Course
Choice Modeling for Marketing in R
- AdvancedSkill Level
- 4.7+
- 71
Learn to analyze and model customer choice data in R.
Probability & Statistics
Data, AI, and Cloud Courses
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Course
Introduction to Regression with statsmodels in Python
- IntermediateSkill Level
- 4.6+
- 2.6K
Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.
Probability & Statistics
Course
Data-Driven Decision Making for Business
- BasicSkill Level
- 4.6+
- 1.3K
Discover how to make better business decisions by applying practical data frameworks—no coding required.
Leadership
Course
Case Study: Analyzing Job Market Data in Power BI
- BasicSkill Level
- 4.5+
- 572
Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!
Data Manipulation
Course
Cleaning Data in PostgreSQL Databases
- IntermediateSkill Level
- 4.8+
- 533
Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.
Data Preparation
Course
Cleaning Data in SQL Server Databases
- IntermediateSkill Level
- 4.6+
- 297
Develop the skills you need to clean raw data and transform it into accurate insights.
Data Preparation
Course
Data Visualization in Tableau
- BasicSkill Level
- 4.5+
- 1.1K
Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.
Data Visualization
Course
Transform and Analyze Data with Microsoft Fabric
- BasicSkill Level
- 4.5+
- 401
Learn how to transform and analyze data within your Microsoft Fabric account
Other
Course
Practical AI with Google Gemini and NotebookLM
- BasicSkill Level
- 4.7+
- 4.2K
Master Gemini and NotebookLM to automate tasks, boost productivity, and work smarter across Googles AI ecosystem.
Artificial Intelligence
Course
Introduction to Databases in Python
- IntermediateSkill Level
- 4.6+
- 812
In this course, youll learn the basics of relational databases and how to interact with them.
Data Manipulation
Course
Data Transformation in Alteryx
- BasicSkill Level
- 4.6+
- 734
Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.
Data Manipulation
Course
Intermediate SQL
- BasicSkill Level
- 4.7+
- 23.5K
Accompanied at every step with hands-on practice queries, this course teaches you everything you need to know to analyze data using your own SQL code today!
Data Manipulation
Course
Case Study: Analyzing Healthcare Data in Power BI
- IntermediateSkill Level
- 4.7+
- 561
Practice Power BI with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.
Data Visualization
Course
Case Study: Analyzing Healthcare Data in Tableau
- IntermediateSkill Level
- 4.8+
- 114
Practice Tableau with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.
Data Visualization
Course
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.
Data Engineering
Course
Visualizing Time Series Data in Python
- IntermediateSkill Level
- 4.6+
- 464
Visualize seasonality, trends and other patterns in your time series data.
Data Visualization
Course
Web Scraping in Python
- IntermediateSkill Level
- 4.6+
- 1.8K
Learn to retrieve and parse information from the internet using the Python library scrapy.
Data Preparation
Course
Analyzing Police Activity with pandas
- IntermediateSkill Level
- 4.1+
- 134
Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.
Data Manipulation
Course
Case Study: Analyzing Customer Churn in Power BI
- BasicSkill Level
- 4.6+
- 7.1K
You will investigate a dataset from a fictitious company called Databel in Power BI, and need to figure out why customers are churning.
Data Visualization
Course
Introduction to Data Visualization with Matplotlib
- BasicSkill Level
- 4.5+
- 6K
Learn how to create, customize, and share data visualizations using Matplotlib.
Data Visualization
Course
Functions for Manipulating Data in PostgreSQL
- IntermediateSkill Level
- 4.5+
- 4.7K
Learn the most important PostgreSQL functions for manipulating, processing, and transforming data.
Data Manipulation
Course
Introduction to Data Science in Python
- BasicSkill Level
- 4.6+
- 4.5K
Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.
Software Development
Course
Data Communication Concepts
- BasicSkill Level
- 4.4+
- 4K
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
Forming Analytical Questions
- BasicSkill Level
- 4.5+
- 3.6K
Learn how to translate business questions to well-formed analytical questions and select the right analytical solutions.
Data Literacy
Course
Case Study: Analyzing Customer Churn in Excel
- BasicSkill Level
- 4.7+
- 3.4K
You will investigate a dataset from a fictitious company called Databel in Excel, and need to figure out why customers are churning.
Reporting
Course
Data-Driven Decision Making in SQL
- IntermediateSkill Level
- 4.6+
- 3K
Learn how to analyze a SQL table and report insights to management.
Data Literacy
Course
Cleaning Data with Generative AI
- BasicSkill Level
- 4.4+
- 2.4K
Use generative AI to tackle data cleaning, fixing duplicates, nulls, and formatting for consistent, accurate datasets.
Artificial Intelligence
Course
Joining Data with dplyr
- BasicSkill Level
- 4.4+
- 1.8K
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Data Manipulation
Course
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
Course
Data Science for Business
- BasicSkill Level
- 4.7+
- 1.3K
Learn about data science for managers and businesses and how to use data to strengthen your organization.
Data Literacy
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.