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294 Courses

Course

Streamlined Data Ingestion with pandas

  • IntermediateSkill Level
  • 4.8+
  • 1,738 reviews

Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.

Data Preparation

4 hours

Course

Joining Data with dplyr

  • BasicSkill Level
  • 4.7+
  • 1,192 reviews

Learn to combine data across multiple tables to answer more complex questions with dplyr.

Data Manipulation

4 hours

Course

Data Science for Business

  • BasicSkill Level
  • 4.8+
  • 926 reviews

Learn about data science for managers and businesses and how to use data to strengthen your organization.

Data Literacy

2 hours

Course

Case Study: Analyzing Customer Churn in Tableau

  • BasicSkill Level
  • 4.8+
  • 922 reviews

You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.

Data Visualization

3 hours

Course

Data Visualization in Databricks

  • BasicSkill Level
  • 4.7+
  • 572 reviews

Create visualizations and dynamic dashboards with Databricks, turning raw data into clear and actionable insights.

Data Visualization

3 hours

Course

Analyzing Survey Data in R

  • IntermediateSkill Level
  • 4.8+
  • 204 reviews

Learn survey design using common design structures followed by visualizing and analyzing survey results.

Probability & Statistics

4 hours

Course

Analyzing Social Media Data in Python

  • IntermediateSkill Level
  • 4.8+
  • 31 reviews

In this course, youll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

Data Manipulation

4 hours

Course

Data Manipulation in KNIME

  • BasicSkill Level
  • 4.8+
  • 242 reviews

Automate data manipulation with KNIME, mastering merging, aggregation, database workflows, and advanced file handling.

Data Manipulation

3 hours

Course

Analyzing Survey Data in Python

  • IntermediateSkill Level
  • 4.6+
  • 50 reviews

Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.

Probability & Statistics

4 hours

Course

Case Study: Analyzing Fitness Data in Alteryx

  • IntermediateSkill Level
  • 4.8+
  • 53 reviews

Advance your Alteryx skills with real fitness data to develop targeted marketing strategies and innovative products!

Data Preparation

3 hours

Course

Scalable Data Processing in R

  • AdvancedSkill Level
  • 4.6+
  • 22 reviews

Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.

Software Development

4 hours

Course

Predictive Analytics using Networked Data in R

  • IntermediateSkill Level
  • 4.8+
  • 31 reviews

Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network

Probability & Statistics

4 hours

Course

Introduction to Tableau

  • BasicSkill Level
  • 4.8+
  • 5,016 reviews

Start your Tableau journey with our Introduction to Tableau course. Discover Tableau basics such as its features and dashboards.

Data Visualization

6 hours

Course

Introduction to Databricks

  • BasicSkill Level
  • 4.7+
  • 3,210 reviews

Learn about the Databricks Lakehouse platform and how it can modernize data architectures and improve data management processes.

Data Engineering

3 hours

Course

Introduction to Snowflake

  • BasicSkill Level
  • 4.8+
  • 3,888 reviews

Snowflake is a top data warehousing platform. Learn how they use Snowsight, a user-friendly SQL interface for accessing and exploring data.

Data Warehouse

2 hours

Course

Creating Dashboards in Tableau

  • BasicSkill Level
  • 4.8+
  • 1,374 reviews

Dashboards are a must-have in a data-driven world. Increase your impact on business performance with Tableau dashboards.

Data Visualization

3 hours

Course

Introduction to SQL Querying with AI

  • BasicSkill Level
  • 4.8+
  • 522 reviews

Learn SQL Querying with AI by writing prompts, generating queries, and analyzing data to solve real-world problems.

Data Manipulation

3 hours

Course

Introduction to NoSQL

  • BasicSkill Level
  • 4.8+
  • 770 reviews

Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.

Data Engineering

4 hours

Course

Introduction to MongoDB in Python

  • IntermediateSkill Level
  • 4.7+
  • 352 reviews

Learn to manipulate and analyze flexibly structured data with MongoDB.

Data Engineering

3 hours

Course

Pivot Tables in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 212 reviews

Learn how to create pivot tables and quickly organize thousands of data points with just a few clicks.

Data Manipulation

2 hours

Course

Introduction to Redshift

  • IntermediateSkill Level
  • 4.8+
  • 101 reviews

Master Amazon Redshifts SQL, data management, optimization, and security.

Data Engineering

4 hours

Course

Conditional Formatting in Google Sheets

  • BasicSkill Level
  • 4.8+
  • 89 reviews

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

Data Manipulation

2 hours

Course

Programming with dplyr

  • IntermediateSkill Level
  • 4.7+
  • 47 reviews

Learn how to perform advanced dplyr transformations and incorporate dplyr and ggplot2 code in functions.

Data Manipulation

4 hours

Course

Introduction to Statistics

  • BasicSkill Level
  • 4.8+
  • 8,399 reviews

Learn the fundamentals of statistics, including measures of center and spread, probability distributions, and hypothesis testing with no coding involved!

Probability & Statistics

4 hours

Course

PostgreSQL Summary Stats and Window Functions

  • IntermediateSkill Level
  • 4.7+
  • 7,010 reviews

Learn how to create queries for analytics and data engineering with window functions, the SQL secret weapon!

Software Development

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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