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349 Courses

Course

Financial Trading in Python

  • IntermediateSkill Level
  • 4.8+
  • 285 reviews

Learn to implement custom trading strategies in Python, backtest them, and evaluate their performance!

Applied Finance

4 hours

Course

Natural Language Processing with spaCy

  • IntermediateSkill Level
  • 4.7+
  • 583 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

Dimensionality Reduction in Python

  • IntermediateSkill Level
  • 4.8+
  • 854 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 Workflow Automation with n8n

  • IntermediateSkill Level
  • 4.8+
  • 47 reviews

Design resilient, production-ready n8n automations that fetch APIs, process data in batches, handle errors, and run unattended on a schedule.

Artificial Intelligence

4 hours

Course

Introduction to Portfolio Risk Management in Python

  • IntermediateSkill Level
  • 4.8+
  • 315 reviews

Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.

Applied Finance

4 hours

Course

Manipulating Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 283 reviews

Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.

Data Manipulation

4 hours

Course

Developing Machine Learning Models for Production

  • IntermediateSkill Level
  • 4.8+
  • 446 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

Reshaping Data with pandas

  • IntermediateSkill Level
  • 4.7+
  • 784 reviews

Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

Data Manipulation

4 hours

Course

A/B Testing in Python

  • IntermediateSkill Level
  • 4.7+
  • 355 reviews

Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.

Probability & Statistics

4 hours

Course

Introduction to Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 112 reviews

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

Probability & Statistics

4 hours

Course

NoSQL Concepts

  • IntermediateSkill Level
  • 4.8+
  • 516 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

Improving Query Performance in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 403 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

Biomedical Image Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 233 reviews

Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.

Data Manipulation

4 hours

Course

Modeling with Data in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 228 reviews

Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.

Probability & Statistics

4 hours

Course

Linear Algebra for Data Science in R

  • IntermediateSkill Level
  • 4.7+
  • 135 reviews

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

Probability & Statistics

4 hours

Course

Foundations of Inference in R

  • IntermediateSkill Level
  • 4.7+
  • 52 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

Course

Reporting with R Markdown

  • IntermediateSkill Level
  • 4.7+
  • 323 reviews

R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.

Reporting

4 hours

Course

Statistical Thinking in Python (Part 1)

  • IntermediateSkill Level
  • 4.8+
  • 108 reviews

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

Probability & Statistics

3 hours

Course

Data Types and Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 492 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

User-Oriented Design in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 417 reviews

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

Data Visualization

2 hours

Course

Monitoring Machine Learning Concepts

  • IntermediateSkill Level
  • 4.8+
  • 463 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

Experimental Design in R

  • IntermediateSkill Level
  • 4.7+
  • 333 reviews

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

Probability & Statistics

4 hours

Course

Fraud Detection in Python

  • IntermediateSkill Level
  • 4.7+
  • 190 reviews

Learn how to detect fraud using Python.

Machine Learning

4 hours

Course

Statistical Techniques in Tableau

  • IntermediateSkill Level
  • 4.8+
  • 643 reviews

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

Probability & Statistics

4 hours

Course

Working with Geospatial Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 275 reviews

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

Data Manipulation

4 hours

Course

Unsupervised Learning in R

  • IntermediateSkill Level
  • 4.7+
  • 101 reviews

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

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.

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