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85 Courses

Course

Working with Dates and Times in Python

  • IntermediateSkill Level
  • 4.7+
  • 2,514 reviews

Learn how to work with dates and times in Python.

Software Development

4 hours

Course

Introduction to Kubernetes

  • IntermediateSkill Level
  • 4.8+
  • 1,402 reviews

In this course, you will learn the fundamentals of Kubernetes and deploy and orchestrate containers using Manifests and kubectl instructions.

Software Development

3 hours

Course

Intermediate GitHub Concepts

  • IntermediateSkill Level
  • 4.7+
  • 1,823 reviews

Level up your GitHub skills with our intermediate course on GitHub Projects, Administration, and advanced security features.

Software Development

3 hours

Course

Advanced Git

  • AdvancedSkill Level
  • 4.7+
  • 933 reviews

Master Git’s advanced features to streamline data science and engineering workflows, from complex merging to large-scale project optimization.

Software Development

3 hours

Course

Introduction to Object-Oriented Programming in Java

  • IntermediateSkill Level
  • 4.8+
  • 963 reviews

Learn key object-oriented programming concepts, from basic classes and objects to advanced topics like inheritance and polymorphism.

Software Development

4 hours

Course

Intermediate Java

  • BasicSkill Level
  • 4.8+
  • 956 reviews

Learn to write cleaner, smarter Java code with methods, control flow, and loops.

Software Development

4 hours

Course

Introduction to Testing in Python

  • AdvancedSkill Level
  • 4.7+
  • 1,205 reviews

Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.

Software Development

4 hours

Course

DevOps Concepts

  • BasicSkill Level
  • 4.8+
  • 795 reviews

In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.

Software Development

4 hours

Course

Regular Expressions in Python

  • BasicSkill Level
  • 4.7+
  • 178 reviews

Learn about string manipulation and become a master at using regular expressions.

Software Development

4 hours

Course

Intermediate Docker

  • IntermediateSkill Level
  • 4.7+
  • 753 reviews

Master multi-stage builds, Docker networking tools, and Docker Compose for optimal containerized applications!

Software Development

4 hours

Course

Writing Efficient R Code

  • IntermediateSkill Level
  • 4.7+
  • 132 reviews

Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.

Software Development

4 hours

Course

Developing Python Packages

  • IntermediateSkill Level
  • 4.7+
  • 876 reviews

Learn to create your own Python packages to make your code easier to use and share with others.

Software Development

4 hours

Course

Introduction to Bash Scripting

  • IntermediateSkill Level
  • 4.8+
  • 432 reviews

Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.

Software Development

4 hours

Course

Intermediate SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 217 reviews

In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.

Software Development

4 hours

Course

Data Types and Exceptions in Java

  • IntermediateSkill Level
  • 4.8+
  • 478 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

Input/Output and Streams in Java

  • IntermediateSkill Level
  • 4.8+
  • 327 reviews

Advance your Java skills by learning to handle files, process data, and build clean, reusable code using real-world techniques.

Software Development

4 hours

Course

Building Web Applications with Shiny in R

  • IntermediateSkill Level
  • 4.7+
  • 212 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

Introduction to Optimization in Python

  • IntermediateSkill Level
  • 4.7+
  • 180 reviews

Learn to solve real-world optimization problems using Pythons SciPy and PuLP, covering everything from basic to constrained and complex optimization.

Software Development

4 hours

Course

Improving Query Performance in SQL Server

  • IntermediateSkill Level
  • 4.8+
  • 380 reviews

In this course, students will learn to write queries that are both efficient and easy to read and understand.

Software Development

4 hours

Course

String Manipulation with stringr in R

  • IntermediateSkill Level
  • 4.7+
  • 47 reviews

Learn how to pull character strings apart, put them back together and use the stringr package.

Software Development

4 hours

Course

Introduction to Julia

  • BasicSkill Level
  • 4.8+
  • 123 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

Optimizing Code in Java

  • AdvancedSkill Level
  • 4.8+
  • 141 reviews

Learn key techniques to optimize Java performance, from algorithm efficiency to JVM tuning and multithreading.

Software Development

3 hours

Course

Working with Dates and Times in R

  • IntermediateSkill Level
  • 4.8+
  • 87 reviews

Learn the essentials of parsing, manipulating and computing with dates and times in R.

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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