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Multi-Agent Systems with LangGraph
- AdvancedSkill Level
- 4.7+
- 1.6K
Build powerful multi-agent systems by applying emerging agentic design patterns in the LangGraph framework.
Artificial Intelligence
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670 Courses
Course
Introduction to Object-Oriented Programming in Java
- IntermediateSkill Level
- 4.7+
- 1.6K
Learn key object-oriented programming concepts, from basic classes and objects to advanced topics like inheritance and polymorphism.
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Deep Learning for Images with PyTorch
- AdvancedSkill Level
- 4.5+
- 1.6K
Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.
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Financial Analysis in Power BI
- IntermediateSkill Level
- 4.6+
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Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.
Applied Finance
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Introduction to Sigma
- BasicSkill Level
- 4.8+
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Get started with Sigma! Learn how to build and customize simple, interactive dashboards for real-time analytics.
Data Manipulation
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Databricks Concepts
- BasicSkill Level
- 4.6+
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Learn about the power of Databricks Lakehouse and help you scale up your data engineering and machine learning skills.
Data Engineering
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Understanding Microsoft Azure Architecture and Services
- BasicSkill Level
- 4.6+
- 1.5K
This course dives deeper into the Azures backbone by going into topics like containers, virtual machines and much more.
Cloud
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Streamlined Data Ingestion with pandas
- IntermediateSkill Level
- 4.6+
- 1.5K
Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
Data Preparation
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Data Preparation in Alteryx
- BasicSkill Level
- 4.6+
- 1.5K
Master data preparation, cleaning, and analysis in Alteryx Designer, whether you are a new or seasoned analyst.
Data Preparation
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Intermediate Power Query in Excel
- IntermediateSkill Level
- 4.4+
- 1.5K
Building on your foundational Power Query in Excel knowledge, this intermediate course takes you to the next level of data transformation mastery
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Vector Databases for Embeddings with Pinecone
- IntermediateSkill Level
- 4.6+
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Discover how the Pinecone vector database is revolutionizing AI application development!
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Linear Classifiers in Python
- IntermediateSkill Level
- 4.6+
- 1.5K
In this course you will learn the details of linear classifiers like logistic regression and SVM.
Machine Learning
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Analyzing Business Data in SQL
- IntermediateSkill Level
- 4.7+
- 1.5K
Learn to write SQL queries to calculate key metrics that businesses use to measure performance.
Reporting
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Intermediate Data Visualization with ggplot2
- IntermediateSkill Level
- 4.4+
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Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
Data Visualization
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Introduction to Deep Learning in Python
- IntermediateSkill Level
- 4.7+
- 1.5K
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.
Artificial Intelligence
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Working with Categorical Data in Python
- IntermediateSkill Level
- 4.6+
- 1.5K
Learn how to manipulate and visualize categorical data using pandas and seaborn.
Data Manipulation
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Introduction to Data Ethics
- BasicSkill Level
- 4.6+
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Explore data ethics with this comprehensive introductory course, covering principles, AI ethics, and practical skills to ensure responsible data use.
Data Literacy
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Introduction to Microsoft Fabric
- BasicSkill Level
- 4.6+
- 1.4K
To understand Fabric’s main use cases, you will explore various tools in the seven Fabric experiences.
Other
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Monetizing Artificial Intelligence
- BasicSkill Level
- 4.5+
- 1.4K
Explore AI and data monetization strategies, build ethical infrastructures, and align products with business goals.
Artificial Intelligence
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Reshaping Data with pandas
- IntermediateSkill Level
- 4.5+
- 1.4K
Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.
Data Manipulation
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Regular Expressions in Python
- BasicSkill Level
- 4.5+
- 1.4K
Learn about string manipulation and become a master at using regular expressions.
Software Development
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Applying SQL to Real-World Problems
- IntermediateSkill Level
- 4.7+
- 1.4K
Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.
Reporting
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Introduction to Testing in Python
- AdvancedSkill Level
- 4.5+
- 1.4K
Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.
Software Development
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Azure App Services
- IntermediateSkill Level
- 4.5+
- 1.4K
Build and deploy scalable web apps and serverless functions in Azure while mastering security, monitoring, and automation.
Cloud
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Working with Llama 3
- IntermediateSkill Level
- 4.7+
- 1.4K
Explore the latest techniques for running the Llama LLM locally and integrating it within your stack.
Artificial Intelligence
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Responsible AI Practices
- BasicSkill Level
- 4.4+
- 1.4K
Master Responsible AI Practices with this comprehensive course, featuring real-world case studies and interactive content.
Artificial Intelligence
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Data Storytelling Case Study: College Majors
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- 4.5+
- 1.3K
Data storytelling is a high-demand skill that elevates analytics. Learn narrative building and visualizations in this course with a college major dataset!
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Intermediate Regression in R
- IntermediateSkill Level
- 4.4+
- 1.3K
Learn to perform linear and logistic regression with multiple explanatory variables.
Probability & Statistics
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Intermediate dbt
- AdvancedSkill Level
- 4.4+
- 1.3K
Take your dbt skills to the next level with this hands-on course designed for data engineers and analytics professionals.
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Building AI Agents with Google ADK
- IntermediateSkill Level
- 4.6+
- 1.3K
Build a customer-support assistant step-by-step with Google’s Agent Development Kit (ADK).
Artificial Intelligence
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.