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528 Courses

Course

Streaming Data with AWS Kinesis and Lambda

  • AdvancedSkill Level
  • 4.7+
  • 176 reviews

Learn how to work with streaming data using serverless technologies on AWS.

Cloud

4 hours

Course

Market Basket Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 272 reviews

Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.

Machine Learning

4 hours

Course

Unsupervised Learning in R

  • IntermediateSkill Level
  • 4.7+
  • 106 reviews

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

Machine Learning

4 hours

Course

Machine Learning for Finance in Python

  • IntermediateSkill Level
  • 4.8+
  • 214 reviews

Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.

Machine Learning

4 hours

Course

Case Study: Analyzing Job Market Data in Tableau

  • BasicSkill Level
  • 4.7+
  • 570 reviews

In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.

Data Visualization

3 hours

Course

Time Series Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 276 reviews

Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.

Data Visualization

5 hours

Course

Supply Chain Analytics in Python

  • IntermediateSkill Level
  • 4.8+
  • 95 reviews

Leverage the power of Python and PuLP to optimize supply chains.

Exploratory Data Analysis

4 hours

Course

RNA-Seq with Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 146 reviews

Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.

Probability & Statistics

4 hours

Course

Improving Your Data Visualizations in Python

  • IntermediateSkill Level
  • 4.7+
  • 312 reviews

Learn to construct compelling and attractive visualizations that help communicate results efficiently and effectively.

Data Visualization

4 hours

Course

Forecasting in R

  • BasicSkill Level
  • 4.9+
  • 54 reviews

Learn how to make predictions about the future using time series forecasting in R including ARIMA models and exponential smoothing methods.

Probability & Statistics

5 hours

Course

Anomaly Detection in Python

  • IntermediateSkill Level
  • 4.8+
  • 179 reviews

Detect anomalies in your data analysis and expand your Python statistical toolkit in this four-hour course.

Probability & Statistics

4 hours

Course

Google: Enterprise Agents and Use Cases

  • BasicSkill Level
  • 4.8+
  • 87 reviews

Map agent types to your KPIs and explore use cases that solve problems, learn how Gemini Enterprise empowers you to build and orchestrate the right agents.

Cloud

45 min

Course

Introduction to MongoDB in Python

  • IntermediateSkill Level
  • 4.7+
  • 379 reviews

Learn to manipulate and analyze flexibly structured data with MongoDB.

Data Engineering

3 hours

Course

Monitor and Troubleshoot Azure Solutions

  • IntermediateSkill Level
  • 4.7+
  • 107 reviews

Learn how to monitor, diagnose, and optimize Azure applications using Azure Monitor, Application Insights, and Log Analytics.

Cloud

3 hours

Course

Case Study: Supply Chain Analytics in Power BI

  • BasicSkill Level
  • 4.8+
  • 191 reviews

Learn how to use Power BI for supply chain analytics in this case study. Create a make vs. buy analysis tool, calculate costs, and analyze production volumes.

Data Visualization

4 hours

Course

Importing Data in Java

  • IntermediateSkill Level
  • 4.7+
  • 97 reviews

Learn to import, manipulate, and transform data in Java using the Tablesaw library. Work with CSV files, tabular structures, and complex JSON formats.

Software Development

3 hours

Course

Using Data Stores in AWS

  • IntermediateSkill Level
  • 4.6+
  • 36 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

Decoding Decision Modeling

  • BasicSkill Level
  • 4.8+
  • 196 reviews

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

Data Literacy

1 hour

Course

Visualizing Geospatial Data in Python

  • IntermediateSkill Level
  • 4.7+
  • 350 reviews

Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.

Data Visualization

4 hours

Course

Ensemble Methods in Python

  • AdvancedSkill Level
  • 4.8+
  • 421 reviews

Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.

Machine Learning

4 hours

Course

Modeling with Data in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 236 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

Feature Engineering with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 303 reviews

Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.

Data Manipulation

4 hours

Course

Cleaning Data in Java

  • IntermediateSkill Level
  • 4.8+
  • 95 reviews

Master data cleaning in Java using statistical methods, transformations, and validation for reliable apps.

Importing & Cleaning Data

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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