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729 Courses

Course

Customer Analytics and A/B Testing in Python

  • IntermediateSkill Level
  • 4.7+
  • 103 reviews

Learn how to use Python to create, run, and analyze A/B tests to make proactive business decisions.

Probability & Statistics

4 hours

Course

Introduction to Spark with sparklyr in R

  • IntermediateSkill Level
  • 4.7+
  • 81 reviews

Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.

Data Engineering

4 hours

Course

Analyzing Financial Statements in Python

  • IntermediateSkill Level
  • 4.7+
  • 111 reviews

Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.

Applied Finance

4 hours

Course

Marketing Analytics in Google Sheets

  • IntermediateSkill Level
  • 4.8+
  • 215 reviews

Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.

Reporting

4 hours

Course

Scalable AI Models with PyTorch Lightning

  • IntermediateSkill Level
  • 4.7+
  • 94 reviews

Streamline your AI projects by building modular models and mastering advanced optimization with PyTorch Lightning!

Artificial Intelligence

3 hours

Course

Network Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 120 reviews

Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.

Probability & Statistics

4 hours

Course

Communicating with Data in the Tidyverse

  • BasicSkill Level
  • 4.8+
  • 193 reviews

Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.

Data Visualization

4 hours

Course

Concepts in Computer Science

  • BasicSkill Level
  • 4.7+
  • 166 reviews

Learn how computers work, design efficient algorithms, and explore computational theory to solve real-world problems.

Software Development

3 hours

Course

Decoding Decision Modeling

  • BasicSkill Level
  • 4.7+
  • 170 reviews

Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.

Data Literacy

1 hour

Course

Introduction to Business Valuation

  • BasicSkill Level
  • 4.8+
  • 157 reviews

Learn business valuation with real-world applications and case studies using discounted cash flows (DCF).

Applied Finance

3 hours

Course

Introduction to Scala

  • IntermediateSkill Level
  • 4.8+
  • 135 reviews

Begin your journey with Scala, a popular language for scalable applications and data engineering infrastructure.

Software Development

3 hours

Course

Modeling with tidymodels in R

  • IntermediateSkill Level
  • 4.8+
  • 173 reviews

Learn to streamline your machine learning workflows with tidymodels.

Machine Learning

4 hours

Course

Writing Efficient Code with pandas

  • IntermediateSkill Level
  • 4.8+
  • 150 reviews

Learn efficient techniques in pandas to optimize your Python code.

Software Development

4 hours

Course

Building Chatbots in Python

  • IntermediateSkill Level
  • 4.7+
  • 145 reviews

Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.

Machine Learning

4 hours

Course

Inference for Numerical Data in R

  • AdvancedSkill Level
  • 4.8+
  • 100 reviews

In this course youll learn techniques for performing statistical inference on numerical data.

Probability & Statistics

4 hours

Course

Advanced Probability: Uncertainty in Data

  • AdvancedSkill Level
  • 4.8+
  • 147 reviews

Develop a better intuition for advanced probability, risk assessment, and simulation techniques to make data-driven business decisions with confidence.

Probability & Statistics

2 hours

Course

Inference for Categorical Data in R

  • AdvancedSkill Level
  • 4.8+
  • 107 reviews

In this course youll learn how to leverage statistical techniques for working with categorical data.

Probability & Statistics

4 hours

Course

Azure API Management

  • IntermediateSkill Level
  • 4.7+
  • 64 reviews

Learn to create, secure, and manage APIs with Azure API Management through hands-on practice.

Cloud

3 hours

Course

Case Study: Data Analysis in Databricks

  • AdvancedSkill Level
  • 4.6+
  • 83 reviews

Learn to analyze Airbnb data using SQL in Databricks, create dashboards, and derive actionable insights.

Importing & Cleaning Data

3 hours

Course

Develop for Azure Storage

  • IntermediateSkill Level
  • 4.7+
  • 76 reviews

Learn how to store, secure, scale, and process data in Azure using Blob Storage, Cosmos DB, queues, and event-driven services.

Cloud

3 hours

Course

Case Study: Exploratory Data Analysis in R

  • BasicSkill Level
  • 4.9+
  • 48 reviews

Use data manipulation and visualization skills to explore the historical voting of the United Nations General Assembly.

Exploratory Data Analysis

4 hours

Course

Introduction to Redshift

  • IntermediateSkill Level
  • 4.8+
  • 103 reviews

Master Amazon Redshifts SQL, data management, optimization, and security.

Data Engineering

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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