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771 Courses

Course

Market Basket Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 269 reviews

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

Machine Learning

4 hours

Course

Transactions and Error Handling in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 290 reviews

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

Software Development

4 hours

Course

Time Series Analysis in SQL Server

  • IntermediateSkill Level
  • 4.7+
  • 384 reviews

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

Data Manipulation

5 hours

Course

Bayesian Data Analysis in Python

  • IntermediateSkill Level
  • 4.7+
  • 261 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

Introduction to GCP

  • BasicSkill Level
  • 4.7+
  • 348 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

Introduction to AI Apps in Sigma

  • BasicSkill Level
  • 4.9+
  • 145 reviews

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

Reporting

2 hours

Course

Unsupervised Learning in R

  • IntermediateSkill Level
  • 4.7+
  • 105 reviews

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Machine Learning

4 hours

Course

Machine Learning for Finance in Python

  • IntermediateSkill Level
  • 4.8+
  • 213 reviews

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Machine Learning

4 hours

Course

Case Study: Analyzing Job Market Data in Tableau

  • BasicSkill Level
  • 4.7+
  • 564 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

RNA-Seq with Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 143 reviews

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

Probability & Statistics

4 hours

Course

Data Fluency

  • BasicSkill Level
  • 4.8+
  • 303 reviews

Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.

Data Literacy

2 hours

Course

Introduction to Portfolio Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 349 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

Fundamentals of Bayesian Data Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 219 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

Introduction to Network Analysis in Python

  • IntermediateSkill Level
  • 4.7+
  • 221 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

Supervised Learning in R: Regression

  • IntermediateSkill Level
  • 4.6+
  • 105 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

Manipulating Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 291 reviews

Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

Data Manipulation

4 hours

Course

Introduction to Python in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 147 reviews

Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.

Data Manipulation

3 hours

Course

Working with Dates and Times in R

  • IntermediateSkill Level
  • 4.8+
  • 94 reviews

Learn the essentials of parsing, manipulating and computing with dates and times in R.

Software Development

4 hours

Course

Introduction to Optimization in Python

  • IntermediateSkill Level
  • 4.7+
  • 200 reviews

Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Software Development

4 hours

Course

Multi-Modal Models with Hugging Face

  • IntermediateSkill Level
  • 4.8+
  • 173 reviews

Combine text, images, audio, and video with the latest AI models from Hugging Face, and generate new images and videos!

Artificial Intelligence

4 hours

Course

Supply Chain Analytics in Python

  • IntermediateSkill Level
  • 4.8+
  • 94 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+
  • 307 reviews

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

Data Visualization

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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