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778 Courses

Course

Data Privacy and Anonymization in Python

  • AdvancedSkill Level
  • 4.8+
  • 52 reviews

Learn to process sensitive information with privacy-preserving techniques.

Machine Learning

4 hours

Course

Google: Add Agent Capabilities With Tools

  • IntermediateSkill Level
  • 4.7+
  • 24 reviews

Equip AI agents with tools for web search, code execution, database queries, and custom actions. Transform agents into capable assistants.

Cloud

3 hours

Course

Network Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 123 reviews

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Probability & Statistics

4 hours

Course

Case Study: Financial Analysis in KNIME

  • IntermediateSkill Level
  • 4.8+
  • 119 reviews

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

Applied Finance

3 hours

Course

Introduction to Security Principles in Cloud Computing

  • IntermediateSkill Level
  • 4.8+
  • 6 reviews

In this course, you’ll explore the essentials of cybersecurity, including the security lifecycle, digital transformation, and key cloud computing concepts.

Cloud

18 hours 15 min

Course

Intermediate Network Analysis in Python

  • AdvancedSkill Level
  • 4.8+
  • 83 reviews

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

Probability & Statistics

4 hours

Course

Data Visualization in KNIME

  • BasicSkill Level
  • 4.8+
  • 201 reviews

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Data Visualization

2 hours

Course

Programming with dplyr

  • IntermediateSkill Level
  • 4.8+
  • 50 reviews

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

Data Manipulation

4 hours

Course

Working with DeepSeek in Python

  • BasicSkill Level
  • 4.7+
  • 105 reviews

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

Artificial Intelligence

3 hours

Course

Monitoring and Troubleshooting AWS

  • IntermediateSkill Level
  • 4.8+
  • 10 reviews

Monitor and troubleshoot AWS apps with Amazon CloudWatch and AWS X-Ray. Collect metrics and logs, build dashboards, set alarms, and trace requests.

Cloud

3 hours

Course

Fraud Detection in R

  • IntermediateSkill Level
  • 4.7+
  • 38 reviews

Learn to detect fraud with analytics in R.

Machine Learning

4 hours

Course

Feature Engineering in R

  • IntermediateSkill Level
  • 4.7+
  • 152 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

Logging and Monitoring in Google Cloud

  • BasicSkill Level
  • 4.9+
  • 25 reviews

This course, Logging and Monitoring in Google Cloud, covers the operations-focused components including Logging, Monitoring, and Service Monitoring.

Cloud

5 hours 15 min

Course

Bond Valuation and Analysis in Python

  • BasicSkill Level
  • 4.8+
  • 72 reviews

Learn how bonds work and how to price them and assess some of their risks using the numpy and numpy-financial packages.

Applied Finance

4 hours

Course

Financial Trading in R

  • IntermediateSkill Level
  • 4.8+
  • 77 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 Spark with sparklyr in R

  • IntermediateSkill Level
  • 4.7+
  • 82 reviews

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

Data Engineering

4 hours

Course

Data Manipulation in KNIME

  • BasicSkill Level
  • 4.8+
  • 249 reviews

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

Data Manipulation

3 hours

Course

Google DeepMind: Accelerate Your Model

  • IntermediateSkill Level
  • 4.9+
  • 24 reviews

Train more powerful models with a single GPU, learn how hardware can speed up model training and the key considerations when training models on a GPU.

Cloud

7 hours

Course

Automating Deployments on AWS

  • IntermediateSkill Level
  • 5
  • 7 reviews

Build CI/CD pipelines with AWS CodePipeline, CodeBuild, and CodeDeploy. Automate blue/green and canary releases, and define infrastructure with CloudFormation.

Cloud

3 hours

Course

Bayesian Regression Modeling with rstanarm

  • AdvancedSkill Level
  • 4.8+
  • 70 reviews

Learn how to leverage Bayesian estimation methods to make better inferences about linear regression models.

Probability & Statistics

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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