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Analyzing Data in Tableau
- BasicSkill Level
- 4.8+
- 1,899 reviews
Take your Tableau skills up a notch with advanced analytics and visualizations.
Data Visualization
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Introduction to Importing Data in R
- BasicSkill Level
- 4.7+
- 403 reviews
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
Data Preparation
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Data Literacy Case Study: Remote Working Analysis
- BasicSkill Level
- 4.8+
- 3,986 reviews
Improve data literacy skills by analyzing remote working policies.
Data Literacy
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Data Governance Concepts
- BasicSkill Level
- 4.8+
- 2,341 reviews
Gain an introduction to data governance, exploring its meaning, purpose, and how to implement a data governance framework.
Data Management
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Microsoft Copilot in PowerPoint
- BasicSkill Level
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Build PowerPoint presentations with Microsoft Copilot. Turn documents into slides, generate visuals, and speaker notes.
Artificial Intelligence
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Introduction to Apache Airflow in Python
- AdvancedSkill Level
- 4.8+
- 2,390 reviews
Learn how to implement and schedule data engineering workflows.
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AI for Finance
- BasicSkill Level
- 4.8+
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Apply AI in finance to analyze data, prompt effectively, and automate workflows for better decisions.
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Financial Modeling in Excel
- IntermediateSkill Level
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Intermediate Deep Learning with PyTorch
- IntermediateSkill Level
- 4.8+
- 2,435 reviews
Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.
Artificial Intelligence
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Report Design in Power BI
- IntermediateSkill Level
- 4.7+
- 3,367 reviews
Continue your data visualization journey where youll learn practical techniques for incorporating DAX measures and progressive disclosure in your reports.
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Introduction to Databricks SQL
- IntermediateSkill Level
- 4.7+
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Learn Databricks SQL for data engineering, analytics, and real-time data workflows in the lakehouse architecture.
Data Engineering
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Deploying and Maintaining Assets in Power BI
- IntermediateSkill Level
- 4.8+
- 3,657 reviews
Learn how to deploy and maintain assets in Power BI. You’ll get to grips with the Power BI Service interface and key elements in it like workspaces.
Data Manipulation
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Natural Language Processing (NLP) in Python
- IntermediateSkill Level
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Master text analysis with essential NLP techniques from preprocessing to advanced transformer models.
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Intermediate Java
- BasicSkill Level
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Software Development
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Exploratory Data Analysis in R
- IntermediateSkill Level
- 4.7+
- 1,350 reviews
Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.
Exploratory Data Analysis
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Introduction to Data Engineering
- IntermediateSkill Level
- 4.7+
- 958 reviews
Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.
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Introduction to Data Security
- BasicSkill Level
- 4.8+
- 2,165 reviews
Discover how to become a data defender and keep data safe and secure with this beginner-friendly interactive course.
Data Management
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Designing Agentic Systems with LangChain
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Get to grips with the foundational components of LangChain agents and build custom chat agents.
Artificial Intelligence
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Introduction to SQL Querying with AI
- BasicSkill Level
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Learn SQL Querying with AI by writing prompts, generating queries, and analyzing data to solve real-world problems.
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Artificial Intelligence
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Introduction to Power Automate
- BasicSkill Level
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Artificial Intelligence
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Intermediate Python for Finance
- IntermediateSkill Level
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Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.
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Building AI Applications with Pinecone
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Discover how the Pinecone vector database is revolutionizing AI application development!
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Introduction to FastAPI
- IntermediateSkill Level
- 4.7+
- 1,790 reviews
Build robust, production-grade APIs with FastAPI, mastering HTTP operations, validation, and async execution to create efficient data and ML pipelines.
Software Development
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Understanding Modern Data Architecture
- IntermediateSkill Level
- 4.7+
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Discover modern data architectures key components, from ingestion and serving to governance and orchestration.
Data Engineering
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Creating Dashboards in Tableau
- BasicSkill Level
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Dashboards are a must-have in a data-driven world. Increase your impact on business performance with Tableau dashboards.
Data Visualization
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Multi-Agent Systems with LangGraph
- AdvancedSkill Level
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Build powerful multi-agent systems by applying emerging agentic design patterns in the LangGraph framework.
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Monetizing Artificial Intelligence
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Introduction to Data Quality
- BasicSkill Level
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Introduction to Microsoft Fabric
- BasicSkill Level
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- 1,235 reviews
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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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