Course
Big Data Fundamentals with PySpark
- AdvancedSkill Level
- 4.7+
- 264 reviews
Learn the fundamentals of working with big data with PySpark.
Data Engineering
Data, AI, and Cloud Courses
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776 Courses
Course
Streamlined Data Ingestion with pandas
- IntermediateSkill Level
- 4.8+
- 2,156 reviews
Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
Data Preparation
Course
Working with Llama 3
- IntermediateSkill Level
- 4.8+
- 2,525 reviews
Explore the latest techniques for running the Llama LLM locally and integrating it within your stack.
Artificial Intelligence
Course
Object-Oriented Programming in Python
- AdvancedSkill Level
- 4.7+
- 846 reviews
Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.
Software Development
Course
Responsible AI Data Management
- IntermediateSkill Level
- 4.7+
- 1,342 reviews
Learn the theory behind responsibly managing your data for any AI project, from start to finish and beyond.
Artificial Intelligence
Course
Understanding Microsoft Azure Management and Governance
- BasicSkill Level
- 4.8+
- 1,527 reviews
Master Azure Management and Governance with our comprehensive course, ideal for data professionals seeking cloud expertise.
Cloud
Course
Financial Analysis in Power BI
- IntermediateSkill Level
- 4.8+
- 593 reviews
Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.
Applied Finance
Course
Introduction to Databricks Lakehouse
- BasicSkill Level
- 4.7+
- 396 reviews
Explore the Databricks Lakehouse - from medallion architecture and clusters to governance, sharing, and deployment.
Data Engineering
Course
Joining Data with dplyr
- BasicSkill Level
- 4.7+
- 1,378 reviews
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Data Manipulation
Course
Machine Learning for Business
- BasicSkill Level
- 4.8+
- 1,913 reviews
Understand the fundamentals of Machine Learning and how its applied in the business world.
Machine Learning
Course
Databricks Concepts
- BasicSkill Level
- 4.7+
- 1,032 reviews
Learn about the power of Databricks Lakehouse and help you scale up your data engineering and machine learning skills.
Data Engineering
Course
Data Visualization in Google Sheets
- BasicSkill Level
- 4.8+
- 731 reviews
Learn the fundamentals of data visualization using Google Sheets.
Data Visualization
Course
Google: Introduction to AI Agents
- BasicSkill Level
- 4.8+
- 395 reviews
Gain an overview of AI Agents. Discover how AI Agents use autonomous action and reasoning to solve complex problems.
Cloud
Course
Working with Categorical Data in Python
- IntermediateSkill Level
- 4.7+
- 2,930 reviews
Learn how to manipulate and visualize categorical data using pandas and seaborn.
Data Manipulation
Course
Applying SQL to Real-World Problems
- IntermediateSkill Level
- 4.8+
- 1,403 reviews
Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.
Reporting
Course
Developing AI Systems with the OpenAI API
- IntermediateSkill Level
- 4.7+
- 3,148 reviews
Leverage the OpenAI API to get your AI applications ready for production.
Artificial Intelligence
Course
Creating PostgreSQL Databases
- BasicSkill Level
- 4.8+
- 832 reviews
Learn how to create a PostgreSQL database and explore the structure, data types, and how to normalize databases.
Data Preparation
Course
Introduction to Sigma
- BasicSkill Level
- 4.8+
- 595 reviews
Get started with Sigma! Learn how to build and customize simple, interactive dashboards for real-time analytics.
Data Manipulation
Course
Data Visualization in Tableau
- BasicSkill Level
- 4.8+
- 955 reviews
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
DevOps Concepts
- BasicSkill Level
- 4.8+
- 1,016 reviews
In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.
Software Development
Course
Introduction to R for Finance
- BasicSkill Level
- 4.7+
- 110 reviews
Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.
Applied Finance
Course
Hypothesis Testing in R
- IntermediateSkill Level
- 4.7+
- 1,094 reviews
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
Probability & Statistics
Course
Reshaping Data with tidyr
- IntermediateSkill Level
- 4.8+
- 515 reviews
Transform almost any dataset into a tidy format to make analysis easier.
Data Manipulation
Course
Deep Learning for Images with PyTorch
- AdvancedSkill Level
- 4.7+
- 889 reviews
Apply PyTorch to images and use deep learning models for object detection with bounding boxes and image segmentation generation.
Artificial Intelligence
Course
Intermediate Data Visualization with ggplot2
- IntermediateSkill Level
- 4.7+
- 1,049 reviews
Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
Data Visualization
Course
Cleaning Data in R
- IntermediateSkill Level
- 4.7+
- 891 reviews
Learn to clean data as quickly and accurately as possible to help you move from raw data to awesome insights.
Data Preparation
Course
Reporting with R Markdown
- IntermediateSkill Level
- 4.7+
- 368 reviews
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
Reporting
Course
Introduction to Bash Scripting
- IntermediateSkill Level
- 4.8+
- 583 reviews
Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.
Software Development
Course
Introduction to Apache Kafka
- IntermediateSkill Level
- 4.7+
- 1,002 reviews
Master Apache Kafka! From core concepts to advanced architecture, learn to create, manage, and troubleshoot Kafka for real-world data streaming challenges!
Data Engineering
Course
Introduction to Data Ethics
- BasicSkill Level
- 4.7+
- 2,659 reviews
Explore data ethics with this comprehensive introductory course, covering principles, AI ethics, and practical skills to ensure responsible data use.
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.
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