Dive into a comprehensive 5.5-hour Python data science course covering essential theory, demos, and real-world applications. Gain hands-on experience through two detailed projects in data analytics, AB testing, and business intelligence. Master data exploration, preprocessing, filtering, sorting, grouping, descriptive statistics, merging, and data visualization in Python. Learn AB testing theory and apply it in a practical project. Explore a Superstore data analytics project, covering customer segmentation, sales insights, loyalty analysis, shipping strategies, geographic market analysis, and product performance. Developed by Tatev and Vahe from LunarTech, this course prepares you for real-world data science challenges through practical experience and in-depth analysis.
Python for Data Science - Hands-on Projects with EDA, AB Testing and Business Intelligence
via freeCodeCamp
Overview
Syllabus
Introduction
Part 1: Python for Data Science and Analytics
Part 1: Data Exploration and Preprocessing
Part 1: Filtering, Sorting, Grouping
Part 1: Descriptive Statistics
Part 1: Merging & Joins
Part 1: Data Visualization in Python
Part 2: AB Test Crash Course - Theory
Part 3 Project 1 - Data Analytics and Data Science Project
Experimental vs. Control Set up
Data Analytics in A/B Testing
Parameters for A/B Testing
Analyzing A/B Test Data
Statistical Outputs Explained
Concluding A/B Test Results and Case Study
Part 3 Project 2 - Superstore Data Analytics Project
Superstore Customer Segmentation
Revenue by Customer Segment
Customers Sales Insights
Exploring Customer Loyalty at Superstores
Superstore Shipping Strategies
Geographic Market Analysis
Product Performance Insights
Comprehensive Sales Analysis
Tracking Sales Trends
Visualizing Sales by State
Taught by
freeCodeCamp.org
