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200 Courses

Course

Interactive Data Visualization with Bokeh

  • IntermediateSkill Level
  • 4.7+
  • 39 reviews

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

Data Visualization

4 hours

Course

Machine Translation with Keras

  • AdvancedSkill Level
  • 4.8+
  • 45 reviews

Are you curious about the inner workings of the models that are behind products like Google Translate?

Artificial Intelligence

4 hours

Course

Retrieval-Augmented Generation with LangChain

  • IntermediateSkill Level
  • 4.7+
  • 31 reviews

Learn to build knowledge-grounded LLM applications that retrieve relevant information from structured and unstructured sources before generating responses.

Artificial Intelligence

AI Native

2 hours

Course

LLM Application Fundamentals with LangChain

  • IntermediateSkill Level
  • 4.6+
  • 83 reviews

Learn to build conversational LLM applications — with reliable structured output, persistent conversation history, and real-time streaming.

Artificial Intelligence

AI Native

3 hours

Course

LLM Tool Use with LangChain

  • IntermediateSkill Level
  • 4.6+
  • 19 reviews

Learn to extend your LLM applications with external tools, so your applications can retrieve live data, perform computations, and take real-world actions.

Artificial Intelligence

AI Native

3 hours

Course

Prompt Engineering with LangChain

  • IntermediateSkill Level
  • 4.6+
  • 38 reviews

Learn to write effective prompts and systematically improve them through evaluation rather than intuition.

Artificial Intelligence

AI Native

2 hours

Course

Working with the OpenAI API

  • BasicSkill Level
  • 4.8+
  • 7,369 reviews

Start your journey developing AI-powered applications with the OpenAI API. Learn about the functionality that underpins popular AI applications like ChatGPT.

Artificial Intelligence

3 hours

Course

Introduction to FastAPI

  • IntermediateSkill Level
  • 4.7+
  • 1,379 reviews

Build robust, production-grade APIs with FastAPI, mastering HTTP operations, validation, and async execution to create efficient data and ML pipelines.

Software Development

4 hours

Course

Working with Llama 3

  • IntermediateSkill Level
  • 4.8+
  • 1,989 reviews

Explore the latest techniques for running the Llama LLM locally and integrating it within your stack.

Artificial Intelligence

2 hours

Course

Cleaning Data with PySpark

  • AdvancedSkill Level
  • 4.7+
  • 451 reviews

Learn how to clean data with Apache Spark in Python.

Data Preparation

4 hours

Course

Reporting in SQL

  • IntermediateSkill Level
  • 4.8+
  • 751 reviews

Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.

Reporting

4 hours

Course

Foundations of PySpark

  • IntermediateSkill Level
  • 4.7+
  • 593 reviews

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

Data Engineering

4 hours

Course

Data Processing in Shell

  • IntermediateSkill Level
  • 4.8+
  • 475 reviews

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Data Manipulation

4 hours

Course

Programming Paradigm Concepts

  • BasicSkill Level
  • 4.8+
  • 121 reviews

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

Software Development

2 hours

Course

Intermediate Julia

  • BasicSkill Level
  • 4.7+
  • 79 reviews

Take your Julia skills to the next level with our intermediate Julia course. Learn about loops, advanced data structures, timing, and more.

Software Development

4 hours

Course

Work with Gemini Models in BigQuery

  • IntermediateSkill Level
  • 4.6+
  • 3 reviews

Work with Gemini AI models in BigQuery for sentiment analysis. Analyze customer reviews using SQL and Python notebooks with Gemini.

Cloud

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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Make progress on the go with our mobile courses and daily 5-minute coding challenges.