Data Research Exploration Techniques
Data Research
| Intermediate
- 11 videos | 49m 15s
- Includes Assessment
- Earns a Badge
This course explores EDA (exploratory data analysis) and data research techniques necessary to communicate with data management professionals involved in application, implementation, and facilitation of the data research mechanism. You will examine EDA as an important way to analyze extracted data by applying various visual and quantitative methods. In this 10-video course, learners acquire data exploration techniques to derive different data dimensions to derive value from the data. You will learn proper methodologies and principles for various data exploration techniques, analysis, decision-making, and visualizations to gain valuable insights from the data. This course covers how to practically implement data exploration by using R random number generator, Python, linear algebra, and plots. You will use EDA to build learning sets which can be utilized by various machine learning algorithms or even statistical modeling. You will learn to apply univariate visualization, and to use multivariate visualizations to identify the relationship among the variables. Finally, the course explores dimensionality reduction to apply different dimension reduction algorithms to deduce the data in a state which is useful for analytics.
WHAT YOU WILL LEARN
-
Specify the essential features and benefits provided by implementing exploratory data analysis
Recognize the prominent approaches that can be adopted to implement data exploration
Install and prepare r for data exploration
Demonstrate how to implement data exploration using r
Implement data exploration using plots in r -
Specify the essential packages provided by python that can be used to explore data
Implement data exploration using python's data exploration packages
Describe the approach of implementing data research using linear algebra
Work with vectors and metrics using python and r
Explore data using r, explore data with python packages, and work with vectors using python
IN THIS COURSE
-
1m 46s
-
4m 11sAfter completing this video, you will be able to specify the essential features and benefits provided by implementing exploratory data analysis. FREE ACCESS
-
3. Data Exploration Types5m 13sAfter completing this video, you will be able to recognize the prominent approaches that can be adopted to implement data exploration. FREE ACCESS
-
4. Working with R8m 44sIn this video, you will learn how to install and prepare R for data exploration. FREE ACCESS
-
5. Data Exploration in R4m 21sIn this video, you will learn how to implement data exploration using R. FREE ACCESS
-
6. Data Exploration Using Plots3m 14sLearn how to implement data exploration using plots in R. FREE ACCESS
-
7. Python Packages for Data Exploration4m 31sAfter completing this video, you will be able to specify the essential packages provided by Python that can be used to explore data. FREE ACCESS
-
8. Data Exploration Using Python3m 53sIn this video, you will learn how to implement data exploration using Python's data exploration packages. FREE ACCESS
-
9. Data Research Using Linear Algebra3mAfter completing this video, you will be able to describe the approach of implementing data research using linear algebra. FREE ACCESS
-
10. Linear Algebra for Data Research6m 36sIn this video, you will learn how to work with vectors and metrics using Python and R. FREE ACCESS
-
11. Exercise: R and Python for Data Exploration3m 49sLearn how to explore data using R, explore data with Python packages, and work with vectors in Python. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.YOU MIGHT ALSO LIKE
Rating 5.0 of 1 users
(1)
