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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Introduction to dbt

This course introduces dbt for data modeling, transformations, testing, and building documentation.

IntermediateSkill Level

Over 3 hoursData EngineeringMike MetzgerCourse

ETL and ELT in Python

Learn to build effective, performant, and reliable data pipelines using Extract, Transform, and Load principles.

IntermediateSkill Level

Over 3 hoursData EngineeringJake McGrathCourse

Developing AI Systems with the OpenAI API

Leverage the OpenAI API to get your AI applications ready for production.

IntermediateSkill Level

Over 3 hoursArtificial IntelligenceFrancesca DonadoniCourse

Hypothesis Testing in Python

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

IntermediateSkill Level

Over 3 hoursProbability & StatisticsJames ChapmanCourse

Retrieval Augmented Generation (RAG) with LangChain

Learn cutting-edge methods for integrating external data with LLMs using Retrieval Augmented Generation (RAG) with LangChain.

IntermediateSkill Level

Over 3 hoursArtificial IntelligenceMeri NovaCourse

Data-Driven Decision Making in SQL

Learn how to analyze a SQL table and report insights to management.

IntermediateSkill Level

Over 3 hoursData LiteracyBart BaesensCourse

Introduction to Object-Oriented Programming in Python

Discover the fundamental concepts of object-oriented programming (OOP), building custom classes and objects!

IntermediateSkill Level

Over 3 hoursSoftware DevelopmentGeorge BoormanCourse

Intermediate Deep Learning with PyTorch

Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.

IntermediateSkill Level

Over 3 hoursArtificial IntelligenceMichał OleszakCourse

Writing Functions in Python

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

IntermediateSkill Level

Over 3 hoursSoftware DevelopmentShayne MielCourse

Sampling in Python

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

IntermediateSkill Level

Over 3 hoursProbability & StatisticsJames ChapmanCourse

Introduction to Kubernetes

In this course, you will learn the fundamentals of Kubernetes and deploy and orchestrate containers using Manifests and kubectl instructions.

IntermediateSkill Level

Over 3 hoursSoftware DevelopmentFrank HeilmannCourse

Introduction to Embeddings with the OpenAI API

Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAIs embedding model!

IntermediateSkill Level

Over 3 hoursArtificial IntelligenceEmmanuel PireCourse

Containerization and Virtualization Concepts

Learn the essentials of VMs, containers, Docker, and Kubernetes. Understand the differences to get started!

IntermediateSkill Level

2-3 hoursSoftware DevelopmentJulia OstheimerCourse

Financial Modeling in Excel

Learn about Excel financial modeling, including cash flow, scenario analysis, time value, and capital budgeting.

IntermediateSkill Level

Over 3 hoursApplied FinanceNick EdwardsCourse

Advanced Excel Functions

Boost your Excel skills with advanced referencing, lookup, and database functions using practical exercises.

IntermediateSkill Level

2-3 hoursData ManipulationAgata Bak-GeerinckCourse

Preprocessing for Machine Learning in Python

Learn how to clean and prepare your data for machine learning!

IntermediateSkill Level

Over 3 hoursMachine LearningJames ChapmanCourse

Data Types in Python

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

IntermediateSkill Level

Over 3 hoursSoftware DevelopmentJason MyersCourse

Introduction to FastAPI

Build robust, production-grade APIs with FastAPI, mastering HTTP operations, validation, and async execution to create efficient data and ML pipelines.

IntermediateSkill Level

Over 3 hoursSoftware DevelopmentMatt EckerleCourse

Working with Dates and Times in Python

Learn how to work with dates and times in Python.

IntermediateSkill Level

Over 3 hoursSoftware DevelopmentDataCamp Content CreatorCourse

Exploratory Data Analysis in R

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

IntermediateSkill Level

Over 3 hoursExploratory Data AnalysisAndrew BrayCourse

Introduction to Natural Language Processing in Python

Learn fundamental natural language processing techniques using Python and how to apply them to extract insights from real-world text data.

IntermediateSkill Level

Over 3 hoursMachine LearningKatharine JarmulCourse

Introduction to Data Modeling in Snowflake

Step right into the dynamic world of data modeling with Snowflake!

IntermediateSkill Level

Over 3 hoursData EngineeringMargarita TorresCourse

Designing Agentic Systems with LangChain

Get to grips with the foundational components of LangChain agents and build custom chat agents.

IntermediateSkill Level

Over 3 hoursArtificial IntelligenceDilini K. Sumanapala, PhDCourse

Analyzing Business Data in SQL

Learn to write SQL queries to calculate key metrics that businesses use to measure performance.

IntermediateSkill Level

Over 3 hoursReportingMichel SemaanCourse

Introduction to Data Engineering

Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.

IntermediateSkill Level

Over 3 hoursData EngineeringVincent VankrunkelsvenCourse

Understanding Modern Data Architecture

Discover modern data architectures key components, from ingestion and serving to governance and orchestration.

IntermediateSkill Level

2-3 hoursData EngineeringMiller TrujilloCourse

Hypothesis Testing in R

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

IntermediateSkill Level

Over 3 hoursProbability & StatisticsRichie CottonCourse

Working with Llama 3

Explore the latest techniques for running the Llama LLM locally and integrating it within your stack.

IntermediateSkill Level

2-3 hoursArtificial IntelligenceImtihan AhmedCourse

Vector Databases for Embeddings with Pinecone

Discover how the Pinecone vector database is revolutionizing AI application development!

IntermediateSkill Level

Over 3 hoursArtificial IntelligenceJames ChapmanCourse

Introduction to Deep Learning in Python

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.

IntermediateSkill Level

Over 3 hoursArtificial IntelligenceDan BeckerCourse

FAQs

Introduction to dbt

ETL and ELT in Python

Developing AI Systems with the OpenAI API

Hypothesis Testing in Python

Retrieval Augmented Generation (RAG) with LangChain

Data-Driven Decision Making in SQL

Introduction to Object-Oriented Programming in Python

Intermediate Deep Learning with PyTorch

Writing Functions in Python

Sampling in Python

Introduction to Kubernetes

Introduction to Embeddings with the OpenAI API

Containerization and Virtualization Concepts

Financial Modeling in Excel

Advanced Excel Functions

Preprocessing for Machine Learning in Python

Data Types in Python

Introduction to FastAPI

Working with Dates and Times in Python

Exploratory Data Analysis in R

Introduction to Natural Language Processing in Python

Introduction to Data Modeling in Snowflake

Designing Agentic Systems with LangChain

Analyzing Business Data in SQL

Introduction to Data Engineering

Understanding Modern Data Architecture

Hypothesis Testing in R

Working with Llama 3

Vector Databases for Embeddings with Pinecone

Introduction to Deep Learning in Python

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?