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294 Courses

Course

Introduction to BigQuery

  • IntermediateSkill Level
  • 4.8+
  • 420 reviews

Unlock BigQuerys power: grasp its fundamentals, execute queries, and optimize workflows for efficient data analysis.

Data Engineering

4 hours

Course

Intermediate SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 223 reviews

In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.

Software Development

4 hours

Course

Experimental Design in R

  • IntermediateSkill Level
  • 4.7+
  • 309 reviews

In this course youll learn about basic experimental design, a crucial part of any data analysis.

Probability & Statistics

4 hours

Course

Anomaly Detection in Python

  • IntermediateSkill Level
  • 4.8+
  • 171 reviews

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Probability & Statistics

4 hours

Course

Introduction to DataLab

  • BasicSkill Level
  • 4.8+
  • 106 reviews

Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.

Reporting

1 hour

Course

Parallel Programming in R

  • IntermediateSkill Level
  • 4.7+
  • 71 reviews

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

Software Development

4 hours

Course

Cleaning Data in Java

  • IntermediateSkill Level
  • 4.8+
  • 53 reviews

Master data cleaning in Java using statistical methods, transformations, and validation for reliable apps.

Importing & Cleaning Data

4 hours

Course

String Manipulation with stringr in R

  • IntermediateSkill Level
  • 4.7+
  • 48 reviews

Learn how to pull character strings apart, put them back together and use the stringr package.

Software Development

4 hours

Course

Data Transformation with Polars

  • IntermediateSkill Level
  • 4.9+
  • 30 reviews

Take Polars further with text manipulation, rolling statistics, DataFrame joins, and advanced analytics.

Data Manipulation

4 hours

Course

Data Manipulation in SQL

  • BasicSkill Level
  • 4.8+
  • 2,496 reviews

Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.

Data Manipulation

4 hours

Course

Data Manipulation in Snowflake

  • BasicSkill Level
  • 4.8+
  • 938 reviews

Master data manipulation and analysis techniques such as CASE statements, subqueries, and CTEs in Snowflake.

Data Manipulation

2 hours

Course

Introduction to R for Finance

  • BasicSkill Level
  • 4.7+
  • 93 reviews

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

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

Visualizations in Sigma

  • BasicSkill Level
  • 4.8+
  • 169 reviews

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

Data Visualization

2 hours

Course

Business Process Analytics in R

  • IntermediateSkill Level
  • 4.8+
  • 42 reviews

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

Reporting

4 hours

Course

Data Preparation in Alteryx

  • BasicSkill Level
  • 4.8+
  • 1,040 reviews

Master data preparation, cleaning, and analysis in Alteryx Designer, whether you are a new or seasoned analyst.

Data Preparation

3 hours

Course

Introduction to KNIME

  • BasicSkill Level
  • 4.8+
  • 524 reviews

Learn to use the KNIME Analytics Platform for data access, cleaning, and analysis with a no-code/low-code approach.

Data Preparation

3 hours

Course

Connecting Data in Tableau

  • BasicSkill Level
  • 4.8+
  • 1,084 reviews

Learn to connect Tableau to different data sources and prepare the data for a smooth analysis.

Data Preparation

3 hours

Course

Case Study: Mortgage Trading Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 269 reviews

In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.

Applied Finance

3 hours

Course

Data Preparation in Power BI

  • BasicSkill Level
  • 4.8+
  • 7,676 reviews

In this interactive Power BI course, you’ll learn how to use Power Query Editor to transform and shape your data to be ready for analysis.

Data Preparation

3 hours

Course

Introduction to Python for Finance

  • BasicSkill Level
  • 4.8+
  • 442 reviews

Build Python skills to elevate your finance career. Learn how to work with lists, arrays and data visualizations to master financial analyses.

Applied Finance

4 hours

Course

Analyzing Social Media Data in R

  • IntermediateSkill Level
  • 4.8+
  • 84 reviews

Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.

Data Manipulation

4 hours

Course

Market Basket Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 256 reviews

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

Machine Learning

4 hours

Course

Case Study: Financial Analysis in KNIME

  • IntermediateSkill Level
  • 4.8+
  • 115 reviews

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.

Applied Finance

3 hours

Course

Time Series Analysis in SQL Server

  • IntermediateSkill Level
  • 4.7+
  • 360 reviews

Explore ways to work with date and time data in SQL Server for time series analysis

Data Manipulation

5 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.

Grow your data skills with DataCamp for Mobile

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