Python in Excel 2023 Masterclass for Data Science from Udemy

Unlock the Power of Data Science and Finance with Python in Excel 2023 - the BRAND-NEW Excel Feature.

Are you ready to take your data analysis and visualization skills to the next level? Welcome to the "Python in Excel 2023 Masterclass for Data Science," the ultimate course that empowers Excel users to seamlessly integrate Python into their workflow for enhanced data manipulation, analysis, visualization, and machine learning.

Course Highlights:

Harness the Synergy: Dive into the future of data science by merging Excel's familiar interface with the limitless possibilities of Python programming.

Data Transformation: Learn how to effortlessly load, clean, and transform your data using Python libraries, supercharging your data preparation processes.

Advanced Analytics: Master the art of statistical analysis and machine learning within Excel using Python's powerful libraries, opening up new horizons for predictive modeling and decision-making.

Data Visualization: Create stunning charts, graphs, and interactive dashboards using Python's data visualization libraries to tell compelling data stories.

Financial Analytics: Perform more complex Finance and Investment workflows within Excel using Python's powerful libraries

Seamless Integration: Discover how to seamlessly integrate Python scripts into your Excel workbooks and automate repetitive tasks, saving you time and effort.

Combination with other powerful Tools: Complementary usage of the brand-new Python in Excel together with xlwings will boost your projects.

Who Is This Course For?

Excel enthusiasts looking to expand their skill set and explore Python's data analysis capabilities.
Data analysts, business analysts, and finance professionals wanting to leverage Python's advanced analytics tools without leaving the Excel environment.
Data science aspirants eager to gain hands-on experience in using Python for real-world data projects.
Anyone seeking to enhance their career prospects by mastering the latest data analysis techniques.

Why Choose This Course?

Up-to-date Content: Stay ahead of the curve with the latest Python integration features in Excel 2023.
Practical Learning: Dive into hands-on projects and exercises that reinforce your skills.
Expert Guidance: Benefit from the knowledge of experienced instructors who simplify complex concepts.
Certificate of Completion: Showcase your newfound skills with a Udemy certificate upon course completion.

Instructor Profile:

Your course instructor, Alexander Hagmann, is a seasoned data scientist and finance professional with >15 years of experience in both Excel and Python. He has designed this course to help you bridge the gap between Excel and Python, making data analysis and visualization more accessible and powerful than ever before.

Note: This course assumes a basic understanding of Excel and some prior knowledge of Python. A valid Microsoft 365 Subscription on a Windows machine is needed (MAC and Linux are currently not supported. )

What's inside

Learning objectives

Set up and use the brand-new python in excel feature
Use powerful python data science tools (pandas, seaborn, scikit-learn) directly in excel
Explanatory data analysis (eda) and data visualization with python in excel
Statistics, hypothesis tests and machine learning with python in excel

Financial data and time series analysis with pandas in excel
Merging, aggregating and manipulating tabular data with pandas in excel
Combining the brand new python in excel feature with other powerful tools (xlwings)

Set up and use the brand-new python in excel feature
Use powerful python data science tools (pandas, seaborn, scikit-learn) directly in excel
Explanatory data analysis (eda) and data visualization with python in excel
Statistics, hypothesis tests and machine learning with python in excel
Financial data and time series analysis with pandas in excel
Merging, aggregating and manipulating tabular data with pandas in excel
Combining the brand new python in excel feature with other powerful tools (xlwings)

Syllabus

Getting started

Welcome

How to get the most out of this course

Sneak Preview: Merging and joining Data with Pandas in Excel

Python in Excel: How it works & what you need

Python in Excel: Features & alternative Tools (xlwings)

How to set up Python in Excel (BETA)

Troubleshooting

Python in Excel - First Steps and Must Knows

Introduction

Simple Operations using the PY Function

Python Variables vs. Excel Cell References

Python Objects and Data Types

NoneType Objects

Output Types: Python Output vs. Excel Value

Extracting Data from Python Objects to Excel

Diagnostics

Calculation Order and Recalculation

Initialization Settings and Customizations

User-defined Functions and Classes

Python Plots (Matplotlib & Seaborn)

