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779 Courses

Course

Fully Automated MLOps

  • IntermediateSkill Level
  • 4.8+
  • 376 reviews

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Machine Learning

4 hours

Course

AI Agents with Hugging Face smolagents

  • AdvancedSkill Level
  • 4.8+
  • 262 reviews

Learn how to build intelligent agents that reason, act, and solve real-world tasks using Python.

Artificial Intelligence

3 hours

Course

Hyperparameter Tuning in Python

  • IntermediateSkill Level
  • 4.8+
  • 861 reviews

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

Machine Learning

4 hours

Course

Building AI Agents with Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 32 reviews

Build autonomous Cortex Agents in Snowflake that query structured and unstructured data, then deploy and monitor them.

Artificial Intelligence

4 hours

Course

Natural Language Processing with spaCy

  • IntermediateSkill Level
  • 4.7+
  • 640 reviews

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

Machine Learning

4 hours

Course

Gen AI: Navigate the Landscape

  • BasicSkill Level
  • 4.8+
  • 162 reviews

You explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.

Cloud

1 hour 15 min

Course

Feature Engineering for NLP in Python

  • IntermediateSkill Level
  • 4.8+
  • 151 reviews

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

Machine Learning

4 hours

Course

Visualizations in Sigma

  • BasicSkill Level
  • 4.8+
  • 234 reviews

Learn to build and customize Sigma charts to tell clear, compelling data stories—no coding required.

Data Visualization

2 hours

Course

Introduction to AWS Boto in Python

  • IntermediateSkill Level
  • 4.8+
  • 226 reviews

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

Cloud

4 hours

Course

Multi-Modal Systems with the OpenAI API

  • IntermediateSkill Level
  • 4.8+
  • 488 reviews

Create multi-modal systems using OpenAIs text and audio models, including an end-to-end customer support chatbot!

Artificial Intelligence

2 hours

Course

Quantitative Risk Management in Python

  • AdvancedSkill Level
  • 4.8+
  • 233 reviews

Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.

Applied Finance

4 hours

Course

Fraud Detection in Python

  • IntermediateSkill Level
  • 4.7+
  • 198 reviews

Learn how to detect fraud using Python.

Machine Learning

4 hours

Course

Machine Learning with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 734 reviews

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

Machine Learning

4 hours

Course

Intermediate Importing Data in R

  • IntermediateSkill Level
  • 4.8+
  • 288 reviews

Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.

Data Preparation

3 hours

Course

Statistical Thinking in Python (Part 1)

  • IntermediateSkill Level
  • 4.8+
  • 115 reviews

Build the foundation you need to think statistically and to speak the language of your data.

Probability & Statistics

3 hours

Course

Calculations in Tableau

  • AdvancedSkill Level
  • 4.7+
  • 697 reviews

In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!

Data Visualization

6 hours

Course

Data Strategy

  • BasicSkill Level
  • 4.7+
  • 1,787 reviews

Master strategic data management for business excellence.

Data Management

1 hour

Course

Power BI for End Users

  • BasicSkill Level
  • 4.7+
  • 339 reviews

Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.

Reporting

1 hour

Course

Serverless Applications with AWS Lambda

  • IntermediateSkill Level
  • 4.7+
  • 40 reviews

Build, deploy, and optimize serverless apps with AWS Lambda. Master event processing, error handling, concurrency, and safe deployments in a live AWS Console.

Cloud

3 hours

Course

Azure Compute Solutions

  • IntermediateSkill Level
  • 4.7+
  • 170 reviews

Learn how containers work in Azure, including registries, ACI, AKS basics, scaling, monitoring, and troubleshooting.

Cloud

3 hours

Course

Google: Build and Deploy Agents in Production

  • IntermediateSkill Level
  • 4.7+
  • 65 reviews

Explore multi-agent system architecture and deployment using Googles ADK and Google Cloud infrastructure for production-grade agent applications.

Cloud

30 min

Course

Monitoring Machine Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 388 reviews

This course covers everything you need to know to build a basic machine learning monitoring system in Python

Machine Learning

3 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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