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775 Courses

Course

Programming with dplyr

  • IntermediateSkill Level
  • 4.7+
  • 51 reviews

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

Data Manipulation

4 hours

Course

Time Series Analysis in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 161 reviews

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Data Visualization

2 hours

Course

Production Machine Learning Systems

  • IntermediateSkill Level
  • 5
  • 10 reviews

Learn how to implement the various flavors of ML: static, dynamic, and continuous training; static and dynamic inference; and batch and online processing.

Cloud

16 hours

Course

Google Workspace End User: Gmail

  • BasicSkill Level
  • 4.8+
  • 29 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

Intermediate Network Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 84 reviews

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

Probability & Statistics

4 hours

Course

Build Data Lakes and Data Warehouses on Google Cloud

  • IntermediateSkill Level
  • 4.8+
  • 23 reviews

Build modern data lakehouses on Google Cloud using BigQuery, Cloud Storage, Apache Iceberg, BigLake, federated queries, and data governance tools.

Cloud

3 hours 48 min

Course

Planning a Product Launch with Claude Cowork

  • IntermediateSkill Level
  • 4.5+
  • 10 reviews

Tired of launch week chaos? Plan and write a full product launch in a single session with Claude Cowork.

Artificial Intelligence

15 min

Course

Bond Valuation and Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 89 reviews

Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.

Applied Finance

4 hours

Course

Financial Trading in R

  • IntermediateSkill Level
  • 4.8+
  • 78 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

Introduction to Gemini Enterprise

  • BasicSkill Level
  • 4.9+
  • 15 reviews

Gemini Enteprise brings together AI agents, enterprise search, NotebookLM, and intelligent data access to solve organizational challenges.

Cloud

2 hours 15 min

Course

Analyzing Survey Data in Python

  • IntermediateSkill Level
  • 4.6+
  • 55 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

Case Study: Financial Analysis in KNIME

  • IntermediateSkill Level
  • 4.8+
  • 121 reviews

Apply financial analysis in KNIME with real-world data, enhancing data preparation and workflow skills.

Applied Finance

3 hours

Course

Working with DeepSeek in Python

  • BasicSkill Level
  • 4.7+
  • 106 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 Infrastructure: Cloud GPUs

  • IntermediateSkill Level
  • 5
  • 16 reviews

Well explore how CPUs, GPUs, and TPUs make AI tasks super fast, what makes each one unique, and how AI software gets the most out of them.

Cloud

1 hour

Course

Data Manipulation in KNIME

  • BasicSkill Level
  • 4.8+
  • 254 reviews

Automate data manipulation with KNIME, mastering merging, aggregation, database workflows, and advanced file handling.

Data Manipulation

3 hours

Course

Market Basket Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 95 reviews

Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.

Data Manipulation

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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