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722 Courses

Course

Intermediate Portfolio Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 68 reviews

Advance you R finance skills to backtest, analyze, and optimize financial portfolios.

Applied Finance

5 hours

Course

Python for MATLAB Users

  • BasicSkill Level
  • 4.7+
  • 28 reviews

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

Software Development

4 hours

Course

Case Studies in Statistical Thinking

  • IntermediateSkill Level
  • 4.9+
  • 79 reviews

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Probability & Statistics

4 hours

Course

Dimensionality Reduction in R

  • BasicSkill Level
  • 4.7+
  • 93 reviews

Learn dimensionality reduction techniques in R and master feature selection and extraction for your own data and models.

Machine Learning

4 hours

Course

Parallel Programming with Dask in Python

  • IntermediateSkill Level
  • 4.8+
  • 62 reviews

Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.

Software Development

4 hours

Course

Support Vector Machines in R

  • IntermediateSkill Level
  • 4.8+
  • 80 reviews

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

Machine Learning

4 hours

Course

Analyzing US Census Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 60 reviews

Learn to use the Census API to work with demographic and socioeconomic data.

Exploratory Data Analysis

5 hours

Course

Feature Engineering in R

  • IntermediateSkill Level
  • 4.7+
  • 139 reviews

Learn the principles of feature engineering for machine learning models and how to implement them using the R tidymodels framework.

Machine Learning

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

Advanced NLP with spaCy

  • IntermediateSkill Level
  • 4.6+
  • 20 reviews

Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.

Machine Learning

5 hours

Course

Working with DeepSeek in Python

  • BasicSkill Level
  • 4.7+
  • 96 reviews

Discover what all of the DeepSeek hype was really about! Build applications using DeepSeeks R1 and V3 models.

Artificial Intelligence

3 hours

Course

AI for Data Analysts

  • IntermediateSkill Level
  • 4.8+
  • 9 reviews

Use AI across every stage of your data analysis. Write sharper prompts, audit data quality, find insights worth chasing, and ship work you can trust.

Artificial Intelligence

4 hours

Course

Loan Amortization in Google Sheets

  • IntermediateSkill Level
  • 4.7+
  • 45 reviews

Learn how to build an amortization dashboard in Google Sheets with financial and conditional formulas.

Applied Finance

4 hours

Course

R For SAS Users

  • BasicSkill Level
  • 4.7+
  • 27 reviews

Learn how to translate your SAS knowledge into R and analyze data using this free and powerful software language.

Software Development

4 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

Google: Agent Fundamentals

  • BasicSkill Level
  • 4.8+
  • 15 reviews

Learn AI agent fundamentals — how they differ from LLMs, when to use them, and explore agent architecture, orchestration, and tools.

Cloud

1 hour

Course

Practicing Statistics Interview Questions in R

  • AdvancedSkill Level
  • 4.7+
  • 19 reviews

In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.

Probability & Statistics

4 hours

Course

Conditional Formatting in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 90 reviews

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

Data Manipulation

2 hours

Course

Case Study: Supply Chain Analytics in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 63 reviews

Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.

Data Visualization

4 hours

Course

Essential Google Cloud Infrastructure: Core Services

  • IntermediateSkill Level
  • 4.9+
  • 16 reviews

This course introduces the comprehensive and flexible infrastructure and platform services provided by Google Cloud with a focus on Core Services.

Cloud

4 hours 15 min

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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