University of the Aegean – Data Science with R
Object & Purpose of the Program
The purpose of the “Data Science with R” program is to educate students and professionals in Data Science (Data Science) using the programming language R. The program provides everything needed to start the journey in data science with easy understanding the content way. We will see why data science is used everywhere today, its applications, its history and its future. The R programming language will be introduced with an extension to basic data science work. We will look at tools, techniques, technologies and libraries for Data Science. Learners will also learn to do Descriptive Analytics, do Data Munging, calculate various statistical measures and do Data Visualization. They will learn Computational Methods and Technologies (Hadoop and MapReduce) for Big Data Analysis. In addition, they will get to know popular Machine Learning packages. Using machine learning algorithms, readers will learn to do Predictive Analytics, which is a basic task and feature of Data Science.
The program is aimed at anyone interested in obtaining a knowledge background related to Data Science and the R programming language. The program is also aimed at professionals who want to improve their respective knowledge, graduates or seniors who want to pursue a career as data scientists, teachers who want to attend a state-of-the-art program.
Program Learning Objectives
Upon completion of the program, trainees will be able to:
- They use the R programming language.
- They do Descriptive Analytics.
- They do Data Munging.
- They do Data Visualization.
- They use computational methods and technologies (Hadoop and MapReduce) for Big Data Analysis.
- They perform Predictive Analytics using Machine learning algorithms.
Module 1: Introduction to data science with the programming language R
The subject of the module is the examination of the epistemology of Data Science and the introduction to the programming language R. This module has been created with a beginner in data science in mind. It provides everything you need to start the journey into data science in an easy-to-understand way. We will see why data science is used everywhere today, its applications, its history and its future. The R programming language will be introduced with an extension to basic data science work. We will look at tools, techniques and technologies for Data Science so that learners get the maximum benefit.
Week 1: Introduction to Data Science
Week 2: Introduction to the programming language R
Week 3: The use of the R language in Data Science
Week 4: R tools and libraries for Data Science applications
Module 2: Data science with programming language R
In this section students will see basic concepts of statistics and probabilities used in data science. They will also see R language techniques and libraries for data handling, cleaning, and preprocessing. They will see techniques for data visualization (Data Visualization). They will learn computational methods and technologies (Hadoop and MapReduce) for Big Data analysis.
Week 5: Basic concepts of statistics and probability
Week 6: Data Munging with R language
Week 7: Data Visualization
Week 8: Big Data Analysis
Module 3: Data science and machine learning
In this section we will focus on machine learning algorithms. We are going to explore and discuss the most important algorithms and how they are implemented in the R language. Understanding machine learning topics is vital for data scientists. Using machine learning algorithms, readers will learn to do Predictive Analytics, which is a basic task and feature of Data Science.
Week 9: Introduction to machine learning
Week 10: Machine Learning Algorithms
Week 11: Important topics in Machine Learning
Week 12: Creating Predictive Models
Week 13: Final work (Mini project)