Below you can find the best data science courses that are currently available on the internet. They are updated regularly with the aim to keep all their characteristics like price, level of difficulty, and certificate quality up to date so you can make an informed decision about which is the best data science course for you. Feel free to use the filters below to sift through the entire database on Courseroot. In the list below you will find all Data Science courses that we have in our database from Coursera. Coursera is an incredble platform for online classes with a high standard in regards to quality. They work with top universities across the globe, like Standford, Hardvard, UC Berkley, and many more, to make education more accessible via the internet.
Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking abou... More information
Este curso te proporcionara las bases del lenguaje de programacion estadistica R, la lengua franca de la estadistica, el cual te permitira escribir programas que lean, manipulen y analicen datos cuantitativos. Te explicaremos la instalacion del lenguaje; tambien veras una introduccion a los sistemas base de graficos y al paquete para graficar ggplot2, para visualizar ...
This course introduces you to the basic biology of modern genomics and the experimental tools that we use to measure it. We'll introduce the Central Dogma of Molecular Biology and cover how next-generation sequencing can be used to measure DNA, RNA, and epigenetic patterns. You'll also get an introduction to the key concepts in computing and data science that you'll n... More information
This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings. As th... More information
In this project-centered course*, you will create a content-rich infographic on a topic of your choice using Adobe Illustrator (which you can download for a free, 30-day trial). You might choose to create a visual representation of data from the world of sports, entertainment, politics, or science, to explain a business trend or environmental issue, or even to present... More information
In this course you will be introduced to the basic ideas behind the qualitative research in social science. You will learn about data collection, description, analysis and interpretation in qualitative research. Qualitative research often involves an iterative process. We will focus on the ingredients required for this process: data collection and analysis. You won't ... More information
As data collection has increased exponentially, so has the need for people skilled at using and interacting with data; to be able to think critically, and provide insights to make better decisions and optimize their businesses. This is a data scientist, ... More information
This class provides an introduction to the Python programming language and the iPython notebook. This is the third course in the Genomic Big Data Science Specialization from Johns Hopkins University.... More information
Process mining is the missing link between model-based process analysis and data-oriented analysis techniques. Through concrete data sets and easy to use software the course provides data science knowledge that can be applied directly to analyze and improve processes in a variety of domains. Data science is the profession of the future, because organizations that are ... More information
If you want to break into competitive data science, then this course is for you! Participating in predictive modelling competitions can help you gain practical experience, improve and harness your data modelling skills in various domains such as credit, insurance, marketing, natural language processing, sales... More information
This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions. Upon completing this course you will be able to identify a... More information
Statistical experiment design and analytics are at the heart of data science. In this course you will design statistical experiments and analyze the results using modern methods. You will also explore the common pitfalls in interpreting statistical arguments, especially those associated with big data. Collectively, this course will help you internalize a core set of p... More information
Mathematical thinking is crucial in all areas of computer science: algorithms, bioinformatics, computer graphics, data science, machine learning, etc. In this course, we will learn the most important tools used in discrete mathematics: induction, recursion, logic, invariants, examples, optimality. We will use these tools to answer typical programming questions like: H...
Introduces to the commands that you need to manage and analyze directories, files, and large sets of genomic data. This is the fourth course in the Genomic Big Data Science Specialization from Johns Hopkins University.... More information
This four-module course introduces users to Julia as a first language. Julia is a high-level, high-performance dynamic programming language developed specifically for scientific computing. This language will be particularly useful for applications in physics, chemistry, astronomy, engineering, data science, bioinformatics and many more. As open source software, you wi... More information
Writing good code for data science is only part of the job. In order to maximizing the usefulness and reusability of data science software, code must be organized and distributed in a manner that adheres to community-based standards and provides a good user experience. This course covers the primary means by which R software is organized and distributed to others. We ... More information
>>> By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area <<< This course, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights in... More information
The Library of Integrative Network-based Cellular Signatures (LINCS) is an NIH Common Fund program. The idea is to perturb different types of human cells with many different types of perturbations such as: drugs and other small molecules; genetic manipulations such as knockdown or overexpression of single genes; manipulation of the extracellular microenvironment condi... More information
The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is dat... More information
This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours. Module 1 - Python Basics ... More information
The value of IoT can be found within the analysis of data gathered from the system under observation, where insights gained can have direct impact on business and operational transformation. Through analysis data correlation, patterns, trends, and other insight are discovered. Insight leads to better communication between stakeholders, or actionable insights, which ca... More information
SQL is a powerful language which is used for communicating with databases. Before you step into the field of data science, it is vitally important that you set yourself apart by mastering the foundations of SQL. The purpose of this course is to introduce relational database concepts and help you learn and apply knowledge of the SQL language. Learners will also practic...
An introduction to the statistics behind the most popular genomic data science projects. This is the sixth course in the Genomic Big Data Science Specialization from Johns Hopkins University.... More information