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711 Courses

Course

Introduction to Data Quality with Great Expectations

  • IntermediateSkill Level
  • 4.7+
  • 356 reviews

Ensure high data quality in data science and data engineering workflows with Pythons Great Expectations library.

Data Engineering

4 hours

Course

AI-Assisted Product Launch

  • BasicSkill Level
  • 4.7+
  • 324 reviews

Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.

Artificial Intelligence

1 hour

Course

Data Strategy

  • BasicSkill Level
  • 4.7+
  • 1,726 reviews

Master strategic data management for business excellence.

Data Management

1 hour

Course

HR Analytics: Exploring Employee Data in R

  • IntermediateSkill Level
  • 4.8+
  • 35 reviews

Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.

Exploratory Data Analysis

5 hours

Course

Baseball Data Visualization in Power BI

  • BasicSkill Level
  • 4.8+
  • 177 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

Fine-Tuning with Llama 3

  • IntermediateSkill Level
  • 4.7+
  • 355 reviews

Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.

Artificial Intelligence

2 hours

Course

Monitoring Machine Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 329 reviews

This course covers everything you need to know to build a basic machine learning monitoring system in Python

Machine Learning

3 hours

Course

Building AI Agents with CrewAI

  • IntermediateSkill Level
  • 4.8+
  • 77 reviews

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

Artificial Intelligence

1 hour

Course

Visualization Best Practices in R

  • BasicSkill Level
  • 4.8+
  • 301 reviews

Learn to effectively convey your data with an overview of common charts, alternative visualization types, and perception-driven style enhancements.

Data Visualization

1 hour

Course

Introduction to Python in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 137 reviews

Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.

Data Manipulation

3 hours

Course

Analyzing Survey Data in R

  • IntermediateSkill Level
  • 4.8+
  • 201 reviews

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

Probability & Statistics

4 hours

Course

Supply Chain Analytics in Python

  • IntermediateSkill Level
  • 4.7+
  • 84 reviews

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

Exploratory Data Analysis

4 hours

Course

Introduction to Data Versioning with DVC

  • IntermediateSkill Level
  • 4.7+
  • 364 reviews

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

Machine Learning

3 hours

Course

Databricks with the Python SDK

  • AdvancedSkill Level
  • 4.7+
  • 72 reviews

Master Databricks with Python: learn to authenticate, manage clusters, automate jobs, and query AI models programmatically.

Artificial Intelligence

3 hours

Course

Introduction to Testing in Java

  • AdvancedSkill Level
  • 4.8+
  • 121 reviews

Learn how to write effective tests in Java using JUnit and Mockito to build robust, reliable applications with confidence.

Software Development

3 hours

Course

Communicating with Data in the Tidyverse

  • BasicSkill Level
  • 4.8+
  • 190 reviews

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Data Visualization

4 hours

Course

Snowflake Architecture

  • BasicSkill Level
  • 4.8+
  • 22 reviews

Master Snowflakes three-layer architecture and build the mental model you need to work effectively in Snowflake.

3 hours

Course

Working with Dates and Times in R

  • IntermediateSkill Level
  • 4.8+
  • 90 reviews

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

Software Development

4 hours

Course

Data Manipulation with data.table in R

  • BasicSkill Level
  • 4.6+
  • 21 reviews

Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.

Data Manipulation

4 hours

Course

Case Study: Inventory Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 165 reviews

This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.

Data Visualization

5 hours

Course

Transactions and Error Handling in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 252 reviews

Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.

Software Development

4 hours

Course

Time Series Analysis in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 247 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

Introduction to DataLab

  • BasicSkill Level
  • 4.8+
  • 106 reviews

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

Reporting

1 hour

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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