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292 Courses

Course

Data Analysis in Excel

  • BasicSkill Level
  • 4.5+
  • 13.3K

Learn how to analyze data with PivotTables and intermediate logical functions before moving on to tools such as what-if analysis and forecasting.

Reporting

3 hours

Course

Exploratory Data Analysis in Python

  • IntermediateSkill Level
  • 4.6+
  • 7.8K

Learn how to explore, visualize, and extract insights from data using exploratory data analysis (EDA) in Python.

Exploratory Data Analysis

4 hours

Course

Exploratory Data Analysis in SQL

  • IntermediateSkill Level
  • 4.4+
  • 7.5K

Learn how to explore whats available in a database: the tables, relationships between them, and data stored in them.

Exploratory Data Analysis

4 hours

Course

Exploratory Data Analysis in Power BI

  • BasicSkill Level
  • 4.5+
  • 4K

Learn how to build impactful reports with Power BI’s Exploratory Data Analysis (EDA) that uncover insights faster and drive business value.

Exploratory Data Analysis

3 hours

Course

Exploratory Data Analysis in R

  • IntermediateSkill Level
  • 4.5+
  • 2.1K

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Exploratory Data Analysis

4 hours

Course

Data Analysis in Google Sheets

  • BasicSkill Level
  • 4.5+
  • 1.7K

Learn to use Google Sheets to clean, analyze, and draw insights from data. Discover how to sort, filter, and use VLOOKUP to combine data.

Data Manipulation

3 hours

Course

Bayesian Data Analysis in Python

  • IntermediateSkill Level
  • 4.6+
  • 525

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

Probability & Statistics

4 hours

Course

Fundamentals of Bayesian Data Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 363

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

Probability & Statistics

4 hours

Course

Case Study: Exploratory Data Analysis in R

  • BasicSkill Level
  • 4.3+
  • 316

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Exploratory Data Analysis

4 hours

Course

Case Study: Data Analysis in Databricks

  • AdvancedSkill Level
  • 4.2+
  • 299

Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.

Importing & Cleaning Data

3 hours

Course

Analyzing Marketing Campaigns with pandas

  • BasicSkill Level
  • 4.5+
  • 1K

Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!

Exploratory Data Analysis

4 hours

Course

HR Analytics: Exploring Employee Data in R

  • IntermediateSkill Level
  • 4.4+
  • 358

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

Exploratory Data Analysis

5 hours

Course

Supply Chain Analytics in Python

  • IntermediateSkill Level
  • 4.6+
  • 336

Leverage the power of Python and PuLP to optimize supply chains.

Exploratory Data Analysis

4 hours

Course

Marketing Analytics: Predicting Customer Churn in Python

  • IntermediateSkill Level
  • 4.5+
  • 294

Learn how to use Python to analyze customer churn and build a model to predict it.

Exploratory Data Analysis

4 hours

Course

Analyzing US Census Data in Python

  • IntermediateSkill Level
  • 4.5+
  • 163

Learn to use the Census API to work with demographic and socioeconomic data.

Exploratory Data Analysis

5 hours

Course

Analyzing US Census Data in R

  • IntermediateSkill Level
  • 4.5+
  • 74

Learn to rapidly visualize and explore demographic data from the United States Census Bureau using tidyverse tools.

Exploratory Data Analysis

4 hours

Course

DAX Functions in Power BI

  • BasicSkill Level
  • 4.6+
  • 4.9K

Data Analysis Expressions (DAX) allow you to take your Power BI skills to the next level by writing custom functions.

Data Manipulation

3 hours

Course

Introduction to BigQuery

  • IntermediateSkill Level
  • 4.5+
  • 1.2K

Unlock BigQuerys power: grasp its fundamentals, execute queries, and optimize workflows for efficient data analysis.

Data Engineering

4 hours

Course

Writing Efficient R Code

  • IntermediateSkill Level
  • 4.5+
  • 1.1K

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Software Development

4 hours

Course

Intermediate SQL Querying with AI

  • BasicSkill Level
  • 4.8+
  • 663

Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.

Data Manipulation

3 hours

Course

Data Processing in Shell

  • IntermediateSkill Level
  • 4.6+
  • 572

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Data Manipulation

4 hours

Course

Writing Functions and Stored Procedures in SQL Server

  • IntermediateSkill Level
  • 4.6+
  • 541

Master SQL Server programming by learning to create, update, and execute functions and stored procedures.

Software Development

4 hours

Course

Statistical Techniques in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 478

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

Probability & Statistics

4 hours

Course

Dealing With Missing Data in R

  • BasicSkill Level
  • 4.3+
  • 382

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Data Preparation

4 hours

Course

Introduction to DataLab

  • BasicSkill Level
  • 4.5+
  • 269

Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.

Reporting

1 hour

Course

Introduction to Spark with sparklyr in R

  • IntermediateSkill Level
  • 4.5+
  • 242

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

Data Engineering

4 hours

Course

Developing R Packages

  • IntermediateSkill Level
  • 4.4+
  • 173

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

Introduction to Python

  • BasicSkill Level
  • 4.6+
  • 142K

Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.

Software Development

4 hours

Course

Introduction to R

  • BasicSkill Level
  • 4.7+
  • 36.2K

Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.

Software Development

4 hours

Course

Introduction to DAX in Power BI

  • BasicSkill Level
  • 4.6+
  • 13.3K

Enhance your Power BI knowledge, by learning the fundamentals of Data Analysis Expressions (DAX) such as calculated columns, tables, and measures.

Data Manipulation

3 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.