And so we've come all the way around…and we're at the final video…for techniques and concepts of big data.…Before we leave,…I wanted to give you some ideas for further learning.…We're going to base this…on the data science Venn diagram…that we talked about earlier,…which talks about coding…and statistics and domain knowledge.…At Lynda.com you can find…a really wide range of coding courses.…If you're new to coding,…a really nice way to do this…might be either with Bash Scripting…through the command line or with Python.…
Similarly, statistics,…there's a range of courses available at Lynda,…these are actually on my courses…about using the programming language R,…which is for statistics,…or processing for data visualization.…I also have courses on SPSS,…another statistical package.…Although it's not explicitly part…of the data science Venn diagram,…databases are absolutely central…in this sort of split between coding and statistics…and there's a great selection…of database courses at Lynda.com,…such as the foundations courses…
Author
Released
10/22/2014- Evaluate the demand for data science in business, research, and consumer technology.
- Assess the careers and skills in data science.
- Review the ethical issues in data science.
- Explore data visualization with graphing tools.
- Discover how data scientists use tools such as Hadoop and Excel.
Skill Level Beginner
Duration
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Introduction
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Welcome1m 13s
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What Is Big Data?
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2. How Is Big Data used?
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3. Big Data and Data Science
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4. Ethics in Big Data
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Challenges with anonymity5m 51s
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5. Sources and Structures of Big Data
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Machine-generated data4m 20s
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Structured data2m 47s
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Unstructured data5m 50s
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6. Storing Big Data
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7. Preparing Data for Analysis
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Challenges with data quality3m 38s
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Additional Vs of big data4m 41s
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8. Big Data Analysis
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Predictive analytics5m 20s
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Big data visualization4m 17s
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Conclusion
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Next steps1m 58s
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Video: Next steps