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728 Courses

Course

Intermediate Google Sheets

  • BasicSkill Level
  • 4.8+
  • 802 reviews

Expand your Google Sheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.

Data Preparation

4 hours

Course

Forecasting in R

  • BasicSkill Level
  • 4.9+
  • 51 reviews

Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

Probability & Statistics

5 hours

Course

Deep Reinforcement Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 270 reviews

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

Artificial Intelligence

4 hours

Course

Reporting with R Markdown

  • IntermediateSkill Level
  • 4.7+
  • 321 reviews

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

Reporting

4 hours

Course

Digital Transformation with Google Cloud

  • BasicSkill Level
  • 4.8+
  • 86 reviews

This course provides an overview of the opportunities and challenges companies encounter in their digital transformation journey.

Cloud

2 hours

Course

Google: Introduction to AI Agents

  • BasicSkill Level
  • 4.8+
  • 100 reviews

Gain an overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems.

Cloud

20 min

Course

Intermediate SQL Querying with AI

  • BasicSkill Level
  • 4.8+
  • 222 reviews

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

Data Manipulation

3 hours

Course

Improving Query Performance in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 398 reviews

In this course, students will learn to write queries that are both efficient and easy to read and understand.

Software Development

4 hours

Course

Building a Go-To-Market Strategy

  • BasicSkill Level
  • 4.7+
  • 370 reviews

Create a go-to-market strategy with generative AI: target industries, generate leads, and optimize website keywords.

Artificial Intelligence

1 hour

Course

Linear Algebra for Data Science in R

  • IntermediateSkill Level
  • 4.7+
  • 133 reviews

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

Probability & Statistics

4 hours

Course

Biomedical Image Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 233 reviews

Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

Data Manipulation

4 hours

Course

Image Modeling with Keras

  • AdvancedSkill Level
  • 4.8+
  • 89 reviews

Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.

Artificial Intelligence

4 hours

Course

Introduction to R for Finance

  • BasicSkill Level
  • 4.7+
  • 94 reviews

Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.

Applied Finance

4 hours

Course

Statistical Thinking in Python (Part 1)

  • IntermediateSkill Level
  • 4.8+
  • 107 reviews

Build the foundation you need to think statistically and to speak the language of your data.

Probability & Statistics

3 hours

Course

Marketing Analytics for Business

  • BasicSkill Level
  • 4.8+
  • 559 reviews

Discover how Marketing Analysts use data to understand customers and drive business growth.

Leadership

2 hours

Course

Building Marketing Workflows with n8n

  • BasicSkill Level
  • 4.9+
  • 50 reviews

Build marketing workflows in n8n using AI agents. Automate campaign strategy, conversion optimization, and lead generation from scratch.

Artificial Intelligence

3 hours

Course

Visualizations in Sigma

  • BasicSkill Level
  • 4.8+
  • 178 reviews

Learn to build and customize Sigma charts to tell clear, compelling data stories—no coding required.

Data Visualization

2 hours

Course

User-Oriented Design in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 415 reviews

Learn how to design Power BI visualizations and reports with users in mind.

Data Visualization

2 hours

Course

Machine Learning for Finance in Python

  • IntermediateSkill Level
  • 4.8+
  • 208 reviews

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Machine Learning

4 hours

Course

Introduction to Databricks Genie

  • BasicSkill Level
  • 4.8+
  • 59 reviews

Ask data questions in plain English with Databricks Genie - build spaces, curate business language, and monitor quality.

Data Engineering

2 hours

Course

Introduction to Spark SQL in Python

  • AdvancedSkill Level
  • 4.7+
  • 142 reviews

Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.

Data Manipulation

4 hours

Course

Foundations of Inference in R

  • IntermediateSkill Level
  • 4.7+
  • 51 reviews

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Probability & Statistics

4 hours

Course

Quantitative Risk Management in Python

  • AdvancedSkill Level
  • 4.8+
  • 213 reviews

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

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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