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 | DataCamp

Data, AI, and Cloud Courses

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619 Courses

Course

Nonlinear Modeling with Generalized Additive Models (GAMs) in R

IntermediateSkill Level
4.7+
105

GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.

Probability & Statistics

Course

Life Insurance Products Valuation in R

BasicSkill Level
4.7+
104

Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.

Applied Finance

Course

HR Analytics: Predicting Employee Churn in Python

IntermediateSkill Level
4.5+
102

In this course youll learn how to apply machine learning in the HR domain.

Machine Learning

Course

Intermediate Network Analysis in Python

AdvancedSkill Level
4.6+
101

Analyze time series graphs, use bipartite graphs, and gain the skills to tackle advanced problems in network analytics.

Probability & Statistics

Course

Building Dashboards with flexdashboard

IntermediateSkill Level
4.3+
101

In this course youll learn how to create static and interactive dashboards using flexdashboard and shiny.

Reporting

Course

Case Study: Net Revenue Management in Google Sheets

IntermediateSkill Level
4.2+
101

You will use Net Revenue Management techniques in Google Sheets for a Fast Moving Consumer Goods company.

Applied Finance

Course

Pandas Joins for Spreadsheet Users

IntermediateSkill Level
4.4+
99

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

Data Manipulation

Course

Building Response Models in R

IntermediateSkill Level
4.5+
97

Learn to build simple models of market response to increase the effectiveness of your marketing plans.

Probability & Statistics

Course

Business Process Analytics in R

IntermediateSkill Level
4.3+
97

Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.

Reporting

Course

DataLab with SQL

BasicSkill Level
4.7+
94

Elevate your analysis with this hands-on course using SQL with DataLab workbooks.

Reporting

Course

Fraud Detection in R

IntermediateSkill Level
4.3+
94

Learn to detect fraud with analytics in R.

Machine Learning

Course

Defensive R Programming

IntermediateSkill Level
4.7+
91

Learn defensive programming in R to make your code more robust.

Software Development

Course

Programming with dplyr

IntermediateSkill Level
4.7+
88

Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.

Data Manipulation

Course

Equity Valuation in R

IntermediateSkill Level
4.9+
86

Learn the fundamentals of valuing stocks.

Applied Finance

Course

Importing Data in Java

IntermediateSkill Level
4.9+
84

Learn to import, manipulate, and transform data in Java using the Tablesaw library. Work with CSV files, tabular structures, and complex JSON formats.

Software Development

Course

Machine Translation with Keras

AdvancedSkill Level
4.7+
83

Are you curious about the inner workings of the models that are behind products like Google Translate?

Artificial Intelligence

Course

Interactive Data Visualization with Bokeh

IntermediateSkill Level
4.5+
83

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

Data Visualization

Course

Intermediate Julia

BasicSkill Level
4.7+
82

Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.

Software Development

Course

Querying a PostgreSQL Database in Java

AdvancedSkill Level
4.9+
81

Connect Java to PostgreSQL with JDBC. Write secure queries, manage transactions, and handle large datasets efficiently.

Software Development

Course

Case Study: Analyzing Fitness Data in Alteryx

IntermediateSkill Level
4.7+
81

Advance your Alteryx skills with real fitness data to develop targeted marketing strategies and innovative products!

Data Preparation

Course

Sentiment Analysis in R

IntermediateSkill Level
4.4+
80

Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

Machine Learning

Course

Multivariate Probability Distributions in R

IntermediateSkill Level
4.7+
78

Learn to analyze, plot, and model multivariate data.

Probability & Statistics

Course

Azure Compute Solutions

IntermediateSkill Level
4.7+
77

Learn how containers work in Azure, including registries, ACI, AKS basics, scaling, monitoring, and troubleshooting.

Cloud

Course

Develop for Azure Storage

IntermediateSkill Level
4.5+
77

Learn how to store, secure, scale, and process data in Azure using Blob Storage, Cosmos DB, queues, and event-driven services.

Cloud

Course

Bayesian Modeling with RJAGS

AdvancedSkill Level
4.8+
75

In this course, youll learn how to implement more advanced Bayesian models using RJAGS.

Probability & Statistics

Course

Choice Modeling for Marketing in R

AdvancedSkill Level
4.3+
75

Learn to analyze and model customer choice data in R.

Probability & Statistics

Course

ChIP-seq with Bioconductor in R

IntermediateSkill Level
4.5+
73

Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.

Probability & Statistics

Course

Probability Puzzles in R

BasicSkill Level
4.7+
72

Learn strategies for answering probability questions in R by solving a variety of probability puzzles.

Probability & Statistics

Course

Intermediate Regular Expressions in R

IntermediateSkill Level
4.8+
70

Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.

Software Development

Course

Parallel Programming in R

IntermediateSkill Level
4.8+
68

Unlock the power of parallel computing in R. Enhance your data analysis skills, speed up computations, and process large datasets effortlessly.

Software Development

Browse Courses

Nonlinear Modeling with Generalized Additive Models (GAMs) in R

Life Insurance Products Valuation in R

HR Analytics: Predicting Employee Churn in Python

Intermediate Network Analysis in Python

Building Dashboards with flexdashboard

Case Study: Net Revenue Management in Google Sheets

Pandas Joins for Spreadsheet Users

Building Response Models in R

Business Process Analytics in R

DataLab with SQL

Fraud Detection in R

Defensive R Programming

Programming with dplyr

Equity Valuation in R

Importing Data in Java

Machine Translation with Keras

Interactive Data Visualization with Bokeh

Intermediate Julia

Querying a PostgreSQL Database in Java

Case Study: Analyzing Fitness Data in Alteryx

Sentiment Analysis in R

Multivariate Probability Distributions in R

Azure Compute Solutions

Develop for Azure Storage

Bayesian Modeling with RJAGS

Choice Modeling for Marketing in R

ChIP-seq with Bioconductor in R

Probability Puzzles in R

Intermediate Regular Expressions in R

Parallel Programming in R

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?