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771 Courses

Course

Supervised Learning in R: Regression

  • IntermediateSkill Level
  • 4.6+
  • 101 reviews

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Machine Learning

4 hours

Course

Gen AI: Unlock Foundational Concepts

  • BasicSkill Level
  • 4.8+
  • 103 reviews

You unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI.

Cloud

1 hour 30 min

Course

Introduction to GCP

  • BasicSkill Level
  • 4.7+
  • 344 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

RNA-Seq with Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 141 reviews

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

Probability & Statistics

4 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

Transactions and Error Handling in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 281 reviews

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Software Development

4 hours

Course

Factor Analysis in R

  • AdvancedSkill Level
  • 4.7+
  • 156 reviews

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Probability & Statistics

4 hours

Course

Data Processing in Shell

  • IntermediateSkill Level
  • 4.8+
  • 503 reviews

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Data Manipulation

4 hours

Course

Introduction to AI Apps in Sigma

  • BasicSkill Level
  • 4.9+
  • 130 reviews

Build interactive AI apps in Sigma using user input, actions, and polished interfaces, no coding required.

Reporting

2 hours

Course

Introduction to Portfolio Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 341 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

Databricks with the Python SDK

  • AdvancedSkill Level
  • 4.7+
  • 81 reviews

Master Databricks with Python: learn to authenticate, manage clusters, automate jobs, and query AI models programmatically.

Artificial Intelligence

3 hours

Course

Data Strategy

  • BasicSkill Level
  • 4.7+
  • 1,747 reviews

Master strategic data management for business excellence.

Data Management

1 hour

Course

Introduction to Network Analysis in Python

  • IntermediateSkill Level
  • 4.7+
  • 215 reviews

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

Probability & Statistics

4 hours

Course

Anomaly Detection in Python

  • IntermediateSkill Level
  • 4.8+
  • 177 reviews

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

Probability & Statistics

4 hours

Course

Fine-Tuning with Llama 3

  • IntermediateSkill Level
  • 4.7+
  • 382 reviews

Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.

Artificial Intelligence

2 hours

Course

ARIMA Models in Python

  • AdvancedSkill Level
  • 4.8+
  • 400 reviews

Learn about ARIMA models in Python and become an expert in time series analysis.

Machine Learning

4 hours

Course

Demystifying Decision Science

  • BasicSkill Level
  • 4.8+
  • 271 reviews

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

Data Literacy

1 hour

Course

AI-Assisted Product Launch

  • BasicSkill Level
  • 4.7+
  • 348 reviews

Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.

Artificial Intelligence

1 hour

Course

Case Study: Analyzing Job Market Data in Tableau

  • BasicSkill Level
  • 4.7+
  • 551 reviews

In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

Data Visualization

3 hours

Course

Bayesian Data Analysis in Python

  • IntermediateSkill Level
  • 4.7+
  • 256 reviews

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

Probability & Statistics

4 hours

Course

Fundamentals of Bayesian Data Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 212 reviews

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

Probability & Statistics

4 hours

Course

String Manipulation with stringr in R

  • IntermediateSkill Level
  • 4.7+
  • 51 reviews

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

Software Development

4 hours

Course

Supply Chain Analytics in Python

  • IntermediateSkill Level
  • 4.8+
  • 91 reviews

Leverage the power of Python and PuLP to optimize supply chains.

Exploratory Data Analysis

4 hours

Course

Improving Your Data Visualizations in Python

  • IntermediateSkill Level
  • 4.7+
  • 293 reviews

Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.

Data Visualization

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

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.

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