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IBM Data Analyst Capstone Project
  • Level Professional
  • المدة 21 ساعات hours
  • الطبع بواسطة IBM
  • Offered by

عن

By completing this final capstone project you will apply various Data Analytics skills and techniques that you have learned as part of the previous courses in the IBM Data Analyst Professional Certificate. You will assume the role of an Associate Data Analyst who has recently joined the organization and be presented with a business challenge that requires data analysis to be performed on real-world datasets. You will perform the various tasks that professional data analysts do as part of their jobs, including: - Data collection from multiple sources - Data wrangling and data preparation - Exploratory data analysis - Statistical analysis and data mining - Data visualization with different charts and plots, and - Interactive dashboard creation. The project will culminate with a presentation of your data analysis report for various stakeholders in the organization. The report will include an executive summary, your analysis, and a conclusion. You will be assessed on both your work for the various stages in the Data Analysis process, as well as the final deliverable. As part of this project you will demonstrate your proficiency with using Jupyter Notebooks, SQL, Relational Databases (RDBMS), Business Intelligence (BI) tools like Cognos, and Python Libraries such as Pandas, Numpy, Scikit-learn, Scipy, Matplotlib, Seaborn and others. This project is a great addition to your portfolio and an opportunity to showcase your Data Analytics skills to prospective employers.

الوحدات

Welcome To The Course

    • 1 Videos
    • 2 Readings
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1 Videos

  • Course Introduction

2 Readings

  • Introduction To Capstone Project
  • Syllabus

Collecting Data Using APIs

    • 2 ExternalTool
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Collecting Data

2 External Tool

  • (Optional) Hands-on Lab 1: Review Of Accessing APIs
  • Hands-on Lab 2: Collecting Data Using APIs

Collecting Data Using Webscraping

    • 2 ExternalTool
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Web Scraping

2 External Tool

  • Hands-on Lab 3: Review Of Web Scraping
  • Hands-on Lab 4: Collecting Data Using Web Scraping

Exploring Data

    • 1 ExternalTool
    • 1 Plugin
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Exploring Data

1 External Tool

  • Hands-on Lab 5: Explore the Data Set

Assignment Overview

    • 1 Readings
    • 1 ExternalTool
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1 External Tool

  • Hands-on Lab: Data Wrangling

1 Readings

  • Assignment Overview

Finding Duplicates

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Duplicates

1 Readings

  • Hands-on Lab 6: Finding Duplicates

Removing Duplicates

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Removing Duplicates

1 Readings

  • Hands-on Lab 7: Removing Duplicates

Finding Missing Values

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Missing Values

1 Readings

  • Hands-on Lab 8: Finding Missing Values

Imputing Missing Values

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Imputing Missing Values

1 Readings

  • Hands-on Lab 9: Imput Missing Values

Normalizing Data

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Normalizing Data

1 Readings

  • Hands-on Lab 10: Normalizing Data

Assignment Overview

    • 1 Readings
    • 1 ExternalTool
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1 External Tool

  • Hands-on Lab: Exploratory Data Analysis

1 Readings

  • Assignment Overview

Analyzing the data distribution

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Distribution

1 Readings

  • Hands-on Lab 11: Finding How The Data Is Distributed

Handling Outliers

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Handling Outliers

1 Readings

  • Hands-on Lab 12: Finding Outliers

Correlation

    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Correlation

1 Readings

  • Hands-on Lab 13: Finding Correlation

Assignment Overview

    • 1 Readings
    • 1 ExternalTool
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1 External Tool

  • Hands-on Lab: Data Visualization

1 Readings

  • Assignment Overview

Visualizing Distribution Of Data

    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Visualizing Distribution Of Data

2 Readings

  • Hands-on Lab 14: Histograms
  • Hands-on Lab 15: Box Plots

Visualizing Relationship

    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Visualizing Relationship

2 Readings

  • Hands-on Lab 16: Scatter Plots
  • Hands-on Lab 17: Bubble Plots

Visualizing Composition of Data

    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Visualizing Composition of Data

2 Readings

  • Hands-on Lab 18: Pie Charts
  • Hands-on Lab 19: Stacked Charts

Visualizing Comparison of Data

    • 2 Readings
    • 1 ExternalTool
    • 1 Assignment
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1 Assignment

  • Graded Quiz: Visualizing Comparison of Data

1 External Tool

  • Lab: Pivot Charts

2 Readings

  • Hands-on Lab 20: Line Charts
  • Hands-on Lab 21: Bar Charts

Assignment Overview

    • 1 Readings
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1 Readings

  • Assignment Overview

Dashboards

    • 1 Readings
    • 1 PeerReview
    • 2 Plugin
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1 Peer Review

  • Peer-Graded Assignment: Dashboards

1 Readings

  • Module 5 Assessment Information

How To Present Your Findings

    • 2 Videos
    • 4 Plugin
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2 Videos

  • Elements Of A Successful Data Findings Report
  • Best Practices For Presenting Your Findings

Final Presentation

    • 2 Readings
    • 1 PeerReview
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1 Peer Review

  • Peer-graded Assignment

2 Readings

  • Assignment Overview
  • Exercise: Preparing Your Presentation

Professional Certificate Completion

    • 2 Readings
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2 Readings

  • Congratulations and Next Steps
  • Course Credits and Acknowledgements

Auto Summary

The IBM Data Analyst Capstone Project immerses learners in real-world data analysis, simulating the role of an Associate Data Analyst. Through tasks like data wrangling, statistical analysis, and interactive dashboard creation, participants will utilize Jupyter Notebooks, SQL, and Python libraries. Culminating in a comprehensive report presentation, this professional-level course by Coursera spans 1260 minutes and offers Starter and Professional subscription options. Ideal for those looking to enhance their data science portfolio and showcase their skills to potential employers.

Rav Ahuja
Instructors

Rav Ahuja

Ramesh Sannareddy
Instructors

Ramesh Sannareddy