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63 Courses

Course

Introduction to Bioconductor in R

  • IntermediateSkill Level
  • 4.7+
  • 121 reviews

Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!

Probability & Statistics

4 hours

Course

Foundations of PySpark

  • IntermediateSkill Level
  • 4.7+
  • 618 reviews

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

Data Engineering

4 hours

Course

Data Processing in Shell

  • IntermediateSkill Level
  • 4.8+
  • 513 reviews

Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.

Data Manipulation

4 hours

Course

Data Fluency

  • BasicSkill Level
  • 4.8+
  • 303 reviews

Master data fluency! Learn skills for individuals and organizations, understand behaviors, and build a data-fluent culture.

Data Literacy

2 hours

Course

Introduction to Python in Power BI

  • IntermediateSkill Level
  • 4.8+
  • 147 reviews

Learn how to use Python scripts in Power BI for data prep, visualizations, and calculating correlation coefficients.

Data Manipulation

3 hours

Course

Improving Your Data Visualizations in Python

  • IntermediateSkill Level
  • 4.7+
  • 307 reviews

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

Data Visualization

4 hours

Course

Financial Analytics in Google Sheets

  • BasicSkill Level
  • 4.7+
  • 129 reviews

Learn how to build a graphical dashboard with Google Sheets to track the performance of financial securities.

Applied Finance

4 hours

Course

Introduction to Julia

  • BasicSkill Level
  • 4.8+
  • 132 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

Python for Spreadsheet Users

  • BasicSkill Level
  • 4.8+
  • 35 reviews

Use your knowledge of common spreadsheet functions and techniques to explore Python!

Software Development

4 hours

Course

Visualizing Time Series Data in R

  • IntermediateSkill Level
  • 4.8+
  • 182 reviews

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

Data Visualization

4 hours

Course

Financial Modeling in Google Sheets

  • IntermediateSkill Level
  • 4.7+
  • 275 reviews

Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Google Sheets.

Applied Finance

4 hours

Course

Optimizing R Code with Rcpp

  • IntermediateSkill Level
  • 4.9+
  • 12 reviews

Use C++ to dramatically boost the performance of your R code.

Software Development

4 hours

Course

Cleaning Data in R

  • IntermediateSkill Level
  • 4.7+
  • 813 reviews

Learn to clean data as quickly and accurately as possible to help you move from raw data to awesome insights.

Data Preparation

4 hours

Course

Data Strategy

  • BasicSkill Level
  • 4.7+
  • 1,769 reviews

Master strategic data management for business excellence.

Data Management

1 hour

Course

Data Types and Exceptions in Java

  • IntermediateSkill Level
  • 4.8+
  • 595 reviews

Learn to work with Plain Old Java Objects, master the Collections Framework, and handle exceptions like a pro, with logging to back it all up!

Software Development

4 hours

Course

Joining Data in SQL

  • BasicSkill Level
  • 4.7+
  • 23,221 reviews

Level up your SQL knowledge and learn to join tables together, apply relational set theory, and work with subqueries.

Data Manipulation

AI Tutor

2 hours 30 min

Course

Data Visualization in Power BI

  • BasicSkill Level
  • 4.8+
  • 10,212 reviews

Power BI is a powerful data visualization tool that can be used in reports and dashboards.

Data Visualization

3 hours

Course

Intermediate Python for Developers

  • BasicSkill Level
  • 4.8+
  • 8,291 reviews

Dive into the Python ecosystem, discovering modules and packages along with how to write custom functions!

Software Development

2 hours

Course

Intermediate Git

  • BasicSkill Level
  • 4.8+
  • 6,967 reviews

Discover branches and remote repos for version control in collaborative software and data projects using Git!

Software Development

2 hours

Course

Vibe Coding with Replit

  • BasicSkill Level
  • 4.8+
  • 870 reviews

Learn vibe coding with Replit. Build apps like a Typeform clone, and master securing and deploying Replit apps.

Artificial Intelligence

2 hours

Course

Introduction to SQL Querying with AI

  • BasicSkill Level
  • 4.8+
  • 614 reviews

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

Data Manipulation

3 hours

Course

Creating PostgreSQL Databases

  • BasicSkill Level
  • 4.8+
  • 638 reviews

Learn how to create a PostgreSQL database and explore the structure, data types, and how to normalize databases.

Data Preparation

4 hours

Course

Using Data Stores in AWS

  • IntermediateSkill Level
  • 4.7+
  • 32 reviews

Learn to choose, build with, and secure AWS data stores including DynamoDB and S3 through hands-on console exercises and real-world scenarios.

Cloud

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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