Course
Foundations of Inference in Python
- AdvancedSkill Level
- 4.5+
- 202
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.
Probability & Statistics
Data, AI, and Cloud Courses
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Course
Develop Azure Event-based and Message-based Solutions
- IntermediateSkill Level
- 4.4+
- 200
Learn to design scalable event-driven architectures in Azure using messaging services and real-world integrations.
Cloud
Course
Survival Analysis in Python
- AdvancedSkill Level
- 4.6+
- 198
Use survival analysis to work with time-to-event data and predict survival time.
Probability & Statistics
Course
Time Series Analysis in PostgreSQL
- IntermediateSkill Level
- 4.7+
- 192
Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.
Data Manipulation
Course
Network Analysis in R
- IntermediateSkill Level
- 4.6+
- 191
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.
Probability & Statistics
Course
Monitor and Troubleshoot Azure Solutions
- IntermediateSkill Level
- 4.5+
- 190
Learn how to monitor, diagnose, and optimize Azure applications using Azure Monitor, Application Insights, and Log Analytics.
Cloud
Course
Conditional Formatting in Google Sheets
- BasicSkill Level
- 3.9+
- 190
Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.
Data Manipulation
Course
Python for Spreadsheet Users
- BasicSkill Level
- 4.6+
- 189
Use your knowledge of common spreadsheet functions and techniques to explore Python!
Software Development
Course
Quantitative Risk Management in R
- BasicSkill Level
- 4.3+
- 187
Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.
Applied Finance
Course
Preparing for Your Associate Cloud Engineer Journey
- IntermediateSkill Level
- 4.6+
- 186
This course helps your preparation for the Associate Cloud Engineer exam, learn about the Google Cloud domains in the exam and create a study plan.
Cloud
Course
Building AI Agents with Haystack
- IntermediateSkill Level
- 4.8+
- 180
Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.
Artificial Intelligence
Course
Machine Learning in the Tidyverse
- IntermediateSkill Level
- 4.8+
- 179
Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.
Machine Learning
Course
Gen AI: Unlock Foundational Concepts
- BasicSkill Level
- 4.7+
- 176
You unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI.
Cloud
Course
Case Study: Set Up a Book Recommendation App in Azure
- BasicSkill Level
- 4.2+
- 172
Learn to set up a secure, efficient book recommendation app in Azure in this hands-on case study.
Cloud
Course
Importing Data in Java
- IntermediateSkill Level
- 4.6+
- 170
Learn to import, manipulate, and transform data in Java using the Tablesaw library. Work with CSV files, tabular structures, and complex JSON formats.
Software Development
Course
Text Mining with Bag-of-Words in R
- IntermediateSkill Level
- 4.5+
- 170
Learn the bag of words technique for text mining with R.
Machine Learning
Course
Developing R Packages
- IntermediateSkill Level
- 4.4+
- 170
Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.
Software Development
Course
Nonlinear Modeling with Generalized Additive Models (GAMs) in R
- IntermediateSkill Level
- 4.5+
- 167
GAMs model relationships in data as nonlinear functions that are highly adaptable to different types of data science problems.
Probability & Statistics
Course
Efficient AI Model Training with PyTorch
- AdvancedSkill Level
- 4.5+
- 167
Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training
Artificial Intelligence
Course
End-to-End RAG with Weaviate
- IntermediateSkill Level
- 4.3+
- 167
Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.
Artificial Intelligence
Course
Gen AI: Navigate the Landscape
- BasicSkill Level
- 4.8+
- 163
You explore the different layers of building gen AI solutions, Google Cloud’s offerings, and the factors to consider when selecting a solution.
Cloud
Course
Text-to-Query Agents with MongoDB and LangGraph
- IntermediateSkill Level
- 4.6+
- 162
Discover how to talk to your data using text-to-query AI agents with MongoDB and LangGraph.
Artificial Intelligence
Course
Analyzing US Census Data in Python
- IntermediateSkill Level
- 4.5+
- 162
Learn to use the Census API to work with demographic and socioeconomic data.
Exploratory Data Analysis
Course
Building Dashboards with flexdashboard
- IntermediateSkill Level
- 4.2+
- 162
In this course youll learn how to create static and interactive dashboards using flexdashboard and shiny.
Reporting
Course
Programming Paradigm Concepts
- BasicSkill Level
- 4.7+
- 161
Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.
Software Development
Course
Market Basket Analysis in R
- IntermediateSkill Level
- 4.4+
- 161
Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.
Data Manipulation
Course
Machine Learning for Marketing Analytics in R
- IntermediateSkill Level
- 4.6+
- 159
In this course youll learn how to use data science for several common marketing tasks.
Machine Learning
Course
Handling Missing Data with Imputations in R
- AdvancedSkill Level
- 4.5+
- 158
Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.
Data Manipulation
Course
Financial Forecasting in Python
- IntermediateSkill Level
- 4.8+
- 157
Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.
Applied Finance
Course
Case Studies: Building Web Applications with Shiny in R
- IntermediateSkill Level
- 4.7+
- 157
Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!
Reporting
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.