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394 Courses

Course

Developing Python Packages

  • IntermediateSkill Level
  • 4.7+
  • 1,021 reviews

Learn to create your own Python packages to make your code easier to use and share with others.

Software Development

4 hours

Course

User-Oriented Design in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 538 reviews

Learn how to design Power BI visualizations and reports with users in mind.

Data Visualization

2 hours

Course

Linear Algebra for Data Science in R

  • IntermediateSkill Level
  • 4.7+
  • 153 reviews

This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.

Probability & Statistics

4 hours

Course

Building AI Agents with Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 49 reviews

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

Artificial Intelligence

4 hours

Course

Model Validation in Python

  • IntermediateSkill Level
  • 4.8+
  • 994 reviews

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

Machine Learning

4 hours

Course

Developing Machine Learning Models for Production

  • IntermediateSkill Level
  • 4.7+
  • 540 reviews

Shift to an MLOps mindset, enabling you to train, document, maintain, and scale your machine learning models to their fullest potential.

Machine Learning

4 hours

Course

Dimensionality Reduction in Python

  • IntermediateSkill Level
  • 4.8+
  • 980 reviews

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

Machine Learning

4 hours

Course

Intermediate Regression in R

  • IntermediateSkill Level
  • 4.8+
  • 841 reviews

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

Probability & Statistics

4 hours

Course

Time Series Analysis in SQL Server

  • IntermediateSkill Level
  • 4.7+
  • 464 reviews

Explore ways to work with date and time data in SQL Server for time series analysis

Data Manipulation

5 hours

Course

Improving Query Performance in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 490 reviews

In this course, students will learn to write queries that are both efficient and easy to read and understand.

Software Development

4 hours

Course

Introduction to Databases in Python

  • IntermediateSkill Level
  • 4.8+
  • 316 reviews

In this course, youll learn the basics of relational databases and how to interact with them.

Data Manipulation

4 hours

Course

Statistical Thinking in Python (Part 1)

  • IntermediateSkill Level
  • 4.8+
  • 120 reviews

Build the foundation you need to think statistically and to speak the language of your data.

Probability & Statistics

3 hours

Course

NoSQL Concepts

  • IntermediateSkill Level
  • 4.8+
  • 589 reviews

In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.

Data Engineering

2 hours

Course

Intermediate Power Automate

  • IntermediateSkill Level
  • 4.8+
  • 35 reviews

Build reliable Power Automate cloud flows with triggers, branching, approvals, error handling, and production handover.

Artificial Intelligence

3 hours

Course

Monitoring Machine Learning Concepts

  • IntermediateSkill Level
  • 4.8+
  • 560 reviews

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Machine Learning

2 hours

Course

Building AI Agents with CrewAI

  • IntermediateSkill Level
  • 4.7+
  • 113 reviews

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

Artificial Intelligence

1 hour

Course

Natural Language Processing with spaCy

  • IntermediateSkill Level
  • 4.7+
  • 681 reviews

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

Machine Learning

4 hours

Course

Fully Automated MLOps

  • IntermediateSkill Level
  • 4.8+
  • 389 reviews

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Machine Learning

4 hours

Course

Transactions and Error Handling in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 358 reviews

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

Software Development

4 hours

Course

Data Types and Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 604 reviews

Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.

Data Manipulation

3 hours

Course

Azure Compute Solutions

  • IntermediateSkill Level
  • 4.7+
  • 201 reviews

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

Cloud

3 hours

Course

Foundations of Inference in R

  • IntermediateSkill Level
  • 4.7+
  • 58 reviews

Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.

Probability & Statistics

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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