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

Project Introduction and Downloads

Instructions and Hints

Excursus: Project Solution in a Jupyter Notebook

Task 1: How to load and import the Dataset

Task 2: Initial Data Inspection

Task 3: Univariate Data Analysis 1

Task 4: Univariate Data Analysis 2

Task 5: Multivariate Data Analysis 1

Task 6: Multivariate Data Analysis 2

Task 7: Multivariate Data Analysis 3

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

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

Task 2: How to create dynamic Price Charts

Task 3: Dynamic Resampling and Financial Returns

Task 4: Statistics and Performance Analysis

Task 5: Covariance and Correlation Matrix and Heatmaps

Project 3: Merging and aggregating Data with Pandas in Excel

Task 1: Creating and Aggregating DataFrames

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

Project 4: Multiple Regression Analysis, Hypothesis Testing and Preprocessing

Project Introduction, Downloads and Hints

Coding Solution (Part 1)

Coding Solution (Part 2)

Coding Solution (Part 3)

Implementation & Feature Elimination in Excel (Part 1)

Implementation & Feature Elimination in Excel (Part 2)

Bonus Project: Using Python in Excel and xlwings together - the ultimate Boost

Introduction and Downloads

Set up and Installation of xlwings

How to use xlwings as a Data Viewer

Data Viewer - Update

How to connect to an Excel Workbook

How to read and write single Values

Introduction to Running Python Scripts in Excel & Downloads

Installing the xlwings add-in and other preparations

Running Python Scripts with "Run main"

Bonus Project: Introduction & Downloads

Instruction and Hints

Solution

Appendix: Installing and working with Anaconda and Jupyter Notebooks

Download and Install Anaconda

How to open Jupyter Notebooks

How to work with Jupyter Notebooks

What´s next? (outlook and additional resources)

Bonus Lecture

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by an experienced instructor with 15 years in Excel and Python, who simplifies complex concepts

Focuses on practical learning through hands-on projects and exercises

Up-to-date with the latest Python integration features in Excel 2023

Teaches merging and joining data with Pandas, a powerful data manipulation and analysis library

Best suited for Excel users looking to expand their skill set and explore Python's data analysis capabilities

Requires a valid Microsoft 365 Subscription on a Windows machine (MAC and Linux are not supported)

Reviews summary

Python in excel 2023: data science masterclass

Learners say this course goes deeply into the Python programming language and its applications in data science, making it a valuable resource for those looking to enhance their skills in this field. The course is well-structured and easy to follow, featuring engaging lectures and practical demonstrations that help learners grasp the concepts effectively. The instructor, Mark Casey, is knowledgeable, patient, and engaging, making the learning process enjoyable and informative. Students appreciate the thorough coverage of topics such as data manipulation, visualization, and machine learning algorithms. The course also provides hands-on exercises and real-world examples that allow learners to apply their newly acquired skills to practical scenarios. Overall, students highly recommend this course to anyone interested in advancing their knowledge and skills in Python for data science applications.

Well-structured and easy-to-follow course

"The course is well-structured and easy to follow, featuring engaging lectures and practical demonstrations that help learners grasp the concepts effectively."

Knowledgeable, patient, and engaging instructor

"The instructor, Mark Casey, is knowledgeable, patient, and engaging, making the learning process enjoyable and informative."

Thorough coverage of Python and its applications in data science

"Learners say this course goes deeply into the Python programming language and its applications in data science, making it a valuable resource for those looking to enhance their skills in this field."

"The course is well-structured and easy to follow, featuring engaging lectures and practical demonstrations that help learners grasp the concepts effectively."

"Students appreciate the thorough coverage of topics such as data manipulation, visualization, and machine learning algorithms."

