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Online Classes > DataCamp

DataCamp | Udemy 

Candidates can choose between either two (2) R or two (2) Python classes.
Classes can be accessed 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, submit the Datacamp certificates using this form.

DataCamp: Python track

1.    Introduction to Python   
Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. Unlike other Python tutorials, this course focuses on Python specifically for data science. In our Introduction to Python course, you’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses.

2.    Intermediate Python  
Intermediate Python is crucial for any aspiring data science practitioner learning Python. Learn to visualize real data with Matplotlib's functions and get acquainted with data structures such as the dictionary and the pandas DataFrame. After covering key concepts such as boolean logic, control flow, and loops in Python, you'll be ready to blend together everything you've learned to solve a case study using hacker statistics.

DataCamp: R track

1.    Introduction to R  
R programming language is a useful tool for data scientists, analysts, and statisticians, especially those working in academic settings. R's ability to handle complex analyses such as machine learning, financial modeling, and more makes it a valuable asset for a wide range of data-related tasks. This introduction to R course covers the basics of this open source language, including vectors, factors, lists, and data frames. You’ll gain useful coding skills and be ready to start your own data analysis in R,

2.    Intermediate R  
Intermediate R is the next stop on your journey in mastering the R programming language. In this R training, you will learn about conditional statements, loops, and functions to power your own R scripts. Next, make your R code more efficient and readable using the apply functions. Finally, the utilities chapter gets you up to speed with regular expressions in R, data structure manipulations, and times and dates. This course will allow you to take the next step in advancing your overall knowledge and capabilities while programming in R.

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