Manage Finance Data with Python & Pandas: Unique Masterclass

- Descrição
- Currículo
- FAQ
- Revisões
**Fully Updated (anticipating Pandas 3.x) in November 2024**
**Now with ChatGPT for Pandas & Data Analytics and Online Coding Exercises!**
The Finance and Investment Industry is experiencing a dramatic change driven by ever-increasing processing power & connectivity and the introduction of powerful Machine Learning tools. The Finance and Investment Industry is more and more shifting from a math/formula-based business to a data-driven business.
What can you do to keep pace?
No matter if you want to dive deep into Machine Learning, or if you simply want to increase productivity at work when handling Financial Data, there is the very first and most important step: Leave Excel behind and manage your Financial Data with Python and Pandas!
Pandas is the Excel for Python and learning Pandas from scratch is almost as easy as learning Excel. Pandas seems to be more complex at a first glance, as it simply offers so much more functionalities. The workflows you are used to do with Excel can be done with Pandas more efficiently. Pandas is a high-level coding library where all the hardcore coding stuff with dozens of coding lines are running automatically in the background. Pandas operations are typically done in one line of code! However, it is important to learn and master Pandas in a way that
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you understand what is going on
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you are aware of the pitfalls (Don´ts)
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you know best practices (Dos)
MANAGE FINANCE DATA WITH PYTHON & PANDAS best prepares you to master new challenges and to stay ahead of your peers, fellows and competitors! Coding with Python/Pandas is one of the most in-demand skills in Finance.
This course is one of the most practical courses on Udemy with 200 Coding Exercises and a Final Project. You are free to select your individual level of difficulty. If you have no experience with Pandas at all, Part 1 will teach you all the essentials (From Zero to Hero).
Part 2 – The Core of this Course
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Import Financial Data from Free Web Sources, Excel- and CSV-Files
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Calculate Risk, Return, and Correlation of Stocks, Indexes and Portfolios
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Calculate simple Returns, log Returns, and annualized Returns & Risk
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Create your own customized Financial Index (price-weighted vs. equal-weighted vs. value-weighted)
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Understand the difference between Price Return and Total Return
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Create, analyze and optimize Stock Portfolios
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Calculate Sharpe Ratio, Systematic Risk, Unsystematic Risk, Beta and Alpha for Stocks, Indexes and Portfolios
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Understand Modern Portfolio Theory, Risk Diversification and the Capital Asset Pricing Model (CAPM)
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Forward-looking Mean-Variance Optimization (MVO) and its pitfalls
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Get an exclusive insight into how MVO is used in Real World (and why it is NOT used in many cases) -> get beyond Investments 101 level!
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Calculate Rolling Statistics (e.g. Simple Moving Averages) and aggregate, visualize and report Financial Performance
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Create Interactive Charts with Technical Indicators (SMA, Candle Stick, Bollinger Bands etc.)
Part 3 – Capstone Project
Step into the Financial Analyst / Advisor Role and give advice on a Client´s Portfolio (Final Project Challenge).
Apply and master what you have learned before!
Part 4
Some advanced topics on handling Time Series Data with Pandas.
Appendix
Do you struggle with some basic Python / Numpy concepts? Here is all you need to know if you are completely new to Python!
Why you should listen to me…
In my career, I have built an extensive level of expertise and experience in both areas: Finance and Coding
Finance:
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10 years experience in the Finance and Investment Industry…
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…where I held various quantitative & strategic positions.
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MSc in Finance
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Passed all three CFA Exams (currently no active member of the CFA Institute)
Python & Pandas:
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I led a company-wide transformation from Excel to Python/Pandas
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Code, models, and workflows are Real World Project-proven
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Instructor of the highest-rated and most trending general Course on Pandas
What are you waiting for? Guaranteed Satisfaction: Otherwise, get your money back with a 30-Days-Money-Back-Guarantee.
Looking Forward to seeing you in the Course!
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1Course Overview and how to maximize your learning successVídeo Aula
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2Tips: How to get the most out of this Course (don´t skip!)Vídeo Aula
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3Did you know that...?Vídeo Aula
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4FAQ / Important InformationTexto
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5Installation of AnacondaVídeo Aula
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6Opening a Jupyter NotebookVídeo Aula
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7How to use Jupyter NotebooksVídeo Aula
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8Downloads (Get all Course Materials here!) **UPD NOV 24**Vídeo Aula
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14Create your very first Pandas DataFrame (from csv)Vídeo Aula
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15Loading a CSV-file into PandasQuestionário
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16How to read CSV-files from other LocationsVídeo Aula
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17Pandas Display Options and the methods head() & tail()Vídeo Aula
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18First Data InspectionVídeo Aula
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19Summary StatisticsQuestionário
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20Built-in Functions, Attributes and Methods with PandasVídeo Aula
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21Make it easy: TAB Completion and TooltipVídeo Aula
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22First StepsQuestionário
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23Explore your own Dataset: Jupyter Coding Exercise 1 (Intro)Vídeo Aula
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24Explore your own Dataset: Jupyter Coding Exercise 1 (Solution)Vídeo Aula
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25Selecting ColumnsVídeo Aula
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26Selecting one Column with the "dot notation"Vídeo Aula
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27Selecting ColumnsQuestionário
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28Zero-based Indexing and Negative IndexingVídeo Aula
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29Selecting Rows with iloc (position-based indexing)Vídeo Aula
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30Slicing Rows and Columns with iloc (position-based indexing)Vídeo Aula
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31Position-based Indexing Cheat SheetsTexto
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32Position-based Indexing 1Questionário
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33Position-based Indexing 2Questionário
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34Selecting Rows with loc (label-based indexing)Vídeo Aula
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35Slicing Rows and Columns with loc (label-based indexing)Vídeo Aula
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36Label-based Indexing Cheat SheetsTexto
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37Label-based Indexing 1Questionário
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38Label-based Indexing 2Questionário
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39Indexing and Slicing with reindex()Vídeo Aula
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40Summary, Best Practices and OutlookVídeo Aula
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41Indexing and SlicingQuestionário
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42Jupyter Coding Exercise 2 - IntroVídeo Aula
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43Jupyter Coding Exercise 2 - SolutionVídeo Aula
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44**NEW** Coding Exercises with ChatGPTVídeo Aula
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45Advanced Indexing and Slicing (optional)Vídeo Aula
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46IntroductionVídeo Aula
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47Test your debugging skills!Vídeo Aula
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48Major reasons for Coding ErrorsVídeo Aula
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49The most commonly made Errors at a glanceVídeo Aula
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50Omitting cells, changing the sequence and moreVídeo Aula
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51IndexErrorsVídeo Aula
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52Indentation ErrorsVídeo Aula
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53Misuse of function names and keywordsVídeo Aula
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54TypeErrors and ValueErrorsVídeo Aula
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55**NEW** Debugging Pandas Errors with ChatGPTVídeo Aula
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56Getting help on StackOverflow.comVídeo Aula
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57How to traceback more complex ErrorsVídeo Aula
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58Problems with the Python InstallationVídeo Aula
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59External Factors and IssuesVídeo Aula
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60Errors related to the course content (Transcription Errors)Vídeo Aula
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61Summary and Debugging Flow-ChartVídeo Aula
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62**NEW** The Debugging Flow-Chart with ChatGPTVídeo Aula
