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711 Courses

Course

Practicing Machine Learning Interview Questions in Python

  • AdvancedSkill Level
  • 4.8+
  • 105 reviews

Sharpen your knowledge and prepare for your next interview by practicing Python machine learning interview questions.

Machine Learning

4 hours

Course

Network Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 119 reviews

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

Probability & Statistics

4 hours

Course

Statistical Thinking in Python (Part 2)

  • IntermediateSkill Level
  • 4.7+
  • 244 reviews

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Probability & Statistics

4 hours

Course

Case Study: Exploratory Data Analysis in R

  • BasicSkill Level
  • 4.9+
  • 47 reviews

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

Exploratory Data Analysis

4 hours

Course

Survival Analysis in R

  • IntermediateSkill Level
  • 4.7+
  • 179 reviews

Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!

Probability & Statistics

4 hours

Course

Cleaning Data in SQL Server Databases

  • IntermediateSkill Level
  • 4.8+
  • 173 reviews

Develop the skills you need to clean raw data and transform it into accurate insights.

Data Preparation

4 hours

Course

Marketing Analytics in Google Sheets

  • IntermediateSkill Level
  • 4.8+
  • 214 reviews

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

Reporting

4 hours

Course

Azure Compute Solutions

  • IntermediateSkill Level
  • 4.7+
  • 91 reviews

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

Cloud

3 hours

Course

Building Chatbots in Python

  • IntermediateSkill Level
  • 4.7+
  • 143 reviews

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

Machine Learning

4 hours

Course

Introduction to Spark with sparklyr in R

  • IntermediateSkill Level
  • 4.7+
  • 79 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

Categorical Data in the Tidyverse

  • BasicSkill Level
  • 4.7+
  • 160 reviews

Get ready to categorize! In this course, you will work with non-numerical data, such as job titles or survey responses, using the Tidyverse landscape.

Data Manipulation

4 hours

Course

Modeling with tidymodels in R

  • IntermediateSkill Level
  • 4.8+
  • 166 reviews

Learn to streamline your machine learning workflows with tidymodels.

Machine Learning

4 hours

Course

Introduction to Redshift

  • IntermediateSkill Level
  • 4.8+
  • 101 reviews

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

Data Engineering

4 hours

Course

Scalable AI Models with PyTorch Lightning

  • IntermediateSkill Level
  • 4.7+
  • 90 reviews

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

Artificial Intelligence

3 hours

Course

Introduction to Business Valuation

  • BasicSkill Level
  • 4.8+
  • 153 reviews

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

Applied Finance

3 hours

Course

Writing Efficient Code with pandas

  • IntermediateSkill Level
  • 4.8+
  • 147 reviews

Learn efficient techniques in pandas to optimize your Python code.

Software Development

4 hours

Course

Generalized Linear Models in Python

  • AdvancedSkill Level
  • 4.7+
  • 141 reviews

Extend your regression toolbox with the logistic and Poisson models and learn to train, understand, and validate them, as well as to make predictions.

Probability & Statistics

5 hours

Course

Time Series Analysis in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 152 reviews

In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.

Data Visualization

2 hours

Course

Concepts in Computer Science

  • BasicSkill Level
  • 4.7+
  • 163 reviews

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

Software Development

3 hours

Course

Using Data Stores in AWS

  • IntermediateSkill Level
  • 4.7+
  • 23 reviews

Learn to choose, build with, and secure AWS data stores including DynamoDB and S3 through hands-on console exercises and real-world scenarios.

Cloud

3 hours

Course

Machine Learning for Marketing in Python

  • IntermediateSkill Level
  • 4.8+
  • 164 reviews

From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.

Machine Learning

4 hours

Course

Data Transformation in KNIME

  • BasicSkill Level
  • 4.8+
  • 279 reviews

Enhance your KNIME skills with our course on data transformation, column operations, and workflow optimization.

Data Preparation

2 hours

Course

Azure API Management

  • IntermediateSkill Level
  • 4.7+
  • 61 reviews

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

Cloud

3 hours

Course

Marketing Analytics in Tableau

  • IntermediateSkill Level
  • 4.8+
  • 84 reviews

Master marketing analytics using Tableau. Analyze performance, benchmark metrics, and optimize strategies across channels.

Data Preparation

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