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294 Courses

Course

Introduction to Natural Language Processing in R

  • IntermediateSkill Level
  • 4.8+
  • 40 reviews

Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.

Machine Learning

4 hours

Course

DataLab with SQL

  • BasicSkill Level
  • 4.8+
  • 41 reviews

Elevate your analysis with this hands-on course using SQL with DataLab workbooks.

Reporting

1 hour

Course

Intermediate Regular Expressions in R

  • IntermediateSkill Level
  • 4.8+
  • 33 reviews

Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.

Software Development

4 hours

Course

Introduction to Regression with statsmodels in Python

  • IntermediateSkill Level
  • 4.8+
  • 2,763 reviews

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

Probability & Statistics

4 hours

Course

Data-Driven Decision Making for Business

  • BasicSkill Level
  • 4.8+
  • 871 reviews

Discover how to make better business decisions by applying practical data frameworks—no coding required.

Leadership

2 hours

Course

Cleaning Data in PostgreSQL Databases

  • IntermediateSkill Level
  • 4.8+
  • 438 reviews

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

Data Preparation

4 hours

Course

Case Study: Analyzing Job Market Data in Power BI

  • BasicSkill Level
  • 4.8+
  • 313 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

Cleaning Data in SQL Server Databases

  • IntermediateSkill Level
  • 4.8+
  • 176 reviews

Develop the skills you need to clean raw data and transform it into accurate insights.

Data Preparation

4 hours

Course

Data Visualization in Tableau

  • BasicSkill Level
  • 4.7+
  • 798 reviews

Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.

Data Visualization

6 hours

Course

Introduction to Databases in Python

  • IntermediateSkill Level
  • 4.7+
  • 261 reviews

In this course, youll learn the basics of relational databases and how to interact with them.

Data Manipulation

4 hours

Course

Data Transformation in Alteryx

  • BasicSkill Level
  • 4.8+
  • 742 reviews

Unlock Alteryx for data transformation, mastering Crosstab, Transpose, and workflow optimization in this interactive course.

Data Manipulation

2 hours

Course

Intermediate SQL

  • BasicSkill Level
  • 4.8+
  • 34,973 reviews

Accompanied at every step with hands-on practice queries, this course teaches you everything you need to know to analyze data using your own SQL code today!

Data Manipulation

AI Native

5 hours

Course

Intermediate dbt

  • AdvancedSkill Level
  • 4.7+
  • 898 reviews

Take your dbt skills to the next level with this hands-on course designed for data engineers and analytics professionals.

Data Engineering

2 hours

Course

Web Scraping in Python

  • IntermediateSkill Level
  • 4.7+
  • 1,015 reviews

Learn to retrieve and parse information from the internet using the Python library scrapy.

Data Preparation

4 hours

Course

Analyzing Police Activity with pandas

  • IntermediateSkill Level
  • 4.8+
  • 25 reviews

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

Data Manipulation

4 hours

Course

Case Study: Analyzing Customer Churn in Power BI

  • BasicSkill Level
  • 4.8+
  • 6,554 reviews

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

Data Visualization

3 hours

Course

Forming Analytical Questions

  • BasicSkill Level
  • 4.8+
  • 3,680 reviews

Learn how to translate business questions to well-formed analytical questions and select the right analytical solutions.

Data Literacy

1 hour

Course

Data Communication Concepts

  • BasicSkill Level
  • 4.7+
  • 5,229 reviews

No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.

Data Literacy

3 hours

Course

Introduction to Data Science in Python

  • BasicSkill Level
  • 4.8+
  • 464 reviews

Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.

Software Development

4 hours

Course

Case Study: Analyzing Customer Churn in Excel

  • BasicSkill Level
  • 4.8+
  • 2,726 reviews

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

Reporting

1 hour

Course

Cleaning Data with Generative AI

  • BasicSkill Level
  • 4.7+
  • 1,375 reviews

Use generative AI to tackle data cleaning, fixing duplicates, nulls, and formatting for consistent, accurate datasets.

Artificial Intelligence

1 hour

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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