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711 Courses

Course

Foundations of PySpark

  • IntermediateSkill Level
  • 4.7+
  • 596 reviews

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

Data Engineering

4 hours

Course

Introduction to Julia

  • BasicSkill Level
  • 4.8+
  • 125 reviews

Julia is a new programming language designed to be the ideal language for scientific computing, machine learning, and data mining.

Software Development

4 hours

Course

Intermediate Importing Data in R

  • IntermediateSkill Level
  • 4.8+
  • 266 reviews

Parse data in any format. Whether its flat files, statistical software, databases, or data right from the web.

Data Preparation

3 hours

Course

Dealing with Missing Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 176 reviews

Learn how to identify, analyze, remove and impute missing data in Python.

Data Manipulation

4 hours

Course

Streaming Concepts

  • BasicSkill Level
  • 4.7+
  • 463 reviews

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

Data Engineering

2 hours

Course

Visualizing Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 171 reviews

Learn how to visualize time series in R, then practice with a stock-picking case study.

Data Visualization

4 hours

Course

Fraud Detection in Python

  • IntermediateSkill Level
  • 4.7+
  • 182 reviews

Learn how to detect fraud using Python.

Machine Learning

4 hours

Course

Case Study: Supply Chain Analytics in Power BI

  • BasicSkill Level
  • 4.8+
  • 175 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

Case Study: Analyzing Job Market Data in Tableau

  • BasicSkill Level
  • 4.7+
  • 526 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

Data Types and Functions in Snowflake

  • IntermediateSkill Level
  • 4.8+
  • 441 reviews

Learn Snowflake data types and functions to manipulate text, numbers, and dates while building custom functions and pivot tables.

Data Manipulation

3 hours

Course

Introduction to AWS Boto in Python

  • IntermediateSkill Level
  • 4.8+
  • 199 reviews

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

Cloud

4 hours

Course

Understanding Digital Transformation

  • BasicSkill Level
  • 4.8+
  • 514 reviews

Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.

Data Literacy

1 hour

Course

Feature Engineering with PySpark

  • AdvancedSkill Level
  • 4.8+
  • 285 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

Corporate Finance Fundamentals

  • BasicSkill Level
  • 4.8+
  • 210 reviews

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

Applied Finance

2 hours

Course

Graph RAG with LangChain and Neo4j

  • AdvancedSkill Level
  • 4.7+
  • 92 reviews

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

Artificial Intelligence

3 hours

Course

Fully Automated MLOps

  • IntermediateSkill Level
  • 4.8+
  • 314 reviews

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

Machine Learning

4 hours

Course

Multi-Modal Systems with the OpenAI API

  • IntermediateSkill Level
  • 4.8+
  • 419 reviews

Create multi-modal systems using OpenAIs text and audio models, including an end-to-end customer support chatbot!

Artificial Intelligence

2 hours

Course

Monitoring Machine Learning Concepts

  • IntermediateSkill Level
  • 4.7+
  • 435 reviews

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

Machine Learning

2 hours

Course

Conquering Data Bias

  • BasicSkill Level
  • 4.7+
  • 215 reviews

Unlock your datas potential by learning to detect and mitigate bias for precise analysis and reliable models.

Data Management

2 hours

Course

Introduction to GCP

  • BasicSkill Level
  • 4.7+
  • 324 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

ARIMA Models in Python

  • AdvancedSkill Level
  • 4.8+
  • 380 reviews

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

Machine Learning

4 hours

Course

Improving Your Data Visualizations in Python

  • IntermediateSkill Level
  • 4.7+
  • 276 reviews

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

Data Visualization

4 hours

Course

Spoken Language Processing in Python

  • AdvancedSkill Level
  • 4.8+
  • 247 reviews

Learn how to load, transform, and transcribe speech from raw audio files in Python.

Data Manipulation

4 hours

Course

AI-Assisted Travel Planning

  • BasicSkill Level
  • 4.8+
  • 420 reviews

Master travel planning with WanderBot: craft prompts, build confidence, and streamline your next adventure.

Artificial Intelligence

1 hour

Course

Introduction to Databricks Genie

  • BasicSkill Level
  • 4.8+
  • 48 reviews

Ask data questions in plain English with Databricks Genie - build spaces, curate business language, and monitor quality.

Data Engineering

2 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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Make progress on the go with our mobile courses and daily 5-minute coding challenges.