Section 1 : Introduction
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Lecture 1 | INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM |
Section 2 : Defining Big Data
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Lecture 1 | The volume, velocity, and variety of big data | 00:05:51 Duration |
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Lecture 2 | Artificial intelligence and machine learning | |
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Lecture 3 | Social media and the Internet of Things | 00:05:52 Duration |
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Lecture 4 | Data warehouses, data lakes, and the cloud | 00:08:25 Duration |
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Lecture 5 | Edge computing and fog computing |
Section 3 : How Is Big Data Used
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Lecture 1 | Big data for business strategy | 00:06:49 Duration |
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Lecture 2 | Big data for customer interactions | 00:04:28 Duration |
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Lecture 3 | Big data for applications | 00:04:41 Duration |
Section 4 : Big Data and Data Science
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Lecture 1 | Ten ways big data is different from small data | 00:05:59 Duration |
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Lecture 2 | The three facets of data science | 00:02:22 Duration |
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Lecture 3 | Data science without big data | 00:02:41 Duration |
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Lecture 4 | Big data without data science | 00:03:20 Duration |
Section 5 : Ethics in Big Data
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Lecture 1 | Big data and privacy | |
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Lecture 2 | Data governance | 00:06:02 Duration |
Section 6 : Data Logistics
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Lecture 1 | Structured, semi-structured, and unstructured data | 00:06:06 Duration |
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Lecture 2 | Batch processing vs | 00:04:22 Duration |
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Lecture 3 | Distributed storage and processing | 00:03:08 Duration |
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Lecture 4 | An evolving data landscape | 00:05:48 Duration |
Section 7 : Analyzing Big Data
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Lecture 1 | Challenges with data preparation | |
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Lecture 2 | Visualizing big data | 00:05:13 Duration |
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Lecture 3 | Data mining | 00:04:39 Duration |
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Lecture 4 | Text analytics | |
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Lecture 5 | Sentiment analysis | 00:04:48 Duration |
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Lecture 6 | Predictive analytics | 00:04:07 Duration |
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Lecture 7 | Anomaly detection | 00:03:59 Duration |