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774 Courses

Course

Introduction to MongoDB in Python

  • IntermediateSkill Level
  • 4.7+
  • 388 reviews

Learn to manipulate and analyze flexibly structured data with MongoDB.

Data Engineering

3 hours

Course

Advanced Data Engineering with Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 30 reviews

Build reliable Snowflake pipelines with DevOps and observability: Git, CI/CD, and Snowflake Trail monitoring.

Data Engineering

3 hours

Course

Importing Data in Java

  • IntermediateSkill Level
  • 4.7+
  • 114 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

Biomedical Image Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 240 reviews

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

Data Manipulation

4 hours

Course

Generative AI Essentials with Snowflake

  • IntermediateSkill Level
  • 4.6+
  • 18 reviews

Build generative AI apps on Snowflake with Cortex LLM functions, prompt engineering, and fine-tuning.

Artificial Intelligence

3 hours

Course

Cleaning Data in Java

  • IntermediateSkill Level
  • 4.7+
  • 110 reviews

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

Importing & Cleaning Data

4 hours

Course

Bayesian Data Analysis in Python

  • IntermediateSkill Level
  • 4.7+
  • 266 reviews

Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!

Probability & Statistics

4 hours

Course

Deep Reinforcement Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 284 reviews

Learn and use powerful Deep Reinforcement Learning algorithms, including refinement and optimization techniques.

Artificial Intelligence

4 hours

Course

Case Study: Building Software in Python

  • AdvancedSkill Level
  • 4.7+
  • 307 reviews

Build real-world applications with Python—practice using OOP and software engineering principles to write clean and maintainable code.

Software Development

3 hours

Course

Building AI Agents with CrewAI

  • IntermediateSkill Level
  • 4.8+
  • 108 reviews

Build AI teams that work together, automate workflows, and generate content with CrewAI.

Artificial Intelligence

1 hour

Course

Case Study: Analyzing Job Market Data in Tableau

  • BasicSkill Level
  • 4.7+
  • 578 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

Introduction to Python in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 151 reviews

Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.

Data Manipulation

3 hours

Course

Introduction to Optimization in Python

  • IntermediateSkill Level
  • 4.7+
  • 206 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

Machine Learning for Finance in Python

  • IntermediateSkill Level
  • 4.8+
  • 220 reviews

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

Machine Learning

4 hours

Course

Supply Chain Analytics in Python

  • IntermediateSkill Level
  • 4.8+
  • 97 reviews

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

Exploratory Data Analysis

4 hours

Course

Reporting with R Markdown

  • IntermediateSkill Level
  • 4.7+
  • 331 reviews

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

Reporting

4 hours

Course

Time Series Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 280 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

Unsupervised Learning in R

  • IntermediateSkill Level
  • 4.7+
  • 107 reviews

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

Machine Learning

4 hours

Course

Financial Analytics in Google Sheets

  • BasicSkill Level
  • 4.7+
  • 135 reviews

Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.

Applied Finance

4 hours

Course

RNA-Seq with Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 147 reviews

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

Probability & Statistics

4 hours

Course

Working with Dates and Times in R

  • IntermediateSkill Level
  • 4.8+
  • 98 reviews

Learn the essentials of parsing, manipulating and computing with dates and times in R.

Software Development

4 hours

Course

Case Study: Supply Chain Analytics in Power BI

  • BasicSkill Level
  • 4.8+
  • 194 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

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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