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722 Courses

Course

Marketing Analytics for Business

  • BasicSkill Level
  • 4.8+
  • 553 reviews

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

Leadership

2 hours

Course

Introduction to Oracle SQL

  • BasicSkill Level
  • 4.8+
  • 243 reviews

Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.

Data Manipulation

4 hours

Course

Financial Trading in Python

  • IntermediateSkill Level
  • 4.8+
  • 276 reviews

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

Applied Finance

4 hours

Course

Statistical Thinking in Python (Part 1)

  • IntermediateSkill Level
  • 4.8+
  • 106 reviews

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

Probability & Statistics

3 hours

Course

Introduction to Generative AI in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 327 reviews

Learn to build AI applications using Snowflake Cortexs built-in LLM functions for text analysis, generation, and multi-step workflows.

Artificial Intelligence

2 hours

Course

Deep Reinforcement Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 267 reviews

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

Artificial Intelligence

4 hours

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+
  • 230 reviews

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

Data Manipulation

4 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 Subagents

  • IntermediateSkill Level
  • 4.8+
  • 75 reviews

Learn how to use and create sub-agents in Claude Code to manage context, delegate tasks, and build workflows that keep your conversation clean and focused.

Artificial Intelligence

2 hours

Course

User-Oriented Design in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 407 reviews

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

Data Visualization

2 hours

Course

Building a Go-To-Market Strategy

  • BasicSkill Level
  • 4.7+
  • 364 reviews

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

Artificial Intelligence

1 hour

Course

Building Marketing Workflows with n8n

  • BasicSkill Level
  • 4.9+
  • 45 reviews

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

Artificial Intelligence

3 hours

Course

NoSQL Concepts

  • IntermediateSkill Level
  • 4.8+
  • 504 reviews

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Data Engineering

2 hours

Course

Building Web Applications with Shiny in R

  • IntermediateSkill Level
  • 4.7+
  • 213 reviews

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

Software Development

4 hours

Course

Digital Transformation with Google Cloud

  • BasicSkill Level
  • 4.8+
  • 81 reviews

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

Cloud

2 hours

Course

Visualizations in Sigma

  • BasicSkill Level
  • 4.8+
  • 170 reviews

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

Data Visualization

2 hours

Course

Intermediate Workflow Automation with n8n

  • IntermediateSkill Level
  • 4.8+
  • 39 reviews

Design resilient, production-ready n8n automations that fetch APIs, process data in batches, handle errors, and run unattended on a schedule.

Artificial Intelligence

4 hours

Course

Quantitative Risk Management in Python

  • AdvancedSkill Level
  • 4.8+
  • 211 reviews

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

Applied Finance

4 hours

Course

Introduction to Polars

  • BasicSkill Level
  • 4.8+
  • 389 reviews

Learn how to efficiently transform, clean, and analyze data using Polars, a Python library for fast data manipulation.

Data Manipulation

3 hours

Course

Improving Query Performance in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 388 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

Foundations of Inference in R

  • IntermediateSkill Level
  • 4.7+
  • 50 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

Introduction to Spark SQL in Python

  • AdvancedSkill Level
  • 4.7+
  • 137 reviews

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

Data Manipulation

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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Make progress on the go with our mobile courses and daily 5-minute coding challenges.