Python for Data Analytics

Date: 27th and 28th April 2021

Time: 09:00 – 12:00

Location: Online | Virtual instructor-led

CPE Hours: 6 hours total – CORE

Price: EUR 270

Registration Link: www.pwc.com/Mt/academy or  mt.academy@pwc.com

Course Description

Python is the fastest growing programming language used for all types of applications, especially in the data analytics area. Users make extensive use of Excel and Power BI Data Analytics and Visualizations features for their day-to-day analytics. However, using Python with Power BI one can very easily perform advanced Analytics.

Throughout this course a user will learn Python from scratch and move on to apply python scripts to import, transform and visualize data in Power BI.

Prerequisites
A good knowledge of Advanced Excel and Power BI

Objectives
The aim of this course is to give delegates a thorough grounding in the main concepts of the Python programming language, and how to deploy python scripts for Data Analysis, Business Modelling and Visualisations in Power BI. It uses multiple practical tasks to ensure that users can practice the key techniques that are taught and also ask any questions that they may have.

Our aim is that you leave the course as a confident user of Python programming language and for data Analytics.

Certifications
Attending delegates will be presented with a Certificate of Attendance upon completion of training.

Training Methodology
We believe that learning is most effective when presented in a relevant context so that the skills, strategy, and knowledge are meaningful to our delegates and can be applied directly in the training. Training sessions are conducted as hands-on workshops.

Course Outline

Python Basics

• • Install Python
  • Starting with Programming and Python Basics
  • Data Types, variables and Operators
  • Lists and Strings

Python Advanced

• • Functions
  • Conditional Statements
  • Loops
  • Object-Oriented Programming (OOP) Concepts
  • Creating Classes
  • Packages in Python

Running Python Scripts in Power BI for Data Analytics

• • Install required Python Packages – Pandas, Numpy and scikit-learn
  • Creating Python scripts to apply Machine Learning Analytics on the data
  • Setting-Up Python Scripting in Power BI
  • Creating Advanced Analysis & Visualisations using Python

Practical Application
Analysing Customer Purchasing Behaviours, for a retail business, with Machine Learning, Python and Power BI

Learning Outcomes

• How to analyse a retail business e-commerce sales data and visualize the customer behaviour and characteristics from diverse aspects by using Customer Segmentation Techniques.
• How to approach the problem from a behavioural aspect to better understand customers’ spending and ordering habits using the following features:

1. 1. Number of products ordered
   2. Average return rate
   3. Total spending

• How to generalize customers into segments/groups to find similar characteristics in each customer’s behaviour and needs using Python.
• How to analyse and visualise data in Power BI, within the various groups as follows:
• Customers who ordered at least one product, with a maximum total spending threshold and having the highest average return rate. They might be the newcomers of the e-commerce website.
• Customers who ordered a range of products, with an average total spending of €x and a maximum return rate of 0.5.
• Customers who ordered a range of products, with average total spending of €z and average return rate as 0. It makes the most favourable customer group for the company.