Course
Data Transformation in Power BI
- IntermediateSkill Level
- 4.8+
- 4.7K
You’ll learn how to (un)pivot, transpose, append and join tables. Gain power with custom columns, M language, and the Advanced Editor.
Data Manipulation
Data, AI, and Cloud Courses
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Course
Unsupervised Learning in Python
- IntermediateSkill Level
- 4.8+
- 4.7K
Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
Machine Learning
Course
Building Scalable Agentic Systems
- BasicSkill Level
- 4.8+
- 4.7K
Discover what it takes to scale AI agents, with a little help from frameworks like MCP and A2A.
Artificial Intelligence
Course
Introduction to Data Culture
- BasicSkill Level
- 4.8+
- 4.6K
Learn the key components of building a strong data culture within an organization.
Data Literacy
Course
Data Storytelling Concepts
- BasicSkill Level
- 4.8+
- 4.6K
Elevate your data storytelling skills and discover how to tell great stories that drive change with your audience.
Data Literacy
Course
Developing LLM Applications with LangChain
- IntermediateSkill Level
- 4.8+
- 4.6K
Discover how to build AI-powered applications using LLMs, prompts, chains, and agents in LangChain.
Artificial Intelligence
Course
Introduction to Workflow Automation with n8n
- BasicSkill Level
- 4.8+
- 4.5K
Get started with n8n and learn to build automated workflows using triggers, logic, APIs, and AI—no coding required!
Artificial Intelligence
Course
Introduction to Java
- BasicSkill Level
- 4.9+
- 4.4K
Learn Java from the ground up with this beginner-friendly course, mastering essential programming concepts and skills.
Software Development
Course
Introduction to Power Query in Excel
- BasicSkill Level
- 4.8+
- 4.3K
Explore Excel Power Query for advanced data transformation and cleansing to boost your decision-making and analysis.
Data Preparation
Course
Functions for Manipulating Data in PostgreSQL
- IntermediateSkill Level
- 4.8+
- 4.2K
Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.
Data Manipulation
Course
Cleaning Data in Python
- IntermediateSkill Level
- 4.8+
- 4.1K
Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!
Data Preparation
Course
Forming Analytical Questions
- BasicSkill Level
- 4.8+
- 4K
Learn how to translate business questions to well-formed analytical questions and select the right analytical solutions.
Data Literacy
Course
Data Communication Concepts
- BasicSkill Level
- 4.8+
- 3.8K
No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.
Data Literacy
Course
Data Manipulation with dplyr
- BasicSkill Level
- 4.9+
- 3.8K
Build Tidyverse skills by learning how to transform and manipulate data with dplyr.
Data Manipulation
Course
Introduction to Docker
- IntermediateSkill Level
- 4.8+
- 3.6K
Gain an introduction to Docker and discover its importance in the data professional’s toolkit. Learn about Docker containers, images, and more.
Software Development
Course
Data Warehousing Concepts
- IntermediateSkill Level
- 4.8+
- 3.5K
This introductory and conceptual course will help you understand the fundamentals of data warehousing.
Data Engineering
Course
Intermediate ChatGPT
- BasicSkill Level
- 4.8+
- 3.5K
Learn the architecture behind GPT models and master advanced prompt crafting to unlock ChatGPTs full potential.
Artificial Intelligence
Course
Case Study: HR Analytics in Power BI
- BasicSkill Level
- 4.8+
- 3.4K
Apply your skills to import, analyze and visualize Human Resources (HR) data using Power BI.
Data Manipulation
Course
Exploratory Data Analysis in Power BI
- BasicSkill Level
- 4.8+
- 3.4K
Learn how to build impactful reports with Power BI’s Exploratory Data Analysis (EDA) that uncover insights faster and drive business value.
Exploratory Data Analysis
Course
Introduction to Python for Finance
- BasicSkill Level
- 4.8+
- 3.4K
Build Python skills to elevate your finance career. Learn how to work with lists, arrays and data visualizations to master financial analyses.
Applied Finance
Course
Introduction to Shell
- BasicSkill Level
- 4.8+
- 3.2K
The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs on clusters and clouds.
Software Development
Course
Data Literacy Case Study: Remote Working Analysis
- BasicSkill Level
- 4.8+
- 3K
Improve data literacy skills by analyzing remote working policies.
Data Literacy
Course
Introduction to Data Privacy
- BasicSkill Level
- 4.8+
- 3K
Gain a clear understanding of data privacy principles and how to implement privacy and security processes.
Data Literacy
Course
Analyzing Data in Tableau
- BasicSkill Level
- 4.9+
- 2.9K
Take your Tableau skills up a notch with advanced analytics and visualizations.
Data Visualization
Course
Data Connections in Power BI
- BasicSkill Level
- 4.8+
- 2.9K
Discover the different ways you can enhance your Power BI data importing skills.
Data Manipulation
Course
Introduction to Google Sheets
- BasicSkill Level
- 4.8+
- 2.9K
Bring your Google Sheets to life by mastering fundamental skills such as formulas, operations, and cell references.
Data Preparation
Course
Software Engineering Principles in Python
- BasicSkill Level
- 4.7+
- 2.9K
Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.
Software Development
Course
ETL and ELT in Python
- IntermediateSkill Level
- 4.8+
- 2.8K
Learn to build effective, performant, and reliable data pipelines using Extract, Transform, and Load principles.
Data Engineering
Course
Deploying and Maintaining Assets in Power BI
- IntermediateSkill Level
- 4.8+
- 2.8K
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
Course
Writing Efficient Python Code
- IntermediateSkill Level
- 4.8+
- 2.7K
Learn to write efficient code that executes quickly and allocates resources skillfully to avoid unnecessary overhead.
Software Development
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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