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771 Courses

Course

Building AI Agents with CrewAI

  • IntermediateSkill Level
  • 4.7+
  • 96 reviews

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

Artificial Intelligence

1 hour

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

Spoken Language Processing in Python

  • IntermediateSkill Level
  • 4.8+
  • 275 reviews

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

Data Manipulation

4 hours

Course

Building AI Agents with Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 23 reviews

Build autonomous Cortex Agents in Snowflake that query structured and unstructured data, then deploy and monitor them.

Artificial Intelligence

4 hours

Course

Time Series Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 271 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

Factor Analysis in R

  • AdvancedSkill Level
  • 4.7+
  • 159 reviews

Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.

Probability & Statistics

4 hours

Course

Case Study: Building Software in Python

  • AdvancedSkill Level
  • 4.7+
  • 298 reviews

Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.

Software Development

3 hours

Course

Forecasting in R

  • BasicSkill Level
  • 4.9+
  • 52 reviews

Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

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

Financial Analytics in Google Sheets

  • BasicSkill Level
  • 4.7+
  • 129 reviews

Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.

Applied Finance

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

Ensemble Methods in Python

  • AdvancedSkill Level
  • 4.8+
  • 416 reviews

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Machine Learning

4 hours

Course

Introduction to MongoDB in Python

  • IntermediateSkill Level
  • 4.7+
  • 375 reviews

Learn to manipulate and analyze flexibly structured data with MongoDB.

Data Engineering

3 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

Google: Build and Deploy Agents in Production

  • IntermediateSkill Level
  • 4.8+
  • 45 reviews

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

Cloud

30 min

Course

Introduction to Data Engineering on Google Cloud

  • BasicSkill Level
  • 4.8+
  • 20 reviews

Learn the data engineering role on Google Cloud. Explore data sources, storage solutions, ETL/ELT architectures, BigQuery, Dataform, and Dataproc.

Cloud

3 hours 41 min

Course

Analyzing Survey Data in R

  • IntermediateSkill Level
  • 4.8+
  • 219 reviews

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

Probability & Statistics

4 hours

Course

Modeling with Data in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 233 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

Dealing With Missing Data in R

  • BasicSkill Level
  • 4.7+
  • 141 reviews

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Data Preparation

4 hours

Course

Introduction to DataLab

  • BasicSkill Level
  • 4.8+
  • 116 reviews

Learn the fundamentals of using DataLab, an AI-powered data notebook for data analysis and exploration.

Reporting

1 hour

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

Feature Engineering with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 296 reviews

Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Data Manipulation

4 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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