Dive into the world of data and unlock its potential! Learn how to clean and explore your data effectively, gaining valuable insights for informed decision-making.
Feb 1, 1:00 – 2:30 PM
Career DevelopmentExplore MLMachine Learning
About this event
Join us for an interactive session where we'll delve into the world of data cleaning and practical Exploratory Data Analysis (EDA). Whether you're a seasoned data scientist or just starting your journey, this session is packed with valuable insights and hands-on learning.
Part 1: Data Cleaning Bootcamp
Identify data quality issues: We'll begin by revisiting the key findings from your initial EDA, uncovering hidden gremlins like missing values, outliers, inconsistencies, and more. Learn how to prioritize these issues based on their potential impact on your analysis.
Conquer common challenges: Our experts will guide you through various data cleaning techniques, equipping you with the tools to tackle missing values (imputation, deletion), handle outliers (capping, winsorizing, removal), and address inconsistencies.
Get hands-on: Dive into practical demonstrations using your specific data and preferred tools (e.g., Python libraries, spreadsheets). See how these techniques are applied in real-time, and get ready to ask questions!
Validate your success: We'll show you how to use visualizations and summary statistics to assess whether your data cleaning efforts have paid off. Learn how to identify any remaining issues and ensure your data is ready for in-depth analysis.
Part 2: Practical EDA Workshop
Refine your data: Briefly discuss the outcome of your data cleaning session and address any lingering concerns.
Deep dive into key variables: Select a few crucial variables based on your research question and prepare to embark on a deeper exploration.
Visualize for understanding: Our instructors will guide you through creating insightful charts and graphs (histograms, box plots, scatter plots, heatmaps) to uncover relationships, distributions, and trends within your data.
Quantify your findings: Calculate relevant summary statistics like mean, median, standard deviation, and percentiles to gain a quantitative understanding of your data's characteristics.
Test hypotheses and draw conclusions: Based on your visualizations and statistics, learn how to formulate and test hypotheses related to your research question.
Interpret and share insights: Summarize the key takeaways from your EDA, highlighting the valuable insights you've unearthed and potential next steps in your analysis journey.
Don't miss this opportunity to:
Gain hands-on experience with essential data cleaning techniques.
Learn how to create informative visualizations for EDA.
Deepen your understanding of your data and extract valuable insights.
Ask questions and get expert guidance from experienced data professionals.
Register today and join us on this exciting journey towards data mastery!