Python for Business Analysis and Excel

本课程使用实际业务案例来演示Python的实际应用。在课程结束时，您将获得一系列业务分析示例，这些示例将证明您对Python的精通。这包括：

客户细分分析-我们将查看大量的客户数据，并挑出更有利可图的不同客户细分。这将使营销部门可以确定要定位的组。我们将重点关注有婴儿的父母，并分析他们花了多少钱以及他们的人口统计学特征。

生产瓶颈分析-我们将研究汽车制造厂的生产线，以了解哪些机器导致最终汽车制造的延误。使用此分析，我们将建议投资哪些新机器。此外，我们还将查看机器发生故障的频率以及这如何导致延迟。

季节性-我们将分析服装制造商销售中的每日，每月和每季趋势，以了解一年中的哪个时期产生最佳效果。我们还将研究利润率如何随时间变化。

营销推广-我们将为拟议的营销活动创建投资回报（ROI）分析，然后分析实际结果以确定我们的ROI分析是否准确。

在此过程中，您将加强关键的Python概念并学习如何调试和重构代码。本课程比其他任何课程都提供了更多的调试指导。调试是一项至关重要的技能，它将帮助您更有效地解决问题，并在编写自己的代码时更加独立。

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.

Who this course is for
Business professionals that want to supercharge their data analysis skills with Python
Anyone that has been introduced to Python and wants real world, practical examples