Python for Business Analysis and Excel

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 119 lectures (20h 50m) | Size: 5.77 GB
Supercharge your business analysis skills by using Python to analyze Excel data!

What you’ll learn:
Python fundamentals
Import data from Excel and CSV files into Python
Clean and structure data in Python
Analyze data in Python
Export finalized data analysis back to Excel
Debug code
Build compelling business analysis models using real world examples
Develop customer segmentation analysis
Conduct in-depth process and bottleneck analysis
Analyze seasonality and demand fluctuations
Structure a marketing promotion and analyze the return on investment

Requirements
Basic understanding of Python
Basic understanding of Excel
A computer (PC or Mac)

Description
In this course we’ll use Python to:

Read data from Excel and CSV files into Python

Clean and analyze the data in Python going way beyond the functionality that Excel is capable of

Create reusable Python code which can make analyzing data in Python quick and easy

Write data back to Excel for final touches and creating charts

This course uses real world business cases to demonstrate practical applications of Python. By the end of the course you will have a portfolio of business analysis examples that will prove your mastery over Python. This includes:

Customer segmentation analysis – we’ll look at a large set of customer data and tease out different customer segments which are more profitable. This will allow the marketing department to determine which groups to target. We’ll focus on parents with babies and analyze how much money they spend and what their demographic characteristics look like.

Production bottleneck analysis – we’ll look at the production line of a car factory to understand which machines are causing delays in completing the final cars. Using this analysis, we’ll make recommendations on which new machines to invest in. Additionally, we’ll look at how often machines break down and how this contributes to delays.

Seasonality – we’ll analyze daily, monthly, and quarterly trends in a clothing manufacturers sales to understand which times of year produce the best results. We’ll also look at how profit margins change over time.

Marketing promotion – we’ll create a return on investment (ROI) analysis for a proposed marketing campaign and then analyze the actual results to determine whether our ROI analysis was accurate.

Along the way you will reinforce key Python concepts and learn how to debug and refactor your code. This course provides more guidance on debugging than any other. Debugging is a crucial skill which will help you solve problems more effectively and be more independent when writing your own code.

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