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341 Courses

Course

Marketing Analytics in Tableau

  • IntermediateSkill Level
  • 4.8+
  • 85 reviews

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

Data Preparation

6 hours

Course

Working with the OpenAI Responses API

  • IntermediateSkill Level
  • 4.8+
  • 60 reviews

Build smart, interactive, and reliable AI applications easier than ever before with the OpenAI Responses API and GPT-5.

Artificial Intelligence

3 hours

Course

Analyzing IoT Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 101 reviews

Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.

Data Manipulation

4 hours

Course

Importing Data in Java

  • IntermediateSkill Level
  • 4.8+
  • 53 reviews

Learn to import, manipulate, and transform data in Java using the Tablesaw library. Work with CSV files, tabular structures, and complex JSON formats.

Software Development

3 hours

Course

Python for R Users

  • IntermediateSkill Level
  • 4.7+
  • 78 reviews

This course is for R users who want to get up to speed with Python!

Software Development

5 hours

Course

Essential Google Cloud Infrastructure: Foundation

  • IntermediateSkill Level
  • 4.8+
  • 21 reviews

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

Cloud

4 hours 45 min

Course

Sentiment Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 95 reviews

Learn sentiment analysis by identifying positive and negative language, specific emotional intent and making compelling visualizations.

Machine Learning

4 hours

Course

Analyzing Social Media Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 32 reviews

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

Data Manipulation

4 hours

Course

Fraud Detection in R

  • IntermediateSkill Level
  • 4.7+
  • 36 reviews

Learn to detect fraud with analytics in R.

Machine Learning

4 hours

Course

End-to-End RAG with Weaviate

  • IntermediateSkill Level
  • 4.6+
  • 15 reviews

Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.

Artificial Intelligence

2 hours

Course

Credit Risk Modeling in R

  • IntermediateSkill Level
  • 4.7+
  • 81 reviews

Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.

Applied Finance

4 hours

Course

Visualizing Geospatial Data in R

  • IntermediateSkill Level
  • 4.5+
  • 86 reviews

Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.

Data Visualization

4 hours

Course

Building AI Agents with Haystack

  • IntermediateSkill Level
  • 4.8+
  • 39 reviews

Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.

Artificial Intelligence

1 hour 30 min

Course

Market Basket Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 83 reviews

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

Data Manipulation

4 hours

Course

Machine Learning in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 105 reviews

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Machine Learning

5 hours

Course

Case Study: Financial Analysis in KNIME

  • IntermediateSkill Level
  • 4.8+
  • 115 reviews

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

Applied Finance

3 hours

Course

Cleaning Data in Java

  • IntermediateSkill Level
  • 4.8+
  • 53 reviews

Master data cleaning in Java using statistical methods, transformations, and validation for reliable apps.

Importing & Cleaning Data

4 hours

Course

Time Series Analysis in PostgreSQL

  • IntermediateSkill Level
  • 4.8+
  • 92 reviews

Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.

Data Manipulation

4 hours

Course

Monitor and Troubleshoot Azure Solutions

  • IntermediateSkill Level
  • 4.7+
  • 58 reviews

Learn how to monitor, diagnose, and optimize Azure applications using Azure Monitor, Application Insights, and Log Analytics.

Cloud

3 hours

Course

Statistical Simulation in Python

  • IntermediateSkill Level
  • 4.8+
  • 28 reviews

Learn to solve increasingly complex problems using simulations to generate and analyze data.

Probability & Statistics

4 hours

Course

Analyzing Police Activity with pandas

  • IntermediateSkill Level
  • 4.8+
  • 25 reviews

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

Data Manipulation

4 hours

Course

Pandas Joins for Spreadsheet Users

  • IntermediateSkill Level
  • 4.7+
  • 53 reviews

Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.

Data Manipulation

4 hours

Course

Bond Valuation and Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 81 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

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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Make progress on the go with our mobile courses and daily 5-minute coding challenges.