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728 Courses

Course

Data Types and Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 479 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

Introduction to Polars

  • BasicSkill Level
  • 4.8+
  • 391 reviews

Learn how to efficiently transform, clean, and analyze data using Polars, a Python library for fast data manipulation.

Data Manipulation

3 hours

Course

Monitoring Machine Learning Concepts

  • IntermediateSkill Level
  • 4.7+
  • 457 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

Fraud Detection in Python

  • IntermediateSkill Level
  • 4.7+
  • 189 reviews

Learn how to detect fraud using Python.

Machine Learning

4 hours

Course

Power BI for End Users

  • BasicSkill Level
  • 4.7+
  • 307 reviews

Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.

Reporting

1 hour

Course

Advanced AI-Assisted Coding for Developers

  • AdvancedSkill Level
  • 4.9+
  • 60 reviews

Learn to use AI as a senior engineering partner for code analysis, performance optimization, security, and software architecture decisions.

Artificial Intelligence

1 hour 30 min

Course

Generalized Linear Models in R

  • IntermediateSkill Level
  • 4.8+
  • 190 reviews

The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.

Probability & Statistics

4 hours

Course

Working with Geospatial Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 273 reviews

This course will show you how to integrate spatial data into your Python Data Science workflow.

Data Manipulation

4 hours

Course

AI Agents with Hugging Face smolagents

  • AdvancedSkill Level
  • 4.8+
  • 236 reviews

Learn how to build intelligent agents that reason, act, and solve real-world tasks using Python.

Artificial Intelligence

3 hours

Course

Unsupervised Learning in R

  • IntermediateSkill Level
  • 4.7+
  • 100 reviews

This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.

Machine Learning

4 hours

Course

Experimental Design in R

  • IntermediateSkill Level
  • 4.7+
  • 326 reviews

In this course youll learn about basic experimental design, a crucial part of any data analysis.

Probability & Statistics

4 hours

Course

Optimizing Code in Java

  • AdvancedSkill Level
  • 4.8+
  • 191 reviews

Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.

Software Development

3 hours

Course

Statistical Techniques in Tableau

  • IntermediateSkill Level
  • 4.8+
  • 636 reviews

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

Probability & Statistics

4 hours

Course

Math for Finance Professionals

  • BasicSkill Level
  • 4.8+
  • 291 reviews

Learn essential finance math skills with practical Excel exercises and real-world examples.

Applied Finance

3 hours

Course

Foundations of Probability in R

  • BasicSkill Level
  • 4.8+
  • 445 reviews

In this course, youll learn about the concepts of random variables, distributions, and conditioning.

Probability & Statistics

4 hours

Course

Building Web Applications with Shiny in R

  • IntermediateSkill Level
  • 4.7+
  • 214 reviews

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

Software Development

4 hours

Course

Cleaning Data in PostgreSQL Databases

  • IntermediateSkill Level
  • 4.8+
  • 444 reviews

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.

Data Preparation

4 hours

Course

Foundations of Probability in Python

  • IntermediateSkill Level
  • 4.8+
  • 201 reviews

Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.

Probability & Statistics

5 hours

Course

Introduction to TensorFlow in Python

  • IntermediateSkill Level
  • 4.8+
  • 53 reviews

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

Machine Learning

4 hours

Course

Data Pipeline Automation in Snowflake

  • BasicSkill Level
  • 4.8+
  • 65 reviews

Load, automate, and optimize data pipelines in Snowflake using COPY INTO, Snowpipe, streams, tasks, dynamic tables, and query performance tools.

Data Engineering

3 hours

Course

Understanding Digital Transformation

  • BasicSkill Level
  • 4.8+
  • 542 reviews

Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.

Data Literacy

1 hour

Course

Window Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 476 reviews

Discover Snowflake window functions to solve complex data problems with rankings, partitions, and rolling calculations.

Data Manipulation

3 hours

Course

Introduction to Optimization in Python

  • IntermediateSkill Level
  • 4.7+
  • 184 reviews

Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Software Development

4 hours

Course

AI-Assisted Travel Planning

  • BasicSkill Level
  • 4.8+
  • 443 reviews

Master travel planning with WanderBot: craft prompts, build confidence, and streamline your next adventure.

Artificial Intelligence

1 hour

Course

Intermediate Importing Data in R

  • IntermediateSkill Level
  • 4.8+
  • 269 reviews

Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.

Data Preparation

3 hours

Course

Supervised Learning in R: Regression

  • IntermediateSkill Level
  • 4.6+
  • 99 reviews

In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.

Machine Learning

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.

Grow your data skills with DataCamp for Mobile

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