Data, AI, and Cloud Courses

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670 Courses

Course

Analyzing Social Media Data in Python

IntermediateSkill Level
4.7+
200

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

Data Manipulation

Course

Monitor and Troubleshoot Azure Solutions

IntermediateSkill Level
4.5+
200

Learn how to monitor, diagnose, and optimize Azure applications using Azure Monitor, Application Insights, and Log Analytics.

Cloud

Course

Practicing Statistics Interview Questions in Python

AdvancedSkill Level
4.5+
199

Prepare for your next statistics interview by reviewing concepts like conditional probabilities, A/B testing, the bias-variance tradeoff, and more.

Probability & Statistics

Course

Quantitative Risk Management in R

BasicSkill Level
4.3+
194

Work with risk-factor return series, study their empirical properties, and make estimates of value-at-risk.

Applied Finance

Course

Conditional Formatting in Google Sheets

BasicSkill Level
3.9+
194

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

Data Manipulation

Course

Importing Data in Java

IntermediateSkill Level
4.6+
187

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

Time Series Analysis in PostgreSQL

IntermediateSkill Level
4.6+
185

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
4.7+
184

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Probability & Statistics

Course

Machine Learning in the Tidyverse

IntermediateSkill Level
4.8+
183

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

Machine Learning

Course

Efficient AI Model Training with PyTorch

AdvancedSkill Level
4.6+
179

Learn how to reduce training times for large language models with Accelerator and Trainer for distributed training

Artificial Intelligence

Course

Analyzing US Census Data in Python

IntermediateSkill Level
4.5+
175

Learn to use the Census API to work with demographic and socioeconomic data.

Exploratory Data Analysis

Course

Developing R Packages

IntermediateSkill Level
4.4+
175

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

Hyperparameter Tuning in R

AdvancedSkill Level
4.1+
174

Learn how to tune your models hyperparameters to get the best predictive results.

Machine Learning

Course

End-to-End RAG with Weaviate

IntermediateSkill Level
4.4+
172

Master RAG with Weaviate! Embed text and images for retrieval, and experiment with vector, BM25, and hybrid search.

Artificial Intelligence

Course

Building Dashboards with flexdashboard

IntermediateSkill Level
4.2+
171

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+
168

Explore a range of programming paradigms, including imperative and declarative, procedural, functional, and object-oriented programming.

Software Development

Course

Financial Forecasting in Python

IntermediateSkill Level
4.7+
164

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

Text-to-Query Agents with MongoDB and LangGraph

IntermediateSkill Level
4.5+
163

Discover how to talk to your data using text-to-query AI agents with MongoDB and LangGraph.

Artificial Intelligence

Course

Building AI Agents with Haystack

IntermediateSkill Level
4.7+
159

Create a healthcare AI agent using Haystack, an open-source framework for orchestrating LLMs and external components.

Artificial Intelligence

Course

GARCH Models in R

AdvancedSkill Level
4.5+
158

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

Applied Finance

Course

Structural Equation Modeling with lavaan in R

AdvancedSkill Level
4.8+
156

Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.

Probability & Statistics

Course

Introduction to Spark with sparklyr in R

IntermediateSkill Level
4.6+
156

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

Data Engineering

Course

Machine Learning for Marketing Analytics in R

IntermediateSkill Level
4.6+
153

In this course youll learn how to use data science for several common marketing tasks.

Machine Learning

Course

Case Studies: Building Web Applications with Shiny in R

IntermediateSkill Level
4.7+
152

Practice your Shiny skills while building some fun Shiny apps for real-life scenarios!

Reporting

Course

Handling Missing Data with Imputations in R

AdvancedSkill Level
4.5+
152

Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.

Data Manipulation

Course

Differential Expression Analysis with limma in R

AdvancedSkill Level
4.5+
152

Learn to use the Bioconductor package limma for differential gene expression analysis.

Probability & Statistics

Course

Introduction to Natural Language Processing in R

IntermediateSkill Level
4.4+
151

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

Machine Learning

Course

Text Mining with Bag-of-Words in R

IntermediateSkill Level
4.5+
149

Learn the bag of words technique for text mining with R.

Machine Learning

Course

Market Basket Analysis in R

IntermediateSkill Level
4.4+
149

Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.

Data Manipulation

Course

Gen AI: Unlock Foundational Concepts

BasicSkill Level
4.7+
148

You unlock the foundational concepts of generative AI by exploring the differences between AI, ML, and gen AI.

Cloud

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.