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127 Courses

Course

Building Dashboards with shinydashboard

  • BasicSkill Level
  • 4.7+
  • 79 reviews

Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

Reporting

4 hours

Course

Handling Missing Data with Imputations in R

  • AdvancedSkill Level
  • 4.7+
  • 104 reviews

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

Data Manipulation

4 hours

Course

Communicating with Data in the Tidyverse

  • BasicSkill Level
  • 4.8+
  • 197 reviews

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Data Visualization

4 hours

Course

Modeling with tidymodels in R

  • IntermediateSkill Level
  • 4.8+
  • 179 reviews

Learn to streamline your machine learning workflows with tidymodels.

Machine Learning

4 hours

Course

Market Basket Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 93 reviews

Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.

Data Manipulation

4 hours

Course

Credit Risk Modeling in R

  • IntermediateSkill Level
  • 4.7+
  • 87 reviews

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Applied Finance

4 hours

Course

Visualizing Geospatial Data in R

  • IntermediateSkill Level
  • 4.5+
  • 87 reviews

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Data Visualization

4 hours

Course

Inference for Numerical Data in R

  • AdvancedSkill Level
  • 4.8+
  • 107 reviews

In this course youll learn techniques for performing statistical inference on numerical data.

Probability & Statistics

4 hours

Course

Fraud Detection in R

  • IntermediateSkill Level
  • 4.7+
  • 38 reviews

Learn to detect fraud with analytics in R.

Machine Learning

4 hours

Course

Quantitative Risk Management in R

  • BasicSkill Level
  • 4.8+
  • 83 reviews

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Applied Finance

5 hours

Course

Support Vector Machines in R

  • IntermediateSkill Level
  • 4.8+
  • 91 reviews

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

Machine Learning

4 hours

Course

Data Manipulation with data.table in R

  • BasicSkill Level
  • 4.6+
  • 22 reviews

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

Data Manipulation

4 hours

Course

Bond Valuation and Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 89 reviews

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Applied Finance

4 hours

Course

Developing R Packages

  • IntermediateSkill Level
  • 4.7+
  • 151 reviews

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

Software Development

4 hours

Course

HR Analytics: Exploring Employee Data in R

  • IntermediateSkill Level
  • 4.8+
  • 37 reviews

Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.

Exploratory Data Analysis

5 hours

Course

Intermediate Portfolio Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 70 reviews

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

Applied Finance

5 hours

Course

A/B Testing in R

  • IntermediateSkill Level
  • 4.8+
  • 90 reviews

Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.

Probability & Statistics

4 hours

Course

Inference for Categorical Data in R

  • AdvancedSkill Level
  • 4.8+
  • 111 reviews

In this course youll learn how to leverage statistical techniques for working with categorical data.

Probability & Statistics

4 hours

Course

R For SAS Users

  • BasicSkill Level
  • 4.7+
  • 27 reviews

Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.

Software Development

4 hours

Course

GARCH Models in R

  • AdvancedSkill Level
  • 4.8+
  • 96 reviews

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

Applied Finance

4 hours

FAQs

What is data science?

Data science is an area of expertise focused on gaining information from data. Using programming skills, scientific methods, algorithms, and more, data scientists analyze data to form actionable insights.

How can I learn data science?

You’ll need to learn a programming language such as Python or R and master the principles of math and statistics. Knowledge of data analysis methods and data science tools is also essential. There are many ways to learn data science. As well as formal means of education, such as a degree or university study, there are plenty of other resources to help you learn at your own pace. As well as online courses and tutorials, there are books, videos, and more.

What skills are required for data science?

As well as knowledge of mathematics and statistics, data scientists need programming skills in languages such as Python, R, and SQL. Additionally, data science requires the ability to work with large data sets, knowledge of data visualization, data wrangling, and database management. Skills in machine learning and deep learning can also be useful.

What can I use data science for?

In a professional capacity, almost every industry can use data science to some degree. Healthcare organizations use data science to detect and cure diseases, while finance companies use it to detect and prevent fraud. All kinds of industries use data science for marketing, such as building recommendation systems and analyzing customer churn.

Is data science a good career?

Yes, data science is among the fastest-growing sectors in the US and worldwide. It’s also one of the best-paid careers out there. According to data from Payscale, experience data scientists earn an average of $97,609 and have a satisfaction rating of four stars out of five in the US.

Is it difficult to become a data scientist?

There are a few things to consider here. First, data science degrees can be competitive to get onto, often requiring consistently high grades. Similarly, many of the skills required for data science require a lot of study and patience. It can take several months to master all of the necessary basics, as well as a lot of practical experience to secure an entry-level position.

Does data science require coding?

Yes, you’ll need some coding experience in languages such as Python, R, SQL, Java, and C/C++. However, due to its relatively simple syntax, Python programming language is often the preferred choice among newcomers.

How long does it take to become a data scientist?

For a person with no prior coding experience and/or mathematical background, it can typically take 7 to 12 months of intensive studies to be at the level of an entry-level data scientist. However, it is important to remember that learning only the theoretical basis of data science may not make you a real data scientist.

What topics can I study within data science?

Once you’ve mastered the foundations of data science, you can then specialize in a variety of areas, including machine learning, artificial intelligence, big data analysis, business analytics and intelligence, data mining, and more.

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