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397 Courses

Course

Improving Your Data Visualizations in Python

  • IntermediateSkill Level
  • 4.7+
  • 308 reviews

Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.

Data Visualization

4 hours

Course

Multi-Modal Models with Hugging Face

  • IntermediateSkill Level
  • 4.8+
  • 174 reviews

Combine text, images, audio, and video with the latest AI models from Hugging Face, and generate new images and videos!

Artificial Intelligence

4 hours

Course

Supply Chain Analytics in Python

  • IntermediateSkill Level
  • 4.8+
  • 94 reviews

Leverage the power of Python and PuLP to optimize supply chains.

Exploratory Data Analysis

4 hours

Course

Introduction to Optimization in Python

  • IntermediateSkill Level
  • 4.7+
  • 200 reviews

Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Software Development

4 hours

Course

Fundamentals of Bayesian Data Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 219 reviews

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

Probability & Statistics

4 hours

Course

Working with Dates and Times in R

  • IntermediateSkill Level
  • 4.8+
  • 94 reviews

Learn the essentials of parsing, manipulating and computing with dates and times in R.

Software Development

4 hours

Course

Building AI Agents with CrewAI

  • IntermediateSkill Level
  • 4.7+
  • 97 reviews

Build AI teams that work together, automate workflows, and generate content with CrewAI.

Artificial Intelligence

1 hour

Course

Machine Learning for Finance in Python

  • IntermediateSkill Level
  • 4.8+
  • 213 reviews

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Machine Learning

4 hours

Course

Supervised Learning in R: Regression

  • IntermediateSkill Level
  • 4.6+
  • 105 reviews

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Machine Learning

4 hours

Course

Time Series Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 273 reviews

Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.

Data Visualization

5 hours

Course

Foundations of Probability in Python

  • IntermediateSkill Level
  • 4.8+
  • 202 reviews

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

Probability & Statistics

5 hours

Course

Monte Carlo Simulations in Python

  • IntermediateSkill Level
  • 4.7+
  • 166 reviews

Learn to design and run your own Monte Carlo simulations using Python!

Probability & Statistics

4 hours

Course

Google: Build and Deploy Agents in Production

  • IntermediateSkill Level
  • 4.7+
  • 47 reviews

Explore multi-agent system architecture and deployment using Googles ADK and Google Cloud infrastructure for production-grade agent applications.

Cloud

30 min

Course

Manipulating Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 291 reviews

Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

Data Manipulation

4 hours

Course

Anomaly Detection in Python

  • IntermediateSkill Level
  • 4.8+
  • 178 reviews

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Probability & Statistics

4 hours

Course

Introduction to MongoDB in Python

  • IntermediateSkill Level
  • 4.7+
  • 376 reviews

Learn to manipulate and analyze flexibly structured data with MongoDB.

Data Engineering

3 hours

Course

Spoken Language Processing in Python

  • IntermediateSkill Level
  • 4.8+
  • 276 reviews

Learn how to load, transform, and transcribe speech from raw audio files in Python.

Data Manipulation

4 hours

Course

Cluster Analysis in R

  • IntermediateSkill Level
  • 4.8+
  • 71 reviews

Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.

Machine Learning

4 hours

Course

Azure Compute Solutions

  • IntermediateSkill Level
  • 4.7+
  • 123 reviews

Learn how containers work in Azure, including registries, ACI, AKS basics, scaling, monitoring, and troubleshooting.

Cloud

3 hours

Course

Introduction to Amazon Bedrock

  • IntermediateSkill Level
  • 4.7+
  • 133 reviews

Learn to use Amazon Bedrock to access foundation AI models and build with AI - without managing complex infrastructure.

Artificial Intelligence

3 hours

Course

Visualizing Geospatial Data in Python

  • IntermediateSkill Level
  • 4.7+
  • 345 reviews

Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.

Data Visualization

4 hours

Course

Modeling with Data in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 235 reviews

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

4 hours

Course

Analyzing Survey Data in R

  • IntermediateSkill Level
  • 4.8+
  • 220 reviews

Learn survey design using common design structures followed by visualizing and analyzing survey results.

Probability & Statistics

4 hours

Course

Develop for Azure Storage

  • IntermediateSkill Level
  • 4.7+
  • 97 reviews

Learn how to store, secure, scale, and process data in Azure using Blob Storage, Cosmos DB, queues, and event-driven services.

Cloud

3 hours

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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