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.

Data, AI, and Cloud Courses

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Cleaning Data with PySpark

Learn how to clean data with Apache Spark in Python.

AdvancedSkill Level

Over 3 hoursData PreparationMike MetzgerCourse

Introduction to Azure

Explore Azure services like Compute, Storage, and Automation, with hands-on experience.

BasicSkill Level

1-2 hoursCloudShahzad MianCourse

Introduction to R for Finance

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

BasicSkill Level

Over 3 hoursApplied FinanceLore DirickCourse

Artificial Intelligence Governance

Learn AI governance with Collibra. Build, embed, and scale responsible AI using tools, frameworks, and MLOps workflows.

BasicSkill Level

2-3 hoursArtificial IntelligenceAlexandre T'KintCourse

Reporting in SQL

Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.

IntermediateSkill Level

Over 3 hoursReportingTyler PernesCourse

Data Management in Databricks

Learn data management in Databricks with Delta Lake, including ACID transactions, schema enforcement, and security.

BasicSkill Level

Over 3 hoursData ManagementSmriti MishraCourse

A/B Testing in Python

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

IntermediateSkill Level

Over 3 hoursProbability & StatisticsMoe Lotfy, PhDCourse

Data Types and Functions in Snowflake

Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.

IntermediateSkill Level

Over 3 hoursData ManipulationJake McGrathCourse

Window Functions in Snowflake

Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.

IntermediateSkill Level

Over 3 hoursData ManipulationJake McGrathCourse

Introduction to TensorFlow in Python

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

IntermediateSkill Level

Over 3 hoursMachine LearningIsaiah HullCourse

Linear Algebra for Data Science in R

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

IntermediateSkill Level

Over 3 hoursProbability & StatisticsEric EagerCourse

Introduction to Portfolio Risk Management in Python

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

IntermediateSkill Level

Over 3 hoursApplied FinanceDakota WixomCourse

Introduction to GPTs

Learn how to use GPT tools responsibly and confidently. Discover how these tools work and techniques for writing prompts and evaluating outputs.

BasicSkill Level

1-2 hoursArtificial IntelligenceJasmin LudolfCourse

Credit Risk Modeling in Python

Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.

IntermediateSkill Level

Over 3 hoursApplied FinanceMichael CrabtreeCourse

Introduction to GCP

Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.

BasicSkill Level

2-3 hoursCloudNabeel ImamCourse

Data Types and Exceptions in Java

Learn to work with Plain Old Java Objects, master the Collections Framework, and handle exceptions like a pro, with logging to back it all up!

IntermediateSkill Level

Over 3 hoursSoftware DevelopmentJim WhiteCourse

Calculations in Tableau

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

AdvancedSkill Level

Over 3 hoursData VisualizationAgata Bak-GeerinckCourse

Data Validation in Excel

Learn Excel data validation to improve accuracy, create drop-downs, and manage inventory and orders with confidence.

BasicSkill Level

2-3 hoursData ManagementRamiz AssafCourse

Introduction to Oracle SQL

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

BasicSkill Level

Over 3 hoursData ManipulationHadrien LacroixCourse

Introduction to Deep Learning with Keras

Learn to start developing deep learning models with Keras.

IntermediateSkill Level

Over 3 hoursArtificial IntelligenceMiguel EstebanCourse

Machine Learning for Finance in Python

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

IntermediateSkill Level

Over 3 hoursMachine LearningNathan GeorgeCourse

Understanding GDPR

Gain a clear understanding of GDPR principles and how to set up GDPR-compliant processes in this comprehensive course.

BasicSkill Level

1-2 hoursData LiteracyShalini KurapatiCourse

Foundations of Inference in R

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

IntermediateSkill Level

Over 3 hoursProbability & StatisticsJo HardinCourse

Deep Reinforcement Learning in Python

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

AdvancedSkill Level

Over 3 hoursArtificial IntelligenceTimothée CarayolCourse

Financial Trading in Python

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

IntermediateSkill Level

Over 3 hoursApplied FinanceChelsea YangCourse

Sentiment Analysis in Python

Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

IntermediateSkill Level

Over 3 hoursMachine LearningVioleta MishevaCourse

Foundations of Probability in R

In this course, youll learn about the concepts of random variables, distributions, and conditioning.

BasicSkill Level

Over 3 hoursProbability & StatisticsDavid RobinsonCourse

Introduction to Sigma

Get started with Sigma! Learn how to build and customize simple, interactive dashboards for real-time analytics.

BasicSkill Level

2-3 hoursData ManipulationKatrina MenneCourse

Data Storytelling Case Study: Green Businesses

Practice data storytelling using real-world examples! Communicate complex insights effectively with a dataset of certified green businesses.

BasicSkill Level

1-2 hoursData LiteracyCamilo MartínezCourse

Data Visualization in Databricks

Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.

BasicSkill Level

Over 3 hoursData VisualizationGang WangCourse

FAQs

Cleaning Data with PySpark

Introduction to Azure

Introduction to R for Finance

Artificial Intelligence Governance

Reporting in SQL

Data Management in Databricks

A/B Testing in Python

Data Types and Functions in Snowflake

Window Functions in Snowflake

Introduction to TensorFlow in Python

Linear Algebra for Data Science in R

Introduction to Portfolio Risk Management in Python

Introduction to GPTs

Credit Risk Modeling in Python

Introduction to GCP

Data Types and Exceptions in Java

Calculations in Tableau

Data Validation in Excel

Introduction to Oracle SQL

Introduction to Deep Learning with Keras

Machine Learning for Finance in Python

Understanding GDPR

Foundations of Inference in R

Deep Reinforcement Learning in Python

Financial Trading in Python

Sentiment Analysis in Python

Foundations of Probability in R

Introduction to Sigma

Data Storytelling Case Study: Green Businesses

Data Visualization in Databricks

Skill Level

technology

topic

FAQs

How can I learn data science?

What skills are required for data science?

What can I use data science for?

Is data science a good career?

Is it difficult to become a data scientist?

Does data science require coding?

How long does it take to become a data scientist?

What topics can I study within data science?