Data Science & Analytics courses

4.06

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.

4.66

Solve time series and forecasting problems in TensorFlowPrepare data for time series learning using best practicesExplore how RNNs and ConvNets can be used for predictionsBuild a sunspot prediction model using real-world data

4.72

This online course is an introduction into formal concept analysis (FCA), a mathematical theory oriented at applications in knowledge representation, knowledge acquisition, data analysis and visualization. It provides tools for understanding the dat...

4.78

Differentiate between a capstone, case study, and a portfolioIdentify the key features and attributes of a completed case studyApply the practices and procedures associated with the data analysis process to a given set of dataDiscuss...

Most of the useful data in the world, from economic data to news content to geographic information, lives somewhere on the internet - and this course will teach you how to access it. You'll explore...

4.72

This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held...

4.64

BEST R BEGINNERS COURSE ON UDEMY! LEARN R PROGRAMMING IN 2 HOURS! This course will not waste your time, Are you tired of watching tutorials that take hours to explain simple concepts? You came to...

Volatility is an essential concept in finance, which is why GARCH models in Python are a popular choice for forecasting changes in variance, specifically when working with time-series data that are time-dependant. This course will...

4.5

A self-paced course that helps you to understand the various Statistical Techniques from the very basics and how each technique is employed on a real world data set to analyze and conclude insights. Statistics and...

4.48

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining....

Did you know that data scientists and data analysts spend a large amount of time cleaning data before they can analyze it? This is because real-world data is messy. To help you navigate messy data...

From a machine learning perspective, regression is the task of predicting numerical outcomes from various inputs. In this course, you'll learn about different regression models, how to train these models in R, how to evaluate...

4.83

Confidence intervals and Hypothesis tests are very important tools in the Business Statistics toolbox. A mastery over these topics will help enhance your business decision making and allow you to understand and measure the extent...

4.33

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...

In this course you learn to build, refine, extrapolate, and, in some cases, interpret models designed for a single, sequential series. There are three modeling approaches presented. The traditional, Box-Jenkins approach for modeling time series...

Before you can analyze data, you first have to acquire it. This course teaches you how to build pipelines to import data kept in common storage formats. You’ll use pandas, a major Python library for...

4.76

This course provides a framework for how analysts can create and evaluate quantitative measures. Consider the many tricky concepts that are often of interest to analysts, such as health, educational attainment and trust in government....

4

R Programming Capstone

4.59

The capstone course, Design and Build a Data Warehouse for Business Intelligence Implementation, features a real-world case study that integrates your learning across all courses in the specialization. In response to business requirements presented...

3.76

A warm welcome to the R Programming course by Uplatz. R is a programming language that provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering) and graphica...