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697 Courses

Course

AI-Assisted Coding for Developers

  • IntermediateSkill Level
  • 4.8+
  • 631 reviews

Boost your coding with AI—guide your coding assistant to write, test, and document code effectively.

Artificial Intelligence

1 hour 30 min

Course

Responsible AI Practices

  • BasicSkill Level
  • 4.7+
  • 2,877 reviews

Master Responsible AI Practices with this comprehensive course, featuring real-world case studies and interactive content.

Artificial Intelligence

2 hours

Course

Natural Language Processing (NLP) in Python

  • IntermediateSkill Level
  • 4.8+
  • 679 reviews

Master text analysis with essential NLP techniques from preprocessing to advanced transformer models.

Artificial Intelligence

4 hours

Course

Financial Modeling in Excel

  • IntermediateSkill Level
  • 4.8+
  • 916 reviews

Learn about Excel financial modeling, including cash flow, scenario analysis, time value, and capital budgeting.

Applied Finance

3 hours

Course

Sampling in Python

  • IntermediateSkill Level
  • 4.7+
  • 3,493 reviews

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

Probability & Statistics

4 hours

Course

Data Types in Python

  • IntermediateSkill Level
  • 4.8+
  • 479 reviews

Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.

Software Development

4 hours

Course

Hypothesis Testing in R

  • IntermediateSkill Level
  • 4.7+
  • 910 reviews

Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.

Probability & Statistics

4 hours

Course

Introduction to Model Context Protocol (MCP)

  • IntermediateSkill Level
  • 4.8+
  • 84 reviews

Integrate AI/LLM applications with APIs, databases, and filesystems easier than ever before with the Model Context Protocol (MCP).

Artificial Intelligence

3 hours

Course

Object-Oriented Programming in Python

  • AdvancedSkill Level
  • 4.7+
  • 727 reviews

Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.

Software Development

4 hours

Course

Introduction to Data Quality

  • BasicSkill Level
  • 4.7+
  • 3,193 reviews

Explore the basics of data quality management. Learn the key concepts, dimensions, and techniques for monitoring and improving data quality.

Data Management

2 hours

Course

Designing Agentic Systems with LangChain

  • IntermediateSkill Level
  • 4.8+
  • 1,755 reviews

Get to grips with the foundational components of LangChain agents and build custom chat agents.

Artificial Intelligence

3 hours

Course

Web Scraping in Python

  • IntermediateSkill Level
  • 4.7+
  • 987 reviews

Learn to retrieve and parse information from the internet using the Python library scrapy.

Data Preparation

4 hours

Course

Introduction to Databricks SQL

  • IntermediateSkill Level
  • 4.7+
  • 556 reviews

Learn Databricks SQL for data engineering, analytics, and real-time data workflows in the lakehouse architecture.

Data Engineering

3 hours

Course

Machine Learning for Business

  • BasicSkill Level
  • 4.8+
  • 1,591 reviews

Understand the fundamentals of Machine Learning and how its applied in the business world.

Machine Learning

2 hours

Course

Introduction to Kubernetes

  • IntermediateSkill Level
  • 4.8+
  • 1,395 reviews

In this course, you will learn the fundamentals of Kubernetes and deploy and orchestrate containers using Manifests and kubectl instructions.

Software Development

3 hours

Course

Introduction to Sigma

  • BasicSkill Level
  • 4.8+
  • 376 reviews

Get started with Sigma! Learn how to build and customize simple, interactive dashboards for real-time analytics.

Data Manipulation

2 hours

Course

Intermediate GitHub Concepts

  • IntermediateSkill Level
  • 4.7+
  • 1,805 reviews

Level up your GitHub skills with our intermediate course on GitHub Projects, Administration, and advanced security features.

Software Development

3 hours

Course

Exploratory Data Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 1,164 reviews

Learn how to use graphical and numerical techniques to begin uncovering the structure of your data.

Exploratory Data Analysis

4 hours

Course

Power Pivot in Excel

  • BasicSkill Level
  • 4.8+
  • 1,357 reviews

Master Power Pivot in Excel to help import data, create relationships, and utilize DAX. Build dynamic dashboards to uncover actionable insights.

Data Manipulation

3 hours

Course

AI for Finance

  • BasicSkill Level
  • 4.8+
  • 211 reviews

Apply AI in finance to analyze data, prompt effectively, and automate workflows for better decisions.

Artificial Intelligence

3 hours

Course

Understanding Modern Data Architecture

  • IntermediateSkill Level
  • 4.7+
  • 1,051 reviews

Discover modern data architectures key components, from ingestion and serving to governance and orchestration.

Data Engineering

2 hours

Course

Introduction to Data Ethics

  • BasicSkill Level
  • 4.7+
  • 2,339 reviews

Explore data ethics with this comprehensive introductory course, covering principles, AI ethics, and practical skills to ensure responsible data use.

Data Literacy

1 hour

Course

Introduction to Deep Learning in Python

  • IntermediateSkill Level
  • 4.8+
  • 211 reviews

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.

Artificial Intelligence

4 hours

Course

Intermediate Regression in R

  • IntermediateSkill Level
  • 4.7+
  • 739 reviews

Learn to perform linear and logistic regression with multiple explanatory variables.

Probability & Statistics

4 hours

Course

Data Preparation in Alteryx

  • BasicSkill Level
  • 4.8+
  • 1,009 reviews

Master data preparation, cleaning, and analysis in Alteryx Designer, whether you are a new or seasoned analyst.

Data Preparation

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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