Are you passionate about learning data science and mapping out a career in this versatile, rapidly growing field? Our guide gives you a comprehensive overview of how to get started, free resources to leverage, and the diverse careers that depend on data science expertise.
If you’ve always wanted to learn data science but can’t figure out how to get started, this guide is for you. Here, you’ll learn more about the various ways to learn data science, free resources to take advantage of, and the types of careers that commonly use data science.
Data science is a broad field that encompasses the disciplines of mathematics, computer programming, and artificial intelligence (AI). Data professionals such as Data Scientists and Data Analysts use advanced techniques like machine learning algorithms to find patterns in a vast amount of information. This process can provide actionable insights to stakeholders, from Product Managers to C-suite executives.
Today nearly every sector requires data science expertise, whether public or private. Among the top sectors where data science is critical are health and wellness, retail, web and application development, banking and finance, and governmental agencies. The field continues to project dramatic growth over the next decade; Glassdoor even listed Data Scientist as number three in its 50 Best Jobs in America in 2022.
Read more about what Data Science is and why you should learn it.
Data science has so many applications in different industries that a comprehensive review could fill a book. Professionals as diverse as Business Analysts, Machine Learning Engineers, and Enterprise Architects use data science in their day-to-day activities.
Top sectors for data science include banking and finance, marketing and advertising, and healthcare:
Data science has proven crucial to many other sectors, from retail and manufacturing to the public sector. If you want to combine challenging work with job security, start with data science.
Data science cuts across nearly every industry, with professions in manufacturing, retail, government, and cybersecurity, to name a few. Whereas Data Scientists use their knowledge and skills in one way, Marketing Analysts may use theirs in quite another.
Banking services, web development, and healthcare are among the top sectors where data science is more critical than ever. The following points emphasize how they use data science in vastly different business models.
Your path to learning data science tools and languages depends heavily on how and where you plan to use your knowledge and skills. A Data Scientist or Data Analyst will need comprehensive training in math, computer science, probability, and statistics. However, a Back End Developer may need only a few tools applicable to data science, like Python and Django REST.
The most significant benefit to learning data science skills and tools is the breadth of their applicability. A top programming language like Python will be crucial in fields like machine learning (ML) or artificial intelligence (AI). At the same time, data visualization tools like Tableau can be essential for everyone from Business Analysts to SQL Server Developers.
Whether you plan a role as a Cybersecurity Analyst, a Machine Learning Engineer, or a Business IT Analyst, data science skills will prepare you to analyze information, gain insights, offer conclusions, and even make predictions.
Read more about why you should learn data science.
Live data science classes, either in-person or online, are the most popular options for learning this essential programming language. You can find in-person data science programs near you using Noble Desktop’s Classes Near Me search tool. Check out the Data Science Certificate for training in Python and SQL or the Data Analytics Certificate to learn Python machine learning and Tableau. For virtual live training options, look for the best course for your goals, as you can take it from anywhere. Online live data science courses include a FinTech Bootcamp and Python Data Science & Machine Learning Bootcamp.
On-demand or self-paced data science courses are also available, although they aren’t nearly as thorough as live bootcamps or certificate programs. The Get Started in Data Science video tutorial from Noble Desktop provides a free two-hour introduction, while course providers like Udacity or Skillsoft offer training with your paid subscription to their platforms. Other on-demand alternatives require payment.
Noble offers additional free seminars on data science, along with blog posts and tutorials. You’ll find samples in the data science section of the Learn Hub. Their website's Free Seminars page hosts an Intro to Python Fundamentals seminar. And check out their YouTube page for a playlist on Python, Data Science, and SQL.
Read the full guide on how to learn Data Science.
If you can’t currently commit to a full-length data science bootcamp or certificate program, consider the many free online resources you can use to start learning data science. For example, Noble Desktop’s Intro to SQL is a great place to start. Learn why Structured Query Language is essential to data science in this free introductory course. It’s the perfect background prep for a more extended program like Noble’s Data Science Certificate or Data