': Unknown		'''License for content''': Unknown

	'''Publication date''': ~~2020~~		'''Publication date''': 2021

	This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $~~150~~. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort.		This is a University of Adelaide course that is released on the edX platform. The ten-week course is designed for students to "learn key technologies and techniques, including R and Apache Spark, to analyze large-scale data sets to uncover valuable business information." The course is free to take, with a Verified Certificate of completion available for $199. This course is also part of Adelaide's Big Data MicroMasters program. The course requires on average eight to ten hours a week of effort.

	The edX course description:		The edX course description:
Line 40:		Line 40:

	===The course===		===The course===
	[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics Computer Science] category. Access to the class ~~begins Februay 3, 2020~~.		[[File:PDF.png\|40px\|link=https://www.edx.org/course/big-data-analytics-2]]: The course can be found on the edX site, under the [https://www.edx.org/course/big-data-analytics-2 Computer Science] category. Access to the class is sheduled to begin February 28.

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Shawndouglas at 17:02, 3 February 2020

2020-02-03T17:02:11Z

← Older revision		Revision as of 17:02, 3 February 2020
Line 34:		Line 34:
	'''About the authors'''		'''About the authors'''

	Three instructors are affiliated with this course in some fashion. To learn more about each instructor, go to the [https://www.edx.org/course/big-data-analytics edX course page] and click on the name of each instructor.		Three instructors (Mitchell, Tuke, and Suter) are affiliated with this course in some fashion. To learn more about each instructor, go to the [https://www.edx.org/course/big-data-analytics edX course page] and click on the name of each instructor.

	==General layout and contents of the course==		==General layout and contents of the course==