Data Science & EDA Global Conflict Project from Scratch

What you'll learn
Course Introduction
Loading the Dataset
Understanding the Variables in the Dataset
Exploring the Characteristics of Our Conflict Dataset
Missing and Unique Value Analysis
Renaming Variables
Ensuring Data Consistency
Distribution Analysis of Conflict
Exploring Annual Trends
Analyzing Conflict Data by Region
Visualizing Conflict Data Correlations
Bar Charts for Regional Death Counts
Identifying Top Events with Highest Fatalities
Stacked Bar Charts for Conflict-related Deaths Over the Years
Exploring Trends with Bubble Charts
Filtering Regional Death Trends: A Temporal Analysis
Mastering Elbow Method and Silhouette Scores
Regional Conflict Clustering
Advanced Data Visualization with Plotly - Animating Conflict Trends Over Time
Heatmap Visualization of Regional Conflict Metrics
In-Depth Statistical Analysis of Numerical Data in Conflict Studies
Testing for Normality in Conflict Data Using the Shapiro-Wilk Test
Advanced Outlier Detection Using Z-Scores in Conflict Data
Requirements
A working computer (Windows, Mac, or Linux)
Basic understanding of Python (just the essentials-loops, functions, and variables)
Interest in data science and real-world applications
Curiosity about global issues like conflict, peace, and humanitarian analysis
Motivation to transform raw data into meaningful insights
No prior experience with EDA or conflict datasets required
Just you, your keyboard, and your passion for making data-driven impact!
Description
Welcome to "Data Science & EDA: Global Conflict Project from Scratch"Master Data Science Skills, Analyze Global Conflicts, cluster & visualize real-world crisis data with Python & ChatGPTThis course empowers you to analyze real-world conflict data, uncover hidden patterns, and create impactful visual stories that influence peacebuilding and policy decisions. Whether you're a beginner or an experienced analyst, you'll gain practical skills with hands-on projects using industry-standard tools.In this course, you will dive deep into Exploratory Data Analysis (EDA) focused on complex global conflict datasets. You'll learn how to clean, explore, visualize, and interpret data using Python, Pandas, ChatGPT and key statistical methods to uncover trends and insights crucial for understanding humanitarian crises.By the end of the course, you will confidently perform EDA on messy real-world data, create interactive visualizations, apply clustering techniques, and build portfolio-ready projects that combine data science with social impact.What You Will Learn:This course takes you step-by-step through a hands-on EDA process using conflict datasets, covering:Course introduction and dataset loadingUnderstanding variables and data characteristicsHandling missing values, renaming, and ensuring consistencyDistribution and trend analysis over time and regionsVisualizing data correlations and regional death counts with bar and bubble chartsIdentifying major conflict events and temporal death trendsApplying clustering using Elbow Method and Silhouette ScoresAdvanced interactive visualizations with Plotly, including animated trends and heatmapsIn-depth statistical analysis: normality testing and outlier detectionBy the End of This Course, You Will Be Able To:Confidently apply Exploratory Data Analysis (EDA) techniques to complex, real-world conflict datasetsCreate dynamic and interactive data visualizations using Plotly to reveal meaningful insightsUtilize clustering algorithms and statistical methods to identify underlying patterns in dataDevelop comprehensive data science projects that combine technical expertise with social impactCritically analyze data to understand and communicate the stories it tells about global conflictsWhat is python?Machine learning python is a general-purpose, object-oriented, high-level programming language. Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python bootcamp is one of the most important skills you can learn. Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed on the premise that there should be only one way (and preferably, one obvious way) to do things, a philosophy that resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing different tools for programmers suited for a variety of tasks.What is ChatGPT?ChatGPT is an artificial intelligence (AI) chatbot that uses natural language processing to create humanlike conversational dialogue. The language model can respond to questions and compose various written content, including articles, social media posts, essays, code and emails.ChatGPT is a form of generative AI -- a tool that lets users enter prompts to receive humanlike images, text or videos that are created by AI.What is EDA?Exploratory data analysis (EDA) is used by data scientists to analyze and investigate data sets and summarize their main characteristics, often employing data visualization methods.EDA helps determine how best to manipulate data sources to get the answers you need, making it easier for data scientists to discover patterns, spot anomalies, test a hypothesis, or check assumptions.EDA is primarily used to see what data can reveal beyond the formal modeling or hypothesis testing task and provides a provides a better understanding of data set variables and the relationships between them. It can also help determine if the statistical techniques you are considering for data analysis are appropriate. Originally developed by American mathematician John Tukey in the 1970s, EDA techniques continue to be a widely used method in the data discovery process today.Fresh contentIt's no secret how technology is advancing at a rapid rate New tools are released every day, and it's crucial to stay on top of the latest knowledge for being a better security specialistVideo and Audio Production QualityAll our videos are created/produced as high-quality video and audio to provide you the best learning experience.You will be,Seeing clearlyHearing clearlyMoving through the course without distractionsYou'll also get:Lifetime Access to The CourseFast & Friendly Support in the Q&A sectionUdemy Certificate of Completion Ready for DownloadWe offer full support, answering any questionsSee you in the ""Data Science & EDA: Global Conflict Project from Scratch" course.Master Data Science Skills, Analyze Global Conflicts, cluster & visualize real-world crisis data with Python & ChatGPT
Who this course is for
Anyone who wants to start learning data science through meaningful, real-world applications
Students, researchers, or professionals interested in conflict analysis, international relations, or peace studies
Those seeking a hands-on guide to mastering Exploratory Data Analysis (EDA) with real datasets
Anyone curious about how data can uncover patterns in global crises and shape data-driven decision making
Learners who want to enhance their Python skills by working on impactful analytical projects
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