Course
Developing Python Packages
- IntermediateSkill Level
- 4.4+
- 853
Learn to create your own Python packages to make your code easier to use and share with others.
Software Development
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MLOps Deployment and Life Cycling
- AdvancedSkill Level
- 4.6+
- 849
In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.
Machine Learning
Course
Deploying AI into Production with FastAPI
- AdvancedSkill Level
- 4.7+
- 845
Learn how to use FastAPI to develop APIs that support AI models, built to meet real-world demands.
Artificial Intelligence
Course
End-to-End Machine Learning
- IntermediateSkill Level
- 4.6+
- 845
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.
Machine Learning
Course
Intermediate Object-Oriented Programming in Python
- AdvancedSkill Level
- 4.7+
- 837
Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!
Software Development
Course
A/B Testing in Python
- IntermediateSkill Level
- 4.4+
- 831
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
Data Validation in Excel
- BasicSkill Level
- 4.5+
- 822
Learn Excel data validation to improve accuracy, create drop-downs, and manage inventory and orders with confidence.
Data Management
Course
Pivot Tables in Google Sheets
- BasicSkill Level
- 4.5+
- 820
Learn how to create pivot tables and quickly organize thousands of data points with just a few clicks.
Data Manipulation
Course
Introduction to MongoDB in Python
- IntermediateSkill Level
- 4.5+
- 814
Learn to manipulate and analyze flexibly structured data with MongoDB.
Data Engineering
Course
Introduction to Azure
- BasicSkill Level
- 4.7+
- 812
Explore Azure services like Compute, Storage, and Automation, with hands-on experience.
Cloud
Course
Manipulating Time Series Data in R
- IntermediateSkill Level
- 4.6+
- 809
Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.
Data Manipulation
Course
AI for Marketing
- BasicSkill Level
- 4.6+
- 805
Master AI for marketing to plan smarter campaigns, create quality content, and build custom AI agents.
Artificial Intelligence
Course
Introduction to Databases in Python
- IntermediateSkill Level
- 4.6+
- 798
In this course, youll learn the basics of relational databases and how to interact with them.
Data Manipulation
Course
Forecasting in R
- BasicSkill Level
- 4.4+
- 790
Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.
Probability & Statistics
Course
Data Types and Exceptions in Java
- IntermediateSkill Level
- 4.6+
- 772
Learn to work with Plain Old Java Objects, master the Collections Framework, and handle exceptions like a pro, with logging to back it all up!
Software Development
Course
Calculations in Tableau
- AdvancedSkill Level
- 4.5+
- 772
In this interactive course, you’ll learn how to use functions for your Tableau calculations and when you should use them!
Data Visualization
Course
ARIMA Models in R
- BasicSkill Level
- 4.7+
- 771
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.
Probability & Statistics
Course
Dimensionality Reduction in Python
- IntermediateSkill Level
- 4.7+
- 768
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.
Machine Learning
Course
Intermediate Google Sheets
- BasicSkill Level
- 4.6+
- 761
Expand your Google Sheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.
Data Preparation
Course
Software Development with Windsurf
- IntermediateSkill Level
- 4.6+
- 753
Boost your coding with Windsurf, the AI-powered IDE that helps you build, debug, and deploy faster.
Artificial Intelligence
Course
Modeling with Data in the Tidyverse
- IntermediateSkill Level
- 4.4+
- 748
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
Reporting with R Markdown
- IntermediateSkill Level
- 4.3+
- 747
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
Reporting
Course
Hyperparameter Tuning in Python
- IntermediateSkill Level
- 4.6+
- 745
Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
Machine Learning
Course
Data Transformation in Alteryx
- BasicSkill Level
- 4.6+
- 735
Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.
Data Manipulation
Course
AI for Consulting
- BasicSkill Level
- 4.6+
- 726
Discover how AI can take your consulting work to the next level! Research, analyze, and communicate more productively and effectively.
Artificial Intelligence
Course
Microsoft Copilot in Word
- BasicSkill Level
- 4.6+
- 717
Master Microsoft Copilot in Word to write faster, understand documents instantly, and collaborate more effectively.
Artificial Intelligence
Course
Machine Learning for Finance in Python
- IntermediateSkill Level
- 4.7+
- 713
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.
Machine Learning
Course
Image Modeling with Keras
- AdvancedSkill Level
- 4.7+
- 713
Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.
Artificial Intelligence
Course
User-Oriented Design in Power BI
- IntermediateSkill Level
- 4.3+
- 703
Learn how to design Power BI visualizations and reports with users in mind.
Data Visualization
Course
Credit Risk Modeling in Python
- IntermediateSkill Level
- 4.6+
- 701
Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
Applied Finance
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.