Q4 2019 Exam: November 11 - 23 register here 
Q2 2020 Exam: March 16 - April 4, 2020 register here


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You can access these classes at the Datacamp website. You are responsible for cost of the Datacamp classes. If you choose Datacamp, you must complete the following classes.

Note: When you complete the classes, upload the Datacamp certificates to your FDP Profile.


 1  Introduction to Python     An introduction to the basic concepts of Python. Candidates will learn how to use Python both interactively and through a script.  Candidates will learn about NumPy, a very important Python package, variables, and Python’s basic data types.
 2 Intermediate Python for Data Science The intermediate python course is crucial to applying the techniques that candidates will learn in the FDP program.  Candidates will learn to visualize real data with Matplotlib's functions and to work with different data structures.
 3 Pandas Foundations  Pandas' dataframes are the most widely used representation of complex data collections within Python. Whether in finance, scientific fields, or data science, familiarity with Pandas is essential.  This course teaches candidates to work with real-world data sets containing both string and numeric data, often structured around time series.
 4 Manipulating DataFrames with Pandas In this course, candidates will learn how to leverage Pandas' extremely powerful data manipulation engine to get the most out of their data.  Candidates will learn how to extract, filter, and transform data from dataframes in order to gain further insights into the data.
 5 Importing and Managing Financial Data in Python  In this course, candidates will learn how to get data out of Excel into pandas and back.  Candidates will also learn how to pull stock prices from various online APIs like Google or Yahoo! Finance, macro data from the Federal Reserve, and exchange rates from OANDA.  Finally, candidates will learn how to calculate returns for various time horizons, analyze stock performance by sector for IPOs, and calculate and summarize correlations
 6 Statistical thinking with Python I  In this course, candidates will start building the foundation they need to think statistically.  This refresher course on statistics will use Python to demonstrate the applications of important statistical techniques.
 7 Statistical thinking with Python II  In this course, candidates will to perform the two key tasks in statistical inference, parameter estimation, and hypothesis testing.  Candidates will work with real data sets as they learn.


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