Course
Introduction to Optimization in Python
- IntermediateSkill Level
- 4.6+
- 698
Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.
Software Development
Data, AI, and Cloud Courses
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Course
CI/CD for Machine Learning
- AdvancedSkill Level
- 4.5+
- 698
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control
Machine Learning
Course
Data Visualization in Google Sheets
- BasicSkill Level
- 4.3+
- 690
Learn the fundamentals of data visualization using Google Sheets.
Data Visualization
Course
Introduction to Portfolio Risk Management in Python
- IntermediateSkill Level
- 4.6+
- 685
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
Applied Finance
Course
Intermediate Regression with statsmodels in Python
- IntermediateSkill Level
- 4.6+
- 685
Learn to perform linear and logistic regression with multiple explanatory variables.
Probability & Statistics
Course
Data Manipulation in Alteryx
- BasicSkill Level
- 4.5+
- 685
Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.
Data Manipulation
Course
Statistical Thinking in Python (Part 1)
- IntermediateSkill Level
- 4.4+
- 685
Build the foundation you need to think statistically and to speak the language of your data.
Probability & Statistics
Course
Building Web Applications with Shiny in R
- IntermediateSkill Level
- 4.4+
- 685
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.
Software Development
Course
Introduction to Financial Concepts in Python
- BasicSkill Level
- 4.7+
- 684
Using Python and NumPy, learn the most fundamental financial concepts.
Applied Finance
Course
Working with Geospatial Data in Python
- IntermediateSkill Level
- 4.7+
- 682
This course will show you how to integrate spatial data into your Python Data Science workflow.
Data Manipulation
Course
Microsoft Copilot in PowerPoint
- BasicSkill Level
- 4.5+
- 679
Build PowerPoint presentations with Microsoft Copilot. Turn documents into slides, generate visuals, and speaker notes.
Artificial Intelligence
Course
Case Study: Building E-Commerce Data Models with dbt
- AdvancedSkill Level
- 4.6+
- 677
Learn how to transform raw data into clean, reliable models with dbt through hands-on, real-world exercises.
Data Engineering
Course
Generate a Study Guide
- BasicSkill Level
- 4.4+
- 677
Use a chatbot to create a study guide tailored to your goals and schedule. Build skills with simple, effective prompts.
Artificial Intelligence
Course
Input/Output and Streams in Java
- IntermediateSkill Level
- 4.5+
- 672
Advance your Java skills by learning to handle files, process data, and build clean, reusable code using real-world techniques.
Software Development
Course
Data Types and Functions in Snowflake
- IntermediateSkill Level
- 4.7+
- 669
Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.
Data Manipulation
Course
Window Functions in Snowflake
- IntermediateSkill Level
- 4.7+
- 665
Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.
Data Manipulation
Course
Foundations of Probability in R
- BasicSkill Level
- 4.6+
- 665
In this course, youll learn about the concepts of random variables, distributions, and conditioning.
Probability & Statistics
Course
Data Visualization in Databricks
- BasicSkill Level
- 4.6+
- 665
Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.
Data Visualization
Course
Understanding GDPR
- BasicSkill Level
- 4.5+
- 655
Gain a clear understanding of GDPR principles and how to set up GDPR-compliant processes in this comprehensive course.
Data Literacy
Course
Linear Algebra for Data Science in R
- IntermediateSkill Level
- 4.5+
- 646
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Probability & Statistics
Course
Introduction to Model Context Protocol (MCP)
- IntermediateSkill Level
- 4.6+
- 643
Integrate AI/LLM applications with APIs, databases, and filesystems easier than ever before with the Model Context Protocol (MCP).
Artificial Intelligence
Course
Financial Trading in Python
- IntermediateSkill Level
- 4.7+
- 638
Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!
Applied Finance
Course
Intermediate SQL Querying with AI
- BasicSkill Level
- 4.8+
- 635
Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.
Data Manipulation
Course
Introduction to Polars
- BasicSkill Level
- 4.6+
- 633
Learn how to efficiently transform, clean, and analyze data using Polars, a Python library for fast data manipulation.
Data Manipulation
Course
Introduction to Oracle SQL
- BasicSkill Level
- 4.6+
- 625
Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.
Data Manipulation
Course
Introduction to Text Analysis in R
- IntermediateSkill Level
- 4.7+
- 622
Analyze text data in R using the tidy framework.
Data Manipulation
Course
Introduction to Predictive Analytics in Python
- BasicSkill Level
- 4.5+
- 611
In this course youll learn to use and present logistic regression models for making predictions.
Machine Learning
Course
Market Basket Analysis in Python
- IntermediateSkill Level
- 4.6+
- 610
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
Machine Learning
Course
Building a Go-To-Market Strategy
- BasicSkill Level
- 4.4+
- 604
Create a go-to-market strategy with generative AI: target industries, generate leads, and optimize website keywords.
Artificial Intelligence
Course
Improving Query Performance in SQL Server
- IntermediateSkill Level
- 4.6+
- 597
In this course, students will learn to write queries that are both efficient and easy to read and understand.
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.