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771 Courses

Course

Building AI Agents with CrewAI

  • IntermediateSkill Level
  • 4.8+
  • 85 reviews

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

Artificial Intelligence

1 hour

Course

Conquering Data Bias

  • BasicSkill Level
  • 4.7+
  • 218 reviews

Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.

Data Management

2 hours

Course

Practicing Statistics Interview Questions in Python

  • AdvancedSkill Level
  • 4.7+
  • 87 reviews

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

Probability & Statistics

4 hours

Course

Data Transformation with Polars

  • IntermediateSkill Level
  • 4.9+
  • 40 reviews

Take Polars further with text manipulation, rolling statistics, DataFrame joins, and advanced analytics.

Data Manipulation

4 hours

Course

Azure Compute Solutions

  • IntermediateSkill Level
  • 4.8+
  • 113 reviews

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

Cloud

3 hours

Course

Web Scraping in R

  • IntermediateSkill Level
  • 4.7+
  • 95 reviews

Learn how to efficiently collect and download data from any website using R.

Data Preparation

4 hours

Course

Case Study: Ecommerce Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 201 reviews

In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.

Data Visualization

4 hours

Course

Data Fluency

  • BasicSkill Level
  • 4.8+
  • 279 reviews

Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.

Data Literacy

2 hours

Course

Multi-Modal Models with Hugging Face

  • IntermediateSkill Level
  • 4.8+
  • 157 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

Dealing with Missing Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 180 reviews

Learn how to identify, analyze, remove and impute missing data in Python.

Data Manipulation

4 hours

Course

Introduction to Julia

  • BasicSkill Level
  • 4.8+
  • 128 reviews

Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.

Software Development

4 hours

Course

Using Data Stores in AWS

  • IntermediateSkill Level
  • 4.7+
  • 29 reviews

Learn to choose, build with, and secure AWS data stores including DynamoDB and S3 through hands-on console exercises and real-world scenarios.

Cloud

3 hours

Course

Introduction to Amazon Bedrock

  • IntermediateSkill Level
  • 4.7+
  • 126 reviews

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

Artificial Intelligence

3 hours

Course

Model Context Protocol: Advanced Topics

  • IntermediateSkill Level
  • 4.8+
  • 15 reviews

Go beyond MCP basics with sampling, notifications, roots, and the STDIO and StreamableHTTP transports in Python.

Artificial Intelligence

3 hours

Course

Intermediate R for Finance

  • BasicSkill Level
  • 4.8+
  • 41 reviews

Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.

Applied Finance

5 hours

Course

Statistical Thinking in Python (Part 2)

  • IntermediateSkill Level
  • 4.7+
  • 249 reviews

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Probability & Statistics

4 hours

Course

Case Study: Supply Chain Analytics in Power BI

  • BasicSkill Level
  • 4.8+
  • 181 reviews

Learn how to use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.

Data Visualization

4 hours

Course

Baseball Data Visualization in Power BI

  • BasicSkill Level
  • 4.8+
  • 188 reviews

Discover how to analyze and visualize baseball data using Power BI. Create scatter plots, tornado charts, and gauges to bring baseball insights alive.

Data Visualization

1 hour

Course

Introduction to Spark with sparklyr in R

  • IntermediateSkill Level
  • 4.7+
  • 82 reviews

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

4 hours

Course

GARCH Models in Python

  • IntermediateSkill Level
  • 4.8+
  • 187 reviews

Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.

Applied Finance

4 hours

Course

Case Study: Mortgage Trading Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 277 reviews

In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.

Applied Finance

3 hours

Course

Efficient AI Model Training with PyTorch

  • AdvancedSkill Level
  • 4.9+
  • 100 reviews

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

Artificial Intelligence

4 hours

Course

Survival Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 191 reviews

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

Probability & Statistics

4 hours

Course

Develop for Azure Storage

  • IntermediateSkill Level
  • 4.7+
  • 85 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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