Delve deep into the world of data science and learn about the essential tools and software required to succeed in this field. Explore the key responsibilities and roles of a data scientist, and understand the significance of Python, SQL, and data visualization tools in enhancing your data science skills.

Key Insights

  • Data scientists are responsible for extracting valuable information from raw data, developing machine learning algorithms, automating collection processes, and creating data visualizations for stakeholders across an array of industries.
  • Python is a foundational programming language for data scientists, enabling them to gather data, predict outcomes, automate tasks, and create data visualizations and interactive dashboards.
  • SQL (Standard Query Language) is an essential tool for data scientists used to retrieve and filter data from databases.
  • Data visualization tools like Matplotlib and Tableau are crucial for presenting findings and recommendations to stakeholders within an organization in a visually appealing manner.
  • Becoming a data scientist involves a well-rounded learning program that includes developing soft skills like collaboration and communication, along with gaining business knowledge.
  • Noble Desktop offers several in-person and live online data science classes, such as the Python for Data Science Bootcamp and the Data Science Certificate program, which include hands-on experience, real-time guidance from an expert instructor, and job search assistance.

The work of a Data Scientist is rooted in data science tools and software that enable Data Scientists to gather, process, manage, analyze, and derive information from data. Understanding the tools and software Data Scientists use will help you learn the necessary skills to succeed in your career. The sections below take a closer look at the tools and software used by Data Scientists and how you can learn them.

What is a Data Scientist?

Data Scientists extract meaning from raw data to detect patterns and propose solutions that meet an organization’s needs, especially the needs to compete and grow. A Data Scientist’s responsibilities include finding valuable data from data sources, developing machine learning algorithms, improving data collection procedures, cleansing and validating data integrity to ensure accuracy, and detecting patterns and solutions based on data. Data Scientists build models based on data, create data visualizations that communicate patterns and findings to stakeholders, and automate collection processes. Because data plays a critical role in the success of any organization, Data Scientists can build careers in business, technology, finance, nonprofits, and many other industries. 

Those who wish to become a Data Scientist should develop the analytical, statistical, and programming skills needed to manage and interpret raw data. These skills include understanding statistics, machine learning, and reporting tools. Aspiring Data Scientists also benefit from understanding the programming languages R, SQL, Python, Java, and C++. 

Read more about what a Data Scientist does.

What Tools and Software Do Data Scientists Use?

Data Scientists rely on tools that help them gather, process, analyze, and leverage data sets to help organizations meet their goals. Such tools include programming languages like Python and its libraries, SQL, and data visualization tools like Tableau and Matplotlib.

Python

Python might be the most essential programming language for any aspiring Data Scientist to learn. The Python programming language and its libraries enable Data Scientists to gather and access data, predict future outcomes, leverage automation and machine learning, create data visualizations and interactive dashboards, and more.

To understand the data science applications of Python, you must first gain a foundational understanding of the programming language. Python is considered a beginner-friendly programming language, even for those without prior programming knowledge or experience. That said, learning any programming language alone can prove challenging and frustrating, so it helps to have an instructor who can answer your questions, guide you through hands-on activities, teach you best practices, and provide feedback on your work. 

Python’s data science uses include: 

Data Scientists may also work closely with programmers who use Python, so knowing Python can also serve as a valuable skill for understanding and collaborating with coworkers.

SQL

SQL stands for Standard Query Language. SQL enables Data Scientists to explore databases, retrieve data from the databases’ tables, combine information from tables, and filter, group, and sort data to identify useful and relevant information. 

Data Visualization Tools

Data Scientists frequently present their findings and recommendations to stakeholders within the organization. They must therefore know how to present data in visual forms such as charts and graphs. Data Scientists primarily use the Python library Matplotlib or a software tool such as Tableau to create data visualizations and interactive dashboards. Understanding how to create and leverage data visualizations will enable you to: 

How to Learn Data Science Tools and Software

There are three main methods of learning data science tools and software. You can learn by exploring free and on-demand resources or learn from an instructor through an in-person or live online data science course. This section will explore each of these options in depth.

Self-led/Self-paced Learning

If you are just starting to explore data science professions and want to learn more without committing to a paid option, you may wish to start with free learning resources. Such resources can help you gain a high-level understanding of the skills and tools needed to become a Data Scientist, but do have their limitations. The Noble Desktop Data Learn Hub provides ways you can start learning for free.

