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779 Courses

Course

Dealing With Missing Data in R

  • BasicSkill Level
  • 4.7+
  • 162 reviews

Make it easy to visualize, explore, and impute missing data with naniar, a tidyverse friendly approach to missing data.

Data Preparation

4 hours

Course

Introduction to GCP

  • BasicSkill Level
  • 4.7+
  • 374 reviews

Get to know the Google Cloud Platform (GCP) with this course on storage, data handling, and business modernization using GCP.

Cloud

2 hours

Course

Streaming Concepts

  • BasicSkill Level
  • 4.7+
  • 559 reviews

Learn about the difference between batching and streaming, scaling streaming systems, and real-world applications.

Data Engineering

2 hours

Course

Modeling with Data in the Tidyverse

  • IntermediateSkill Level
  • 4.8+
  • 250 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

Cleaning Data in Java

  • IntermediateSkill Level
  • 4.7+
  • 130 reviews

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

Importing & Cleaning Data

4 hours

Course

Introduction to MongoDB in Python

  • IntermediateSkill Level
  • 4.7+
  • 403 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+
  • 142 reviews

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

Cloud

3 hours

Course

Building Web Applications with Shiny in R

  • IntermediateSkill Level
  • 4.7+
  • 231 reviews

Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.

Software Development

4 hours

Course

Statistical Techniques in Tableau

  • IntermediateSkill Level
  • 4.8+
  • 717 reviews

Take your reporting skills to the next level with Tableau’s built-in statistical functions.

Probability & Statistics

4 hours

Course

Introduction to TensorFlow in Python

  • IntermediateSkill Level
  • 4.8+
  • 57 reviews

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

Machine Learning

4 hours

Course

Foundations of PySpark

  • IntermediateSkill Level
  • 4.7+
  • 645 reviews

Learn to implement distributed data management and machine learning in Spark using the PySpark package.

Data Engineering

4 hours

Course

Sentiment Analysis in Python

  • IntermediateSkill Level
  • 4.8+
  • 481 reviews

Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.

Machine Learning

4 hours

Course

Auditing Expenses with Claude Cowork

  • IntermediateSkill Level
  • 4.7+
  • 24 reviews

Bored of pouring over expenses to figure out which ones violate policy? No longer! Use Claude Cowork to produce fast and clear expense violation reports.

Artificial Intelligence

15 min

Course

AI-Assisted Product Launch

  • BasicSkill Level
  • 4.7+
  • 409 reviews

Analyze market dynamics and craft a strategic entry plan for an EV manufacturer using generative AI.

Artificial Intelligence

1 hour

Course

Introduction to Data Engineering on Google Cloud

  • BasicSkill Level
  • 4.8+
  • 45 reviews

Learn the data engineering role on Google Cloud. Explore data sources, storage solutions, ETL/ELT architectures, BigQuery, Dataform, and Dataproc.

Cloud

3 hours 41 min

Course

Data Modeling in Sigma

  • BasicSkill Level
  • 4.8+
  • 151 reviews

Stop rewriting the same joins and calculations, and dive into well-governed, scalable analytics using Sigma data models.

Reporting

2 hours

Course

Introduction to Generative AI in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 385 reviews

Learn to build AI applications using Snowflake Cortexs built-in LLM functions for text analysis, generation, and multi-step workflows.

Artificial Intelligence

2 hours

Course

Recommending Skincare Products

  • BasicSkill Level
  • 4.7+
  • 324 reviews

Test a chatbot that matches customers with ideal skincare products using your prompting skills for personalized results.

Artificial Intelligence

1 hour

Course

Time Series Analysis in Power BI

  • IntermediateSkill Level
  • 4.7+
  • 296 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

Calculations in Sigma

  • BasicSkill Level
  • 4.8+
  • 224 reviews

Build dynamic Sigma calculations to explore data, automate logic, and uncover trends with practical business examples.

Data Manipulation

2 hours

Course

Introduction to AI Apps in Sigma

  • BasicSkill Level
  • 4.8+
  • 201 reviews

Build interactive AI apps in Sigma using user input, actions, and polished interfaces, no coding required.

Reporting

2 hours

Course

ARIMA Models in Python

  • AdvancedSkill Level
  • 4.8+
  • 437 reviews

Learn about ARIMA models in Python and become an expert in time series analysis.

Machine Learning

4 hours

Course

Fine-Tuning with Llama 3

  • IntermediateSkill Level
  • 4.7+
  • 418 reviews

Fine-tune Llama for custom tasks using TorchTune, and learn techniques for efficient fine-tuning such as quantization.

Artificial Intelligence

2 hours

Course

Case Study: Analyzing Job Market Data in Tableau

  • BasicSkill Level
  • 4.7+
  • 614 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

Graph RAG with LangChain and Neo4j

  • AdvancedSkill Level
  • 4.7+
  • 128 reviews

Create more accurate and reliable RAG systems with Graph RAG and hybrid RAG.

Artificial Intelligence

3 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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