Course
CI/CD for Machine Learning
- AdvancedSkill Level
- 4.8+
- 693
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control
Machine Learning
Data, AI, and Cloud Courses
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Course
User-Oriented Design in Power BI
- IntermediateSkill Level
- 4.7+
- 691
Learn how to design Power BI visualizations and reports with users in mind.
Data Visualization
Course
Introduction to Optimization in Python
- IntermediateSkill Level
- 4.8+
- 690
Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.
Software Development
Course
Building Web Applications with Shiny in R
- IntermediateSkill Level
- 4.8+
- 687
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
- 4.9+
- 684
Using Python and NumPy, learn the most fundamental financial concepts.
Applied Finance
Course
Dimensionality Reduction in Python
- IntermediateSkill Level
- 4.8+
- 684
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.
Machine Learning
Course
Understanding GDPR
- BasicSkill Level
- 4.8+
- 681
Gain a clear understanding of GDPR principles and how to set up GDPR-compliant processes in this comprehensive course.
Data Literacy
Course
Biomedical Image Analysis in Python
- IntermediateSkill Level
- 4.8+
- 680
Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.
Data Manipulation
Course
Credit Risk Modeling in Python
- IntermediateSkill Level
- 4.8+
- 678
Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
Applied Finance
Course
Data Visualization in Google Sheets
- BasicSkill Level
- 4.8+
- 677
Learn the fundamentals of data visualization using Google Sheets.
Data Visualization
Course
Intermediate Google Sheets
- BasicSkill Level
- 4.8+
- 675
Expand your Google Sheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.
Data Preparation
Course
AI for Consulting
- BasicSkill Level
- 4.8+
- 674
Discover how AI can take your consulting work to the next level! Research, analyze, and communicate more productively and effectively.
Artificial Intelligence
Course
Case Study: Building E-Commerce Data Models with dbt
- AdvancedSkill Level
- 4.8+
- 674
Learn how to transform raw data into clean, reliable models with dbt through hands-on, real-world exercises.
Data Engineering
Course
Intermediate Regression with statsmodels in Python
- IntermediateSkill Level
- 4.8+
- 670
Learn to perform linear and logistic regression with multiple explanatory variables.
Probability & Statistics
Course
Foundations of Probability in R
- BasicSkill Level
- 4.8+
- 670
In this course, youll learn about the concepts of random variables, distributions, and conditioning.
Probability & Statistics
Course
Introduction to Google Workspace with Gemini
- BasicSkill Level
- 4.8+
- 667
You learn about the key features of Gemini and how they can be used to improve productivity and efficiency in Google Workspace.
Artificial Intelligence
Course
Statistical Thinking in Python (Part 1)
- IntermediateSkill Level
- 4.9+
- 660
Build the foundation you need to think statistically and to speak the language of your data.
Probability & Statistics
Course
Working with Geospatial Data in Python
- IntermediateSkill Level
- 4.8+
- 659
This course will show you how to integrate spatial data into your Python Data Science workflow.
Data Manipulation
Course
Data Visualization in Databricks
- BasicSkill Level
- 4.8+
- 659
Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.
Data Visualization
Course
Generate a Study Guide
- BasicSkill Level
- 4.8+
- 657
Use a chatbot to create a study guide tailored to your goals and schedule. Build skills with simple, effective prompts.
Artificial Intelligence
Course
Linear Algebra for Data Science in R
- IntermediateSkill Level
- 4.7+
- 651
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Probability & Statistics
Course
Sentiment Analysis in Python
- IntermediateSkill Level
- 4.8+
- 634
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.
Machine Learning
Course
Intermediate SQL Querying with AI
- BasicSkill Level
- 4.9+
- 625
Build SQL skills by writing AI prompts that generate queries for sorting, grouping, filtering, and categorizing data.
Data Manipulation
Course
Introduction to Text Analysis in R
- IntermediateSkill Level
- 4.8+
- 623
Analyze text data in R using the tidy framework.
Data Manipulation
Course
Feature Engineering for NLP in Python
- AdvancedSkill Level
- 4.9+
- 611
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.
Machine Learning
Course
Building a Go-To-Market Strategy
- BasicSkill Level
- 4.8+
- 607
Create a go-to-market strategy with generative AI: target industries, generate leads, and optimize website keywords.
Artificial Intelligence
Course
Introduction to Oracle SQL
- BasicSkill Level
- 4.8+
- 606
Sharpen your skills in Oracle SQL including SQL basics, aggregating, combining, and customizing data.
Data Manipulation
Course
Natural Language Processing with spaCy
- IntermediateSkill Level
- 4.8+
- 604
Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.
Machine Learning
Course
Data Types and Functions in Snowflake
- IntermediateSkill Level
- 4.9+
- 597
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
- 4.9+
- 587
Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.
Data Manipulation
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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