This Python and R course offers comprehensive training in Python and R, two of the most widely used programming languages for data analysis and scientific computing. It begins with an introduction to Python, covering its core syntax, structures, and object-oriented programming. Then, it delves into R, focusing on data processing and its unique programming features. The final module bridges both languages through a practical case study, highlighting their integration for solving real-world problems. Designed for students, professionals, and researchers, this program provides both theoretical knowledge and hands-on experience, enabling participants to apply programming skills to data-driven projects across various fields, from analytics to machine learning.
Python and R
Big Data
40 hours
Introduction
Objectives
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Master Python and R programming basics for data analysis.
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Develop object-oriented programming skills in Python.
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Learn to process and analyze data effectively in R.
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Integrate Python and R for real-world problem-solving.
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Apply programming skills to data-driven case studies.
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Build a foundation for careers in data science and analytics.
Table of Contents
UNIT 1. THE PYTHON PROGRAMMING LANGUAGE
Introduction to python
Data types (I)
Data types (II) and variables
Data groupings (I)
Data groupings (II) and input/output
UNIT 2. STRUCTURES AND FUNCTIONS IN PYTHON. OBJECT-ORIENTED PROGRAMMING
Python structures
While loop
For loop, counters, witnesses, accumulators and iteration
Functions
Object-oriented programming
UNIT 3. DATA PROCESSING IN R
Introduction to R
First steps in R
Vectors
Matrices and lists
Dataframes
UNIT 4. THE PROGRAMMING LANGUAGE R
Functions
Conditional structures and loops
Data files
Graphics (I)
Graphics (II) and programming
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