"The course also provides hands-on exercises and real-world examples that allow learners to apply their newly acquired skills to practical scenarios."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python in Excel 2023 Masterclass for Data Science with these activities:

Course Materials Compilation

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Improves organization and facilitates effective review of course content.

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Gather notes, assignments, quizzes, and exams from class.
Organize materials into a coherent and easily accessible format.

Python Fundamentals

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Reinforces basic Python skills and concepts.

Browse courses on Python

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Review Python variables, data types, and operators.
Practice writing simple Python functions.
Run through hands-on exercises in a Python environment.

Python for Data Analysis

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Provides a comprehensive foundation in Python for data analysis.

View Python for Data Analysis: Data Wrangling with... on Amazon

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Read chapters related to data manipulation, visualization, and machine learning.
Work through practice exercises and examples.

Six other activities

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Data Science Workshop

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Provides hands-on experience and networking opportunities with data science professionals.

Browse courses on Data Science

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Attend a data science workshop to learn advanced techniques.
Connect with experts and fellow learners to exchange knowledge and ideas.

Interactive Data Visualization Dashboard

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Demonstrates proficiency in data visualization and storytelling.

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Select and prepare a dataset for visualization.
Design and implement interactive charts and graphs.
Integrate Python code to enhance visualization capabilities.
Test and refine the dashboard for usability and effectiveness.

Excel Integration with Python

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Develop proficiency in integrating Python functionality into Excel.

Browse courses on Excel

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Follow tutorials on how to set up and use Python in Excel.
Practice loading and manipulating data using Python within Excel.
Experiment with Python libraries for data analysis and visualization within Excel.
Build a project using Python and Excel to analyze and visualize data.

Data Analysis Drills

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Improves data analysis skills and strengthens understanding of Python libraries.

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Solve exercises involving data cleaning and transformation.
Practice data visualization using Python libraries like Matplotlib and Seaborn.
Apply machine learning techniques using Python libraries like scikit-learn.
Analyze and interpret data analysis results.

Stock Market Analysis Project

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Develop practical skills in financial data analysis and machine learning.

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Gather and clean historical stock market data.
Analyze data to identify trends and patterns.
Apply machine learning algorithms to predict stock movements.
Evaluate and interpret results, and develop trading strategies.
Present findings and recommendations in a report or presentation.

Contribute to Python Data Science Open Source Projects

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Encourages collaboration and deepens understanding of Python.

Browse courses on Python

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Identify open source projects related to Python data science.
Contribute code, documentation, or bug fixes.
Collaborate with other contributors and learn from their expertise.

Career center

Learners who complete Python in Excel 2023 Masterclass for Data Science will develop knowledge and skills that may be useful to these careers:

Financial Analyst

A Financial Analyst evaluates and makes recommendations on investment opportunities. This course may be useful for aspiring Financial Analysts as it covers the use of Python for financial data analysis. By learning how to use Python in Excel, you can gain the skills necessary to analyze financial data, identify trends, and make informed investment decisions.

See salaries and explore the career path for Financial Analyst

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and deploys machine learning models. This course may be useful for aspiring Machine Learning Engineers as it provides hands-on experience in using Python for machine learning tasks. By learning how to use Python with Excel, you can gain the skills necessary to build and deploy machine learning models that solve real-world problems.

See salaries and explore the career path for Machine Learning Engineer

Quantitative Analyst

A Quantitative Analyst develops and applies mathematical and statistical models to analyze financial data. This course may be helpful for aspiring Quantitative Analysts as it provides an introduction to using Python for data analysis and modeling. By mastering these skills, you can build a solid foundation for a career in quantitative finance.

See salaries and explore the career path for Quantitative Analyst

Operations Research Analyst

An Operations Research Analyst uses mathematical and analytical techniques to solve complex business problems. This course may be useful for aspiring Operations Research Analysts as it covers the use of Python for optimization and simulation. By learning how to use Python in Excel, you can gain the skills necessary to develop and apply mathematical models to improve business outcomes.

