Course
Developing Machine Learning Models for Production
- IntermediateSkill Level
- 4.8+
- 531
Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.
Machine Learning
Data, AI, and Cloud Courses
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Course
Building a Go-To-Market Strategy
- BasicSkill Level
- 4.8+
- 530
Create a go-to-market strategy with generative AI: target industries, generate leads, and optimize website keywords.
Artificial Intelligence
Course
Introduction to Bioconductor in R
- IntermediateSkill Level
- 4.8+
- 526
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!
Probability & Statistics
Course
Case Study: Analyzing Job Market Data in Power BI
- BasicSkill Level
- 4.8+
- 525
Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!
Data Manipulation
Course
Gen AI: Beyond the Chatbot
- BasicSkill Level
- 4.8+
- 524
This course aims to move beyond the basic understanding of chatbots to explore the true potential of generative AI for your organization.
Cloud
Course
Data Visualization in Google Sheets
- BasicSkill Level
- 4.8+
- 524
Learn the fundamentals of data visualization using Google Sheets.
Data Visualization
Course
Unsupervised Learning in R
- IntermediateSkill Level
- 4.8+
- 522
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
Machine Learning
Course
Introduction to Databricks Lakehouse
- BasicSkill Level
- 4.8+
- 522
Explore the Databricks Lakehouse - from medallion architecture and clusters to governance, sharing, and deployment.
Data Engineering
Course
Introduction to Text Analysis in R
- IntermediateSkill Level
- 4.8+
- 519
Analyze text data in R using the tidy framework.
Data Manipulation
Course
Machine Learning with Tree-Based Models in R
- BasicSkill Level
- 4.9+
- 511
Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.
Machine Learning
Course
Machine Learning with caret in R
- IntermediateSkill Level
- 4.9+
- 509
This course teaches the big ideas in machine learning like how to build and evaluate predictive models.
Machine Learning
Course
Introduction to Predictive Analytics in Python
- BasicSkill Level
- 4.8+
- 502
In this course youll learn to use and present logistic regression models for making predictions.
Machine Learning
Course
Foundations of Probability in R
- BasicSkill Level
- 4.8+
- 501
In this course, youll learn about the concepts of random variables, distributions, and conditioning.
Probability & Statistics
Course
Foundations of Inference in R
- IntermediateSkill Level
- 4.8+
- 500
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.
Probability & Statistics
Course
Improving Query Performance in SQL Server
- IntermediateSkill Level
- 4.8+
- 499
In this course, students will learn to write queries that are both efficient and easy to read and understand.
Software Development
Course
Generalized Linear Models in R
- IntermediateSkill Level
- 4.8+
- 498
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.
Probability & Statistics
Course
Quantitative Risk Management in Python
- AdvancedSkill Level
- 4.8+
- 498
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.
Applied Finance
Course
Gemini in Google Slides
- BasicSkill Level
- 4.8+
- 495
Create impactful presentations faster with Gemini in Google Slides. Use AI-powered design and suggestions to build professional, engaging slides in minutes.
Artificial Intelligence
Course
Gemini in Google Docs
- BasicSkill Level
- 4.9+
- 489
Write and edit faster with Gemini in Google Docs. Get AI-powered drafting, rewriting, and content suggestions to create clear, polished documents effortlessly.
Artificial Intelligence
Course
Visualizations in Sigma
- BasicSkill Level
- 4.9+
- 488
Learn to build and customize Sigma charts to tell clear, compelling data stories—no coding required.
Data Visualization
Course
Financial Trading in Python
- IntermediateSkill Level
- 4.8+
- 484
Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!
Applied Finance
Course
Demystifying Decision Science
- BasicSkill Level
- 4.8+
- 484
Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions.
Data Literacy
Course
String Manipulation with stringr in R
- IntermediateSkill Level
- 4.8+
- 484
Learn how to pull character strings apart, put them back together and use the stringr package.
Software Development
Course
Practicing Coding Interview Questions in Python
- AdvancedSkill Level
- 4.8+
- 478
Prepare for your next coding interviews in Python.
Software Development
Course
AI Agents with Hugging Face smolagents
- AdvancedSkill Level
- 4.8+
- 473
Learn how to build intelligent agents that reason, act, and solve real-world tasks using Python.
Artificial Intelligence
Course
Gemini in Google Sheets
- BasicSkill Level
- 4.9+
- 471
Analyze data smarter with Gemini in Google Sheets. Use AI-powered insights, formula suggestions, and automation to simplify spreadsheets and boost productivity.
Artificial Intelligence
Course
Dealing With Missing Data in R
- BasicSkill Level
- 4.8+
- 471
Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.
Data Preparation
Course
Deep Reinforcement Learning in Python
- AdvancedSkill Level
- 4.8+
- 467
Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.
Artificial Intelligence
Course
Writing Functions and Stored Procedures in SQL Server
- IntermediateSkill Level
- 4.9+
- 460
Master SQL Server programming by learning to create, update, and execute functions and stored procedures.
Software Development
Course
Statistical Techniques in Tableau
- IntermediateSkill Level
- 4.8+
- 460
Take your reporting skills to the next level with Tableau’s built-in statistical functions.
Probability & Statistics
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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