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722 Courses

Course

ChIP-seq with Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 48 reviews

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

Probability & Statistics

4 hours

Course

Getting Started with Google Kubernetes Engine

  • IntermediateSkill Level
  • 4.8+
  • 16 reviews

The goal of this course is to introduce the basics of Google Kubernetes Engine, or GKE, and how to get applications containerized and running in Google Cloud.

Cloud

5 hours 15 min

Course

Bayesian Regression Modeling with rstanarm

  • AdvancedSkill Level
  • 4.8+
  • 63 reviews

Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.

Probability & Statistics

4 hours

Course

Introduction to Data Engineering on Google Cloud

  • BasicSkill Level
  • 4.7+
  • 8 reviews

Learn the data engineering role on Google Cloud. Explore data sources, storage solutions, ETL/ELT architectures, BigQuery, Dataform, and Dataproc.

Cloud

3 hours 41 min

Course

Bond Valuation and Analysis in Python

  • BasicSkill Level
  • 4.8+
  • 67 reviews

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

Applied Finance

4 hours

Course

Case Study: Inventory Analysis in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 54 reviews

Enhance your Tableau skills with this case study on inventory analysis. Analyze a dataset, create calculated fields, and create visualizations.

Data Visualization

2 hours

Course

Building Dashboards with flexdashboard

  • IntermediateSkill Level
  • 4.7+
  • 49 reviews

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

Reporting

4 hours

Course

Google DeepMind: Fine-Tune Your Model

  • IntermediateSkill Level
  • 4.7+
  • 12 reviews

Unleash the power of language models with fine-tuning. In this course, you will learn how to adjust a pre-trained model to a specific task.

Cloud

8 hours

Course

DataLab with SQL

  • BasicSkill Level
  • 4.8+
  • 41 reviews

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

Reporting

1 hour

Course

Intermediate Network Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 76 reviews

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

Probability & Statistics

4 hours

Course

Financial Trading in R

  • IntermediateSkill Level
  • 4.8+
  • 72 reviews

This course covers the basics of financial trading and how to use quantstrat to build signal-based trading strategies.

Applied Finance

5 hours

Course

Case Study: Analyzing Fitness Data in Alteryx

  • IntermediateSkill Level
  • 4.8+
  • 54 reviews

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

Data Preparation

3 hours

Course

Intermediate Julia

  • BasicSkill Level
  • 4.7+
  • 79 reviews

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

Software Development

4 hours

Course

Analyzing Survey Data in Python

  • IntermediateSkill Level
  • 4.6+
  • 50 reviews

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

Probability & Statistics

4 hours

Course

Google Cloud Fundamentals: Core Infrastructure

  • BasicSkill Level
  • 4.8+
  • 6 reviews

Learn Google Cloud essentials including computing, storage, networking, and resource management through videos and hands-on labs in this foundational course.

Cloud

3 hours

Course

Life Insurance Products Valuation in R

  • BasicSkill Level
  • 4.8+
  • 47 reviews

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

Applied Finance

4 hours

Course

Equity Valuation in R

  • IntermediateSkill Level
  • 4.8+
  • 62 reviews

Learn the fundamentals of valuing stocks.

Applied Finance

4 hours

Course

Programming with dplyr

  • IntermediateSkill Level
  • 4.7+
  • 47 reviews

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

Data Manipulation

4 hours

Course

Interactive Data Visualization with Bokeh

  • IntermediateSkill Level
  • 4.7+
  • 40 reviews

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

Data Visualization

4 hours

Course

Intermediate Regular Expressions in R

  • IntermediateSkill Level
  • 4.8+
  • 33 reviews

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

Software Development

4 hours

Course

Google Workspace End User: Gmail

  • BasicSkill Level
  • 4.7+
  • 13 reviews

Learn to compose, send, and manage email in Gmail, organize messages with labels, and configure settings like filters and signatures.

Cloud

7 hours 15 min

Course

Defensive R Programming

  • IntermediateSkill Level
  • 4.9+
  • 71 reviews

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

Software Development

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.

Grow your data skills with DataCamp for Mobile

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