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771 Courses

Course

Data Visualization in KNIME

  • BasicSkill Level
  • 4.8+
  • 199 reviews

Learn to create compelling data visualizations with KNIME, covering charts, components, and dashboards.

Data Visualization

2 hours

Course

Building Dashboards with shinydashboard

  • BasicSkill Level
  • 4.6+
  • 75 reviews

Learn to create interactive dashboards with R using the powerful shinydashboard package. Create dynamic and engaging visualizations for your audience.

Reporting

4 hours

Course

Developing R Packages

  • IntermediateSkill Level
  • 4.7+
  • 146 reviews

Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.

Software Development

4 hours

Course

Hyperparameter Tuning in R

  • AdvancedSkill Level
  • 4.8+
  • 57 reviews

Learn how to tune your models hyperparameters to get the best predictive results.

Machine Learning

4 hours

Course

Discrete Event Simulation in Python

  • AdvancedSkill Level
  • 4.7+
  • 70 reviews

Discover the power of discrete-event simulation in optimizing your business processes. Learn to develop digital twins using Pythons SimPy package.

Probability & Statistics

4 hours

Course

Case Studies in Statistical Thinking

  • IntermediateSkill Level
  • 4.9+
  • 81 reviews

Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.

Probability & Statistics

4 hours

Course

Case Study: Ecommerce Analysis in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 63 reviews

In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, youll investigate data from an online pet supply company.

Data Visualization

3 hours

Course

Introduction to Power Apps

  • BasicSkill Level
  • 5
  • 1 review

Build custom business apps without code using Microsoft Power Apps - from blank canvas to published, responsive app.

Artificial Intelligence

3 hours

Course

GARCH Models in R

  • AdvancedSkill Level
  • 4.8+
  • 95 reviews

Specify and fit GARCH models to forecast time-varying volatility and value-at-risk.

Applied Finance

4 hours

Course

Case Study: Supply Chain Analytics in Tableau

  • IntermediateSkill Level
  • 4.8+
  • 70 reviews

Dive into our Tableau case study on supply chain analytics. Tackle shipment, inventory management, and dashboard creation to drive business improvements.

Data Visualization

4 hours

Course

MLOps for Business

  • BasicSkill Level
  • 4.8+
  • 143 reviews

Learn about MLOps, including the tools and practices needed for automating and scaling machine learning applications.

Machine Learning

3 hours

Course

Python for MATLAB Users

  • BasicSkill Level
  • 4.8+
  • 30 reviews

Transition from MATLAB by learning some fundamental Python concepts, and diving into the NumPy and Matplotlib packages.

Software Development

4 hours

Course

Working with DeepSeek in Python

  • BasicSkill Level
  • 4.7+
  • 99 reviews

Discover what all of the DeepSeek hype was really about! Build applications using DeepSeeks R1 and V3 models.

Artificial Intelligence

3 hours

Course

Parallel Programming with Dask in Python

  • IntermediateSkill Level
  • 4.8+
  • 62 reviews

Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.

Software Development

4 hours

Course

Building Data Pipelines with Airflow

  • AdvancedSkill Level
  • 4.8+
  • 5 reviews

Author Dags with the TaskFlow API, asset-based scheduling, and deferrable sensors, and run an end-to-end SQL ETL pipeline with quality checks.

Data Engineering

4 hours

Course

Google: Deploy Your First Agent

  • IntermediateSkill Level
  • 5
  • 14 reviews

Deploy ADK agents to production using Vertex AI Agent Engine and Cloud Run. Add persistent cross-session memory with Memory Bank.

Cloud

1 hour

Course

Analyzing US Census Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 62 reviews

Learn to use the Census API to work with demographic and socioeconomic data.

Exploratory Data Analysis

5 hours

Course

Conditional Formatting in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 98 reviews

Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.

Data Manipulation

2 hours

Course

Case Study: Inventory Analysis in Tableau

  • IntermediateSkill Level
  • 4.7+
  • 62 reviews

Enhance your Tableau skills with this case study on inventory analysis. Analyze a dataset, create calculated fields, and create visualizations.

Data Visualization

2 hours

Course

Google Cloud Fundamentals: Core Infrastructure

  • BasicSkill Level
  • 4.8+
  • 7 reviews

Learn Google Cloud essentials including computing, storage, networking, and resource management through videos and hands-on labs in this foundational course.

Cloud

5 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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