An affordable way to start learning skills such as Python programming, SQL, and data visualization is with on-demand/self-paced courses like those found on LinkedIn Learning, Skillshare, Udemy, and Coursera. These resources will often take you further than free resources. Because you choose the time and pace at which you learn, on-demand data science classes are flexible and convenient. They do have one major limitation, however, which is limited access to an instructor. Some courses may offer email support for asking questions of your instructor, but this means that you are stuck waiting for a reply, halting your progress for hours or even days. Some self-paced courses may offer no instructor support at all. 

For most people, the most effective way to learn the tools and software used by Data Scientists is to enroll in an instructor-led class.

In-person Data Science Classes

In-person data science classes meet at a physical location that allows you to work with classmates and your instructor face-to-face. This method works well for students who benefit from learning in a more traditional manner. In-person class locations also provide all necessary equipment and software, so you don’t have to worry about setting up your computer or purchasing necessary tools. 

When researching in-person data science classes, look for classes that feature hands-on experience. Lectures and demonstrations provide the facts of data science, but hands-on experience helps to retain the information and is crucial to understanding the real-world work of a Data Scientist. Working on assignments also allows you to collaborate with classmates and develop your teamwork. Your instructor can offer real-time guidance and personalized feedback. You can also use these projects to assemble a professional portfolio.

Because in-person data science classes combine lectures, presentations, and hands-on projects, they benefit all types of learners, such as auditory, visual, and tactile learners. Most people benefit from a combined teaching method, which an in-person class can provide.

In-person classes also consist of local students and instructors, allowing you to network with professionals in your area.

Other benefits to look for when researching in-person data science classes are programs with flexible financing options, one-on-one mentoring, job search assistance, and a free retake option.

In-person classes meet at a designated time, so look for a class that suits your schedule. You will also need to set aside time for any assignments required outside of class and the time needed to commute to the physical learning location.

Live Online Data Science Classes

Live online data science classes offer several of the same benefits as in-person classes, including: 

Live online data science classes have the added benefit of allowing you to learn remotely. Not only does this mean you can skip the commute and learn from home. It also means you take classes offered by schools around the world. Unlike in-person classes, in which your options are dictated by the offerings in your local area, you can choose to enroll in almost any virtual class that meets your needs.

If you want to focus on developing a specific skill, you can look for classes that center on that skill, but to become a Data Scientist, you will need a well-rounded learning program. Programs like Noble Desktop’s Data Science Certificate program bundle multiple data science bootcamps designed to prepare you for a career in data science.

Other Skills Needed to Become a Data Scientist

Soft skills needed to become a data scientist include: 

Classes with a collaborative element, such as hands-on projects, will help you learn to work as part of a team. You will also learn about real-world scenarios you may face when working for an organization, how to communicate with your teammates, and how to present your findings to others––all critical skills for Data Scientists to know.

Learn the Skills to Become a Data Scientist at Noble Desktop

If you are looking to start a new career in data science, you might think the only way for you to become a Data Scientist is by enrolling in a four-year university or pursuing other costly and lengthy educational options. However, there are many alternative methods available to help you transition into a data science career, including data science bootcamps and certificate courses designed to help working professionals gain the skills needed to obtain an entry-level job as a Data Scientist. Exploring in-person and live online data science bootcamps and certificate programs can help you find the class that meets your career goals, budget, and schedule. The first step to finding the class that fits your needs is to understand the differences between in-person classes and live online classes. 

In-person data science classes meet in a traditional classroom setting at a physical location. In-person classes have the advantage of providing all necessary equipment, such as computers and software, and allowing students to network with local professionals such as your classmates and instructor. You also have the advantage of learning from an expert instructor face-to-face. The primary drawback to in-person courses is the extra time and money required to commute to the physical learning location. Live online data science classes offer many of the same benefits as in-person classes, including the ability to learn in real-time from an expert instructor. You can also collaborate with classmates, and you have the advantage of learning remotely. 

Noble Desktop offers several different in-person and live online data science classes that can help you start a career as a Data Scientist. The Python for Data Science Bootcamp teaches students foundational programming concepts and how to handle different data types, use conditional statements to control the flow of a program, use Scikit-Learn, Matplotlib, Numpy, Pandas, and other Python libraries and tools. Noble’s Data Science Certificate program and Data Analytics Certificate program provide a deep dive into the topics and skills essential to launching a career in data science or data analytics and offer one-on-one mentorship and job search assistance. All Noble Desktop classes provide students with hands-on experience, flexible financing options, setup assistance, a free retake, small class sizes, and real-time guidance from an expert instructor.

Learn more about Noble Desktop’s in-person and live online data science classes.

You can also learn more about data science careers and data science learning options with Noble’s free Data Science Learning Hub.