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Analyze Data
  • Level Professional
  • Duration 21 hours
  • Course by CertNexus
  • Offered by

About

This course is designed for business professionals that want to learn how to analyze data to gain insight, use statistical analysis methods to explore the underlying distribution of data, use visualizations such as histograms, scatter plots, and maps to analyze data and preprocess data to produce a dataset ready for training. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.

Modules

Overview

    • 1 Videos
    • 2 Readings
Show info about module content

1 Videos

  • Course Intro: Analyze Data

2 Readings

  • Overview
  • Get help and meet other learners. Join your Community!

Identify Features

    • 4 Videos
Show info about module content

4 Videos

  • Exploratory Data Analysis
  • Dataset Content and Format
  • Analysis of Feature Types
  • Target Features

Identify Issues with Features

    • 4 Videos
Show info about module content

4 Videos

  • Feature Relevance
  • Representative Data and Sampling Techniques
  • Imbalanced Datasets
  • Errors, Outliers, and Noise

Identify Correlations

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Examining Data

1 Videos

  • Correlations

1 Readings

  • Guidelines for Examining Data

Evaluate What You've Learned

    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Examining Data

1 Discussions

  • Reflect on What You've Learned

Overview

    • 1 Readings
Show info about module content

1 Readings

  • Overview

Distributions

    • 2 Videos
Show info about module content

2 Videos

  • Frequency and Probability Distributions
  • Normal and Non-Normal Distributions

Descriptive Statistics

    • 7 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Exploring the Underlying Distribution of Data

7 Videos

  • Descriptive Statistical Analysis
  • Central Tendency
  • Variability and Range Measures
  • Variance
  • Standard Deviation
  • Skewness
  • Kurtosis

1 Readings

  • Guidelines for Exploring the Underlying Distribution of Data

Evaluate What You've Learned

    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Exploring the Underlying Distribution of Data

1 Discussions

  • Reflect on What You've Learned

Overview

    • 1 Readings
Show info about module content

1 Readings

  • Overview

Histograms, Box Plots, and Violin Plots

    • 3 Videos
    • 2 Readings
    • 2 Lab
Show info about module content

2 Labs

  • Analyzing Data Using Histograms
  • Analyzing Data Using Box Plots and Violin Plots

3 Videos

  • Visualizations
  • Histograms
  • Box Plots and Violin Plots

2 Readings

  • Guidelines for Analyzing Data Using Histograms
  • Guidelines for Analyzing Data Using Box Plots and Violin Plots

Scatter Plots, Line Plots, and Area Plots

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Analyzing Data Using Scatter Plots and Line Plots

1 Videos

  • Scatter Plots, Line Plots, and Area Plots

1 Readings

  • Guidelines for Analyzing Data Using Scatter Plots, Line Plots, and Area Plots

Bar Charts

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Analyzing Data Using Bar Charts

1 Videos

  • Bar Charts

1 Readings

  • Guidelines for Analyzing Data Using Bar Charts

Geographical Maps and Heatmaps

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Analyzing Data Using Maps

1 Videos

  • Geographical Maps and Heatmaps

1 Readings

  • Guidelines for Analyzing Data Using Maps

Combination Plots

    • 2 Videos
    • 1 Readings
    • 1 PeerReview
Show info about module content

1 Peer Review

  • Comparing Visual Analysis Methods

2 Videos

  • Plots in Combination (Bar Chart Grid)
  • Plots in Combination (Pair Plot)

1 Readings

  • Guidelines for Using Visualizations to Analyze Data

Evaluate What You've Learned

    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Using Visualizations to Analyze Data

1 Discussions

  • Reflect on What You've Learned

Overview

    • 1 Readings
Show info about module content

1 Readings

  • Overview

Identify and Handle Missing Values

    • 2 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Handling Missing Values

2 Videos

  • Data Preprocessing
  • Missing Values

1 Readings

  • Guidelines for Handling Missing Values

Scale Features Using Transformation Functions

    • 1 Videos
    • 2 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Applying Transformation Functions to a Dataset

1 Videos

  • Feature Scaling

2 Readings

  • Additional Transformation Functions
  • Guidelines for Applying Transformation Functions to Datasets

Encode Data

    • 2 Videos
    • 2 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Encoding Data

2 Videos

  • Feature Engineering
  • Data Encoding

2 Readings

  • Data Encoding Methods
  • Guidelines for Encoding Data

Discretize Variables

    • 2 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Discretizing Variables

2 Videos

  • Continuous Variable Discretization
  • Bin Determination

1 Readings

  • Guidelines for Discretizing Variables

Split Features

    • 1 Videos
    • 1 Readings
    • 1 Lab
Show info about module content

1 Labs

  • Splitting and Removing Features

1 Videos

  • Feature Splitting

1 Readings

  • Guidelines for Splitting Features

Reduce Dimensionality

    • 1 Videos
    • 3 Readings
    • 1 PeerReview
    • 1 Lab
Show info about module content

1 Peer Review

  • Comparing Data Preprocessing Techniques

1 Labs

  • Performing Dimensionality Reduction

1 Videos

  • Dimensionality Reduction

3 Readings

  • Dimensionality Reduction Methods
  • Guidelines for Performing Dimensionality Reduction
  • Guidelines for Preprocessing Data

Evaluate What You've Learned

    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Preprocessing Data

1 Discussions

  • Reflect on What You've Learned

Project

    • 1 PeerReview
    • 1 Lab
Show info about module content

1 Peer Review

  • Online Retailer: Analyzing Data

1 Labs

  • Course 3 Project

Auto Summary

"Analyze Data" is a professional-level course in Data Science & AI offered by Coursera. Targeted at business professionals with experience in computing and programming, it covers statistical analysis, data visualization, and data preprocessing. The course includes 1260 minutes of content and offers Starter and Professional subscription options. Ideal for those seeking to gain insights and enhance their data analysis skills.

Sarah Haq
Instructors

Sarah Haq

Stacey McBrine
Instructors

Stacey McBrine