Python in Excel 2023 Masterclass for Data Science

Course Curriculum

Chapter 1: Getting started

Lecture 1: Welcome

Lecture 2: How to get the most out of this course

Lecture 3: Sneak Preview: Merging and joining Data with Pandas in Excel

Lecture 4: Python in Excel: How it works & what you need

Lecture 5: Python in Excel: Features & alternative Tools (xlwings)

Lecture 6: How to set up Python in Excel (BETA)

Lecture 7: Troubleshooting

Chapter 2: Python in Excel – First Steps and Must Knows

Lecture 1: Introduction

Lecture 2: Simple Operations using the PY Function

Lecture 3: Python Variables vs. Excel Cell References

Lecture 4: Python Objects and Data Types

Lecture 5: NoneType Objects

Lecture 6: Output Types: Python Output vs. Excel Value

Lecture 7: Extracting Data from Python Objects to Excel

Lecture 8: Diagnostics

Lecture 9: Calculation Order and Recalculation

Lecture 10: Initialization Settings and Customizations

Lecture 11: User-defined Functions and Classes

Lecture 12: Python Plots (Matplotlib & Seaborn)

Chapter 3: Project 1: Explanatory Data Analysis (EDA) with Python and Excel

Lecture 1: Project Introduction and Downloads

Lecture 2: Instructions and Hints

Lecture 3: Excursus: Project Solution in a Jupyter Notebook

Lecture 4: Task 1: How to load and import the Dataset

Lecture 5: Task 2: Initial Data Inspection

Lecture 6: Task 3: Univariate Data Analysis 1

Lecture 7: Task 4: Univariate Data Analysis 2

Lecture 8: Task 5: Multivariate Data Analysis 1

Lecture 9: Task 6: Multivariate Data Analysis 2

Lecture 10: Task 7: Multivariate Data Analysis 3

Chapter 4: Project 2: Time Series and Financial Data Analysis with Python in Excel

Lecture 1: Project Introduction and Downloads

Lecture 2: Instructions and Hints

Lecture 3: Excursus: Project Solution in a Jupyter Notebook

Lecture 4: Task 1: How to load the Dataset and Initial Data Inspection

Lecture 5: Task 2: How to create dynamic Price Charts

Lecture 6: Task 3: Dynamic Resampling and Financial Returns

Lecture 7: Task 4: Statistics and Performance Analysis

Lecture 8: Task 5: Covariance and Correlation Matrix and Heatmaps

Chapter 5: Project 3: Merging and aggregating Data with Pandas in Excel

Lecture 1: Project Introduction and Downloads

Lecture 2: Instructions and Hints

Lecture 3: Excursus: Project Solution in a Jupyter Notebook

Lecture 4: Task 1: Creating and Aggregating DataFrames

Lecture 5: Task 2: Creating a tool to join/merge Datasets with full flexibility

Chapter 6: Project 4: Multiple Regression Analysis, Hypothesis Testing and Preprocessing

Lecture 1: Project Introduction, Downloads and Hints

Lecture 2: Coding Solution (Part 1)

Lecture 3: Coding Solution (Part 2)

Lecture 4: Coding Solution (Part 3)

Lecture 5: Implementation & Feature Elimination in Excel (Part 1)

Lecture 6: Implementation & Feature Elimination in Excel (Part 2)

Chapter 7: Bonus Project: Using Python in Excel and xlwings together – the ultimate Boost

Lecture 1: Introduction and Downloads

Lecture 2: Set up and Installation of xlwings

Lecture 3: How to use xlwings as a Data Viewer

Lecture 4: Data Viewer – Update

Lecture 5: How to connect to an Excel Workbook

Lecture 6: How to read and write single Values

Lecture 7: Introduction to Running Python Scripts in Excel & Downloads

Lecture 8: Installing the xlwings add-in and other preparations

Lecture 9: Running Python Scripts with "Run main"

Lecture 10: Troubleshooting

Lecture 11: Bonus Project: Introduction & Downloads

Lecture 12: Instruction and Hints

Lecture 13: Solution

Chapter 8: Appendix: Installing and working with Anaconda and Jupyter Notebooks

Lecture 1: Download and Install Anaconda

Lecture 2: How to open Jupyter Notebooks

Lecture 3: How to work with Jupyter Notebooks

Chapter 9: What´s next? (outlook and additional resources)

Lecture 1: Bonus Lecture