IBM Data Analyst Capstone Project

IBM via Coursera

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Overview

In an increasingly data-centric world, the ability to derive meaningful insights from raw data is essential. The IBM Data Analyst Capstone Project gives you the opportunity to apply the skills and techniques learned throughout the IBM Data Analyst Professional Certificate. Working with actual datasets, you will carry out tasks commonly performed by professional data analysts, such as data collection from multiple sources, data wrangling, exploratory analysis, statistical analysis, data visualization, and creating interactive dashboards. Your final deliverable will include a...

Syllabus

Data Collection

In this module, you will apply key concepts in data collection and analysis through APIs and web scraping. You will begin by analyzing HTTP requests and utilizing the GitHub REST API to retrieve and paginate job postings for various technologies. Next, you will collect job data from the GitHub Jobs API. Additionally, you will perform data collection using web scraping techniques, including downloading webpages, scraping links and images, and extracting data from HTML tables to write into a CSV file. The module also includes a graded quiz to test your knowledge.

Data Wrangling

In this module, you will perform essential data-wrangling techniques necessary for cleaning and preparing datasets for analysis. Throughout the module, you will engage in hands-on activities to identify and handle common data issues, including duplicate entries and missing values. You will strategically remove duplicate records, apply suitable imputation strategies for missing data, and normalize datasets to ensure consistency and accuracy. Additionally, you will have a graded quizz to assess your understanding and reinforce the concepts covered.

Exploratory Data Analysis

In this module, you will engage in essential exploratory data analysis (EDA) techniques to uncover meaningful insights from your data set. You will start by identifying the distribution of the data through plotting distribution curves and histograms, which are crucial for understanding how values are spread across different features. Next, you will detect outliers that may skew your analysis and learn how to effectively remove them to ensure data integrity. Additionally, you will explore correlations between various features in the data set, revealing relationships that can inform your overall analysis. Finally, you will create a new DataFrame to organize and present your findings. The module includes a graded quiz to test your knowledge.

Data Visualization

In this lab, you will perform essential data visualization techniques to extract meaningful insights from the Stack Overflow survey data set. You will start by visualizing the distribution of data using histograms and box plots to understand the spread of compensation and age. Next, you will explore relationships between features through scatterplots and bubble plots, followed by examining the composition of data with pie charts and stacked charts. Additionally, you will compare data across categories using line and bar charts. The module includes a graded quizz thatwill assess your knowledge of these concepts, ensuring you are well prepared for further analysis in your final project.

Building A Dashboard

In this module, you will create dashboards using Stack Overflow survey data using either IBM Cognos Analytics or Google Looker Studio. The assignment is divided into Part A: Building a Dashboard with IBM Cognos Analytics and Part B: Building a Dashboard with Google Looker Studio. You will design a dashboard with sections on Current Technology Usage, Future Technology Trends, and Demographics. After completing the assignment, you will be required to submit the link of the Cognos or Looker Studio dashboard you complete. The module also includes a checklist thats you ensure you have completed all necessary tasks before moving on.

Final Assignment: Present Your Findings

In the final module, you will focus on presenting your data findings effectively. You will begin by exploring key elements contributing to a successful data findings report, including structuring your report, using best practices for data visualization, and presenting complex information in an engaging, accessible format. The module also includes labs covering basics in PowerPoint, foundational presentation techniques, and saving your presentation as a PDF to ensure a polished, professional final product. Finally, you will complete and submit a final presentation that highlights insights derived from the Stack Overflow Developer Survey data. Your final assignment will be graded by one or more of your peers, and you will also evaluate the work of a peer who has completed this capstone project.