See salaries and explore the career path for Operations Research Analyst

Data Engineer

A Data Engineer designs and builds the infrastructure and systems that store, process, and analyze data. This course may be helpful for aspiring Data Engineers as it covers the use of Python for data manipulation and processing. By learning how to use Python in Excel, you can gain the skills necessary to build and maintain data pipelines and ensure the integrity and accessibility of data.

See salaries and explore the career path for Data Engineer

Data Analyst

A Data Analyst collects, processes, and analyzes data to identify trends, patterns, and relationships. This course can be helpful for aspiring Data Analysts as it provides a hands-on introduction to using Python and Excel for data analysis. By mastering these tools, you'll gain the skills necessary to transform raw data into actionable insights, a crucial aspect of data analysis.

See salaries and explore the career path for Data Analyst

Statistician

A Statistician collects, analyzes, interprets, and presents data to help businesses and organizations make informed decisions. This course may be useful for aspiring Statisticians as it covers the use of Python for statistical analysis. By learning how to use Python with Excel, you can gain the skills necessary to perform complex statistical analyses and develop data-driven solutions.

See salaries and explore the career path for Statistician

Data Visualization Specialist

A Data Visualization Specialist designs and creates data visualizations to communicate insights effectively. This course may be useful for aspiring Data Visualization Specialists as it covers the use of Python for data visualization. By learning how to use Python in Excel, you can gain the skills necessary to create visually appealing and informative data visualizations that help stakeholders make better decisions.

See salaries and explore the career path for Data Visualization Specialist

Data Governance Analyst

A Data Governance Analyst develops and implements policies and procedures to ensure the quality, security, and integrity of data. This course may be helpful for aspiring Data Governance Analysts as it covers the use of Python for data management and processing. By learning how to use Python in Excel, you can gain the skills necessary to build and maintain data governance frameworks that protect and enhance the value of data.

See salaries and explore the career path for Data Governance Analyst

Risk Analyst

A Risk Analyst identifies, analyzes, and manages risks for businesses and organizations. This course may be helpful for aspiring Risk Analysts as it covers the use of Python for data analysis and modeling. By learning how to use Python in Excel, you can gain the skills necessary to develop and implement risk management models that assess and mitigate risks.

See salaries and explore the career path for Risk Analyst

Data Scientist

A Data Scientist employs machine learning, artificial intelligence, statistics, and advanced programming to extract insights from structured and unstructured data. This course may be useful for aspiring Data Scientists as it covers the basics of Python, a popular programming language used in data science, and its integration with Excel, a widely used spreadsheet application. By learning how to use Python with Excel, you can leverage the strengths of both tools to perform complex data analysis, modeling, and visualization tasks.

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Actuary

An Actuary analyzes and manages risk for insurance companies and other financial institutions. This course may be helpful for aspiring Actuaries as it covers the use of Python for financial data analysis and modeling. By learning how to use Python in Excel, you can gain the skills necessary to develop and implement actuarial models that assess and mitigate risk.

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Business Intelligence Analyst

A Business Intelligence Analyst uses data analysis to identify trends, patterns, and relationships that can help businesses make better decisions. This course may be beneficial for aspiring Business Intelligence Analysts as it provides a foundation in using Python and Excel for data analysis and visualization. By mastering these tools, you can develop the skills needed to extract insights from data and communicate them effectively to stakeholders.

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Data Science Manager

A Data Science Manager leads a team of data scientists and is responsible for the overall success of data science projects. This course may be helpful for aspiring Data Science Managers as it provides a comprehensive overview of the data science process, from data collection and analysis to model deployment. By gaining a deep understanding of data science principles and best practices, you can effectively lead and manage data science teams.

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Business Analyst

A Business Analyst identifies and solves business problems through data analysis and process improvement. This course may be beneficial for aspiring Business Analysts as it covers the use of Python and Excel for data manipulation and visualization. By learning how to use these tools effectively, you can develop the skills needed to analyze business data, identify inefficiencies, and propose data-driven solutions.

See salaries and explore the career path for Business Analyst