Course
Developing Python Packages
- IntermediateSkill Level
- 4.8+
- 924
Learn to create your own Python packages to make your code easier to use and share with others.
Software Development
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Course
Introduction to KNIME
- BasicSkill Level
- 4.8+
- 912
Learn to use the KNIME Analytics Platform for data access, cleaning, and analysis with a no-code/low-code approach.
Data Preparation
Course
Artificial Intelligence Governance
- BasicSkill Level
- 4.8+
- 902
Learn AI governance with Collibra. Build, embed, and scale responsible AI using tools, frameworks, and MLOps workflows.
Artificial Intelligence
Course
Explainable Artificial Intelligence (XAI) Concepts
- BasicSkill Level
- 4.8+
- 898
Understand the role and real-world realities of Explainable Artificial Intelligence (XAI) with this beginner friendly course.
Artificial Intelligence
Course
Model Validation in Python
- IntermediateSkill Level
- 4.9+
- 893
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
Machine Learning
Course
Data Visualization in Tableau
- BasicSkill Level
- 4.8+
- 877
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
ARIMA Models in R
- BasicSkill Level
- 4.9+
- 868
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.
Probability & Statistics
Course
Machine Learning with PySpark
- AdvancedSkill Level
- 4.8+
- 827
Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.
Machine Learning
Course
Reporting in SQL
- IntermediateSkill Level
- 4.9+
- 825
Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.
Reporting
Course
Cleaning Data with PySpark
- AdvancedSkill Level
- 4.8+
- 822
Learn how to clean data with Apache Spark in Python.
Data Preparation
Course
Connecting Data in Tableau
- BasicSkill Level
- 4.9+
- 815
Learn to connect Tableau to different data sources and prepare the data for a smooth analysis.
Data Preparation
Course
Introduction to Google Workspace with Gemini
- BasicSkill Level
- 4.8+
- 806
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
Data Manipulation in Snowflake
- BasicSkill Level
- 4.8+
- 802
Master data manipulation and analysis techniques such as CASE statements, subqueries, and CTEs in Snowflake.
Data Manipulation
Course
Intermediate Object-Oriented Programming in Python
- AdvancedSkill Level
- 4.8+
- 799
Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!
Software Development
Course
Microsoft Copilot in Word
- BasicSkill Level
- 4.9+
- 787
Master Microsoft Copilot in Word to write faster, understand documents instantly, and collaborate more effectively.
Artificial Intelligence
Course
Marketing Analytics for Business
- BasicSkill Level
- 4.8+
- 784
Discover how Marketing Analysts use data to understand customers and drive business growth.
Leadership
Course
Software Development with Windsurf
- IntermediateSkill Level
- 4.9+
- 772
Boost your coding with Windsurf, the AI-powered IDE that helps you build, debug, and deploy faster.
Artificial Intelligence
Course
Pivot Tables in Google Sheets
- BasicSkill Level
- 4.9+
- 733
Learn how to create pivot tables and quickly organize thousands of data points with just a few clicks.
Data Manipulation
Course
Introduction to Statistics in Google Sheets
- BasicSkill Level
- 4.8+
- 712
Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
Probability & Statistics
Course
Forecasting in R
- BasicSkill Level
- 4.9+
- 698
Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.
Probability & Statistics
Course
Modeling with Data in the Tidyverse
- IntermediateSkill Level
- 4.9+
- 679
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
Probability & Statistics
Course
Sentiment Analysis in Python
- IntermediateSkill Level
- 4.8+
- 671
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
Introduction to R for Finance
- BasicSkill Level
- 4.8+
- 664
Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.
Applied Finance
Course
A/B Testing in Python
- IntermediateSkill Level
- 4.8+
- 645
Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.
Probability & Statistics
Course
CI/CD for Machine Learning
- AdvancedSkill Level
- 4.8+
- 638
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control
Machine Learning
Course
Dimensionality Reduction in Python
- IntermediateSkill Level
- 4.8+
- 636
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.
Machine Learning
Course
Statistical Thinking in Python (Part 1)
- IntermediateSkill Level
- 4.9+
- 624
Build the foundation you need to think statistically and to speak the language of your data.
Probability & Statistics
Course
Reporting with R Markdown
- IntermediateSkill Level
- 4.8+
- 623
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
Reporting
Course
Feature Engineering for NLP in Python
- AdvancedSkill Level
- 4.8+
- 617
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.
Machine Learning
Course
Generate a Study Guide
- BasicSkill Level
- 4.8+
- 613
Use a chatbot to create a study guide tailored to your goals and schedule. Build skills with simple, effective prompts.
Artificial Intelligence
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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