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778 Courses

Course

AI-Assisted Product Launch

  • BasicSkill Level
  • 4.7+
  • 375 reviews

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

Artificial Intelligence

1 hour

Course

Serverless Applications with AWS Lambda

  • IntermediateSkill Level
  • 4.7+
  • 38 reviews

Build, deploy, and optimize serverless apps with AWS Lambda. Master event processing, error handling, concurrency, and safe deployments in a live AWS Console.

Cloud

3 hours

Course

Introduction to TensorFlow in Python

  • IntermediateSkill Level
  • 4.8+
  • 56 reviews

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

Machine Learning

4 hours

Course

Introduction to Data Versioning with DVC

  • IntermediateSkill Level
  • 4.7+
  • 408 reviews

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

Machine Learning

3 hours

Course

Data Modeling in Sigma

  • BasicSkill Level
  • 4.8+
  • 121 reviews

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

Reporting

2 hours

Course

Working with Geospatial Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 281 reviews

This course will show you how to integrate spatial data into your Python Data Science workflow.

Data Manipulation

4 hours

Course

Cleaning Data in PostgreSQL Databases

  • IntermediateSkill Level
  • 4.8+
  • 463 reviews

Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.

Data Preparation

4 hours

Course

Demystifying Decision Science

  • BasicSkill Level
  • 4.8+
  • 293 reviews

Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions.

Data Literacy

1 hour

Course

Graph RAG with LangChain and Neo4j

  • AdvancedSkill Level
  • 4.7+
  • 111 reviews

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

Artificial Intelligence

3 hours

Course

Building Web Applications with Shiny in R

  • IntermediateSkill Level
  • 4.7+
  • 223 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

Streaming Concepts

  • BasicSkill Level
  • 4.7+
  • 520 reviews

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

Data Engineering

2 hours

Course

Deep Reinforcement Learning in Python

  • AdvancedSkill Level
  • 4.8+
  • 279 reviews

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

Artificial Intelligence

4 hours

Course

Foundations of Probability in R

  • BasicSkill Level
  • 4.8+
  • 462 reviews

In this course, youll learn about the concepts of random variables, distributions, and conditioning.

Probability & Statistics

4 hours

Course

Case Study: Analyzing Job Market Data in Power BI

  • BasicSkill Level
  • 4.8+
  • 334 reviews

Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!

Data Manipulation

4 hours

Course

Databricks with the Python SDK

  • AdvancedSkill Level
  • 4.8+
  • 90 reviews

Master Databricks with Python: learn to authenticate, manage clusters, automate jobs, and query AI models programmatically.

Artificial Intelligence

3 hours

Course

Google: Build and Deploy Agents in Production

  • IntermediateSkill Level
  • 4.7+
  • 59 reviews

Explore multi-agent system architecture and deployment using Googles ADK and Google Cloud infrastructure for production-grade agent applications.

Cloud

30 min

Course

Corporate Finance Fundamentals

  • BasicSkill Level
  • 4.8+
  • 236 reviews

Learn key financial concepts such as capital investment, WACC, and shareholder value.

Applied Finance

2 hours

Course

Experimental Design in R

  • IntermediateSkill Level
  • 4.7+
  • 353 reviews

In this course youll learn about basic experimental design, a crucial part of any data analysis.

Probability & Statistics

4 hours

Course

Introduction to AWS Boto in Python

  • IntermediateSkill Level
  • 4.8+
  • 222 reviews

Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.

Cloud

4 hours

Course

AI-Assisted Restaurant Planning

  • BasicSkill Level
  • 4.8+
  • 388 reviews

Interact with a customized GPT and use your prompting skills to plan and open your restaurant.

Artificial Intelligence

1 hour

Course

Introduction to GCP

  • BasicSkill Level
  • 4.7+
  • 354 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

Calculations in Sigma

  • BasicSkill Level
  • 4.8+
  • 180 reviews

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

Data Manipulation

2 hours

Course

Reshaping Data with tidyr

  • IntermediateSkill Level
  • 4.8+
  • 471 reviews

Transform almost any dataset into a tidy format to make analysis easier.

Data Manipulation

4 hours

Course

Reporting with R Markdown

  • IntermediateSkill Level
  • 4.7+
  • 330 reviews

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

Reporting

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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