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729 Courses

Course

Spoken Language Processing in Python

  • AdvancedSkill Level
  • 4.8+
  • 260 reviews

Learn how to load, transform, and transcribe speech from raw audio files in Python.

Data Manipulation

4 hours

Course

Introduction to Portfolio Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 335 reviews

Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.

Applied Finance

4 hours

Course

Financial Analytics in Google Sheets

  • BasicSkill Level
  • 4.7+
  • 123 reviews

Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.

Applied Finance

4 hours

Course

Cluster Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 69 reviews

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Machine Learning

4 hours

Course

Introduction to GCP

  • BasicSkill Level
  • 4.7+
  • 336 reviews

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

Cloud

2 hours

Course

Graph RAG with LangChain and Neo4j

  • AdvancedSkill Level
  • 4.7+
  • 98 reviews

Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.

Artificial Intelligence

3 hours

Course

Machine Learning with caret in R

  • IntermediateSkill Level
  • 4.8+
  • 42 reviews

This course teaches the big ideas in machine learning like how to build and evaluate predictive models.

Machine Learning

4 hours

Course

Dealing With Missing Data in R

  • BasicSkill Level
  • 4.7+
  • 135 reviews

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Data Preparation

4 hours

Course

Foundations of PySpark

  • IntermediateSkill Level
  • 4.7+
  • 601 reviews

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

Data Engineering

4 hours

Course

Data Modeling in Sigma

  • BasicSkill Level
  • 4.9+
  • 91 reviews

Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.

Reporting

2 hours

Course

Case Study: Analyzing Job Market Data in Power BI

  • BasicSkill Level
  • 4.8+
  • 318 reviews

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

Data Manipulation

4 hours

Course

Visualizing Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 175 reviews

Learn how to visualize time series in R, then practice with a stock-picking case study.

Data Visualization

4 hours

Course

Fully Automated MLOps

  • IntermediateSkill Level
  • 4.8+
  • 322 reviews

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Machine Learning

4 hours

Course

Introduction to Testing in Java

  • AdvancedSkill Level
  • 4.8+
  • 153 reviews

Learn how to write effective tests in Java using JUnit and Mockito to build robust, reliable applications with confidence.

Software Development

3 hours

Course

Snowflake Management, Governance & Collaboration

  • BasicSkill Level
  • 4.8+
  • 65 reviews

Learn to secure, govern, and manage Snowflake at scale. Cover RBAC, data masking, cost monitoring, Time Travel, and secure data sharing.

Data Management

3 hours

Course

Recommending Skincare Products

  • BasicSkill Level
  • 4.7+
  • 271 reviews

Test a chatbot that matches customers with ideal skincare products using your prompting skills for personalized results.

Artificial Intelligence

1 hour

Course

Demystifying Decision Science

  • BasicSkill Level
  • 4.8+
  • 265 reviews

Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions.

Data Literacy

1 hour

Course

Calculations in Sigma

  • BasicSkill Level
  • 4.9+
  • 139 reviews

Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.

Data Manipulation

2 hours

Course

Multi-Modal Systems with the OpenAI API

  • IntermediateSkill Level
  • 4.8+
  • 437 reviews

Create multi-modal systems using OpenAIs text and audio models, including an end-to-end customer support chatbot!

Artificial Intelligence

2 hours

Course

RNA-Seq with Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 138 reviews

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Probability & Statistics

4 hours

Course

Introduction to AWS Boto in Python

  • IntermediateSkill Level
  • 4.8+
  • 206 reviews

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

Cloud

4 hours

Course

Streaming Concepts

  • BasicSkill Level
  • 4.7+
  • 480 reviews

Learn about the difference between batching and streaming, scaling streaming systems, and real-world applications.

Data Engineering

2 hours

Course

Ensemble Methods in Python

  • AdvancedSkill Level
  • 4.8+
  • 388 reviews

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Machine Learning

4 hours

Course

Corporate Finance Fundamentals

  • BasicSkill Level
  • 4.8+
  • 219 reviews

Learn key financial concepts such as capital investment, WACC, and shareholder value.

Applied Finance

2 hours

Course

Monitoring Machine Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 344 reviews

This course covers everything you need to know to build a basic machine learning monitoring system in Python

Machine Learning

3 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.