Course Provider
Course Highlights:
- This course is a part of the AI Ascend program.
- Initial data exploration is the first step in any data analytics pipeline. This course will equip the participant with the necessary tools of summarizing and visualizing key parameters from the data and draw useful inferences from it.
- Job Roles-
- Data Scientist
What will you learn in Exploratory Data Analysis course?
At the end of this course, you should be able to:
- Understand the measures of central tendency and dispersion.
- Be able to explore your data through histograms, box plots, and bar plots.
- Explore pairs of variables using scatterplots and scatterplot matrices.
- Understand the intuition behind and be able to carry out PCA.
- Realize how all these techniques can be sewed together into an analytics pipeline in important business scenariosb.abc
Exploratory Data Analysis
- Skill Type Emerging Tech
- Domain Artificial intelligence
- Course Category Deepskilling Course
- Certificate Earned Joint Co-Branded Participation Certificate
- Nasscom assessment Available
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- Course Price Free
- Course Duration 5 Hours
Why you should take Exploratory Data Analysis course?
At the end of this course, you should be able to:
- Understand the measures of central tendency and dispersion.
- Be able to explore your data through histograms, box plots, and bar plots.
- Explore pairs of variables using scatterplots and scatterplot matrices.
- Understand the intuition behind and be able to carry out PCA.
- Realize how all these techniques can be sewed together into an analytics pipeline in important business scenariosb.abc
Who should take Exploratory Data Analysis course?
- BE/ BTech students-any stream
- Non-engineering students-STEM background
- Working Professionals
Curriculum
- This course covers the most widely used techniques for initial data exploration and inference:
- Obtaining the basic summary statistics for each variable in the data
- Visualizing the distributions of each variable
- Visualizing and inferring on the correlation trend between pairs of variables
- Reducing the number of multiple correlated variables to a few independent variables using principal component analysis (PCA)
- Testing hypothesis for one sample mean
- Real-world case study
Tools you will learn in Exploratory Data Analysis course
- Central Tendency
- Mean
- Median
- Mode
- Variance
- Standard Deviation
- Correlation, Boxplot
- Scatterplot
- Dimensionality Reduction