About Course
Introduction to Data Analysis is a foundational course aimed at teaching students essential skills for understanding and interpreting data and also how to monetize these skills on various crowdsourcing platforms. The course covers:
- Data Collection and Cleaning: Techniques for gathering and preparing data, including handling missing values and inconsistencies.
- Descriptive Statistics: Methods for summarizing and visualizing data, such as using mean, median, and standard deviation, along with visual tools like histograms and scatter plots.
- Inferential Statistics: Basics of hypothesis testing, confidence intervals, and regression analysis to draw conclusions about populations from sample data.
- Data Visualization: Skills for analyzing results and recognizing data limitations and biases.
- Practical Applications: Application of data analysis techniques to real-world problems through case studies and exercises.
- Skill monetization: Step-by-step guide on the opening of relevant online work platforms for data analysis skills monetization.
By the end of the course, students will be equipped to effectively analyze data and make informed decisions based on their findings.
Course Content
Module 1: Getting started in data collection and organization
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Introduction
00:00 -
Tools used in data collection
00:00 -
Data entry in Spreadsheets
00:00 -
Basic Excel features for data organization
00:00 -
Practice Quiz
Module 2: Data cleansing and preparation techniques
Module 3: Data Analysis using statistics
Module 4: Relational and Non-Relational Databases
Module 5: Introduction to Structured Queried Language
Module 6: Data Visualization tools
Module 7: Real life applications of Data Analysis
Module 8: Online Work Platforms for Data Analysts
Module 9: Final Exam
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