Course
Introduction to GCP
- BasicSkill Level
- 4.7+
- 374 reviews
Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.
Cloud
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781 Courses
Cloud
Course
Developing Applications on AWS
- IntermediateSkill Level
- 4.9+
- 38 reviews
Build cloud apps on AWS with API Gateway, Lambda, SQS, SNS, EventBridge, and Kinesis. Master serverless and event-driven patterns for the DVA-C02 exam.
Cloud
Course
Building and Optimizing Triggers in SQL Server
- IntermediateSkill Level
- 4.8+
- 319 reviews
Learn how to design and implement triggers in SQL Server using real-world examples.
Software Development
Course
Introduction to Bioconductor in R
- IntermediateSkill Level
- 4.7+
- 135 reviews
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!
Probability & Statistics
Course
Multi-Modal Models with Hugging Face
- IntermediateSkill Level
- 4.8+
- 199 reviews
Combine text, images, audio, and video with the latest AI models from Hugging Face, and generate new images and videos!
Artificial Intelligence
Course
Importing Data in Java
- IntermediateSkill Level
- 4.7+
- 135 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
Course
Apache Iceberg: From Zero to Production Data Lakehouse
- IntermediateSkill Level
- 4.7+
- 35 reviews
Build production-ready Apache Iceberg lakehouses: model, migrate, and maintain tables at scale.
Data Engineering
Course
Introduction to MongoDB in Python
- IntermediateSkill Level
- 4.7+
- 407 reviews
Learn to manipulate and analyze flexibly structured data with MongoDB.
Data Engineering
Course
Software Development with Windsurf
- IntermediateSkill Level
- 4.8+
- 509 reviews
Boost your coding with Windsurf, the AI-powered IDE that helps you build, debug, and deploy faster.
Artificial Intelligence
Course
Cleaning Data in Java
- IntermediateSkill Level
- 4.7+
- 131 reviews
Master data cleaning in Java using statistical methods, transformations, and validation for reliable apps.
Importing & Cleaning Data
Course
Develop Azure Event-based and Message-based Solutions
- IntermediateSkill Level
- 4.7+
- 145 reviews
Learn to design scalable event-driven architectures in Azure using messaging services and real-world integrations.
Cloud
Course
Google: Agent Fundamentals
- BasicSkill Level
- 4.8+
- 128 reviews
Learn AI agent fundamentals — how they differ from LLMs, when to use them, and explore agent architecture, orchestration, and tools.
Cloud
Course
Foundations of PySpark
- IntermediateSkill Level
- 4.7+
- 649 reviews
Learn to implement distributed data management and machine learning in Spark using the PySpark package.
Data Engineering
Course
Monitor and Troubleshoot Azure Solutions
- IntermediateSkill Level
- 4.7+
- 144 reviews
Learn how to monitor, diagnose, and optimize Azure applications using Azure Monitor, Application Insights, and Log Analytics.
Cloud
Course
Building Web Applications with Shiny in R
- IntermediateSkill Level
- 4.7+
- 231 reviews
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.
Software Development
Course
Introduction to TensorFlow in Python
- IntermediateSkill Level
- 4.8+
- 58 reviews
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
Machine Learning
Course
Introduction to AI Apps in Sigma
- BasicSkill Level
- 4.8+
- 212 reviews
Build interactive AI apps in Sigma using user input, actions, and polished interfaces, no coding required.
Reporting
Course
Building AI Agent Harnesses with Strands Agents
- IntermediateSkill Level
- 4.7+
- 33 reviews
Building AI Agent Harnesses with Strands Agents
Artificial Intelligence
Course
Data Modeling in Sigma
- BasicSkill Level
- 4.8+
- 159 reviews
Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.
Reporting
Course
Inference for Linear Regression in R
- AdvancedSkill Level
- 4.8+
- 187 reviews
In this course youll learn how to perform inference using linear models.
Probability & Statistics
Course
ARIMA Models in Python
- AdvancedSkill Level
- 4.8+
- 439 reviews
Learn about ARIMA models in Python and become an expert in time series analysis.
Machine Learning
Course
Case Study: Analyzing Job Market Data in Tableau
- BasicSkill Level
- 4.7+
- 627 reviews
In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.
Data Visualization
Course
Introduction to Python in Power BI
- IntermediateSkill Level
- 4.8+
- 170 reviews
Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.
Data Manipulation
Course
Bayesian Data Analysis in Python
- IntermediateSkill Level
- 4.7+
- 279 reviews
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!
Probability & Statistics
Course
Calculations in Sigma
- BasicSkill Level
- 4.8+
- 230 reviews
Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.
Data Manipulation
Course
Introduction to Generative AI in Snowflake
- IntermediateSkill Level
- 4.8+
- 385 reviews
Learn to build AI applications using Snowflake Cortexs built-in LLM functions for text analysis, generation, and multi-step workflows.
Artificial Intelligence
Course
Graph RAG with LangChain and Neo4j
- AdvancedSkill Level
- 4.7+
- 130 reviews
Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.
Artificial Intelligence
Course
Plan and Implement a Data Analytics Environment with Microsoft Fabric
- BasicSkill Level
- 4.7+
- 302 reviews
Learn how to set up and manage your Microsoft Fabric infrastructure.
Other
Course
Introduction to Network Analysis in Python
- IntermediateSkill Level
- 4.7+
- 232 reviews
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Probability & Statistics
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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