Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
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Bored of pouring over expenses to figure out which ones violate policy? No longer! Use Claude Cowork to produce fast and clear expense violation reports.
Artificial Intelligence
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In this course, youll learn the basics of relational databases and how to interact with them.
Data Manipulation
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You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.
Applied Finance
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Learn how to clean data with Apache Spark in Python.
Data Preparation
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Create interactive data visualizations in Python using Plotly.
Data Visualization
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In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!
Data Visualization
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This course will show you how to integrate spatial data into your Python Data Science workflow.
Data Manipulation
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Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.
Machine Learning
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Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.
Machine Learning
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Build end-to-end data pipelines in Snowflake: ingest, transform with SQL and Snowpark, deliver, and orchestrate.
Data Engineering
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Create a go-to-market strategy with generative AI: target industries, generate leads, and optimize website keywords.
Artificial Intelligence
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Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.
Data Visualization
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Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.
Software Development
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Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.
Data Manipulation
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Learn how to transform and analyze data within your Microsoft Fabric account
Other
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Master travel planning with WanderBot: craft prompts, build confidence, and streamline your next adventure.
Artificial Intelligence
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Learn the most important functions for manipulating, processing, and transforming data in SQL Server.
Data Manipulation
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Explore multi-agent system architecture and deployment using Googles ADK and Google Cloud infrastructure for production-grade agent applications.
Cloud
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Author Dags with the TaskFlow API, asset-based scheduling, and deferrable sensors, and run an end-to-end SQL ETL pipeline with quality checks.
Data Engineering
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Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.
Machine Learning
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Build reliable Power Automate cloud flows with triggers, branching, approvals, error handling, and production handover.
Artificial Intelligence
Course
Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.
Machine Learning
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Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.
Reporting
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Create and refine videos faster with Gemini in Google Vids. Use AI-powered storyboarding and content generation to produce polished videos with ease.
Cloud
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Build custom business apps without code using Microsoft Power Apps - from blank canvas to published, responsive app.
Artificial Intelligence
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You explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.
Cloud
Course
Learn how containers work in Azure, including registries, ACI, AKS basics, scaling, monitoring, and troubleshooting.
Cloud
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Organize and manage files with Gemini in Google Drive. Use AI-powered search to quickly find information, streamline collaboration, and boost productivity.
Artificial Intelligence
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Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
Probability & Statistics
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Build no-code Copilot Studio agents and flows that answer routine questions, take action, and cite approved sources.
Artificial Intelligence
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.
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.
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.
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.
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.
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.
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.
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.
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.
Make progress on the go with our mobile courses and daily 5-minute coding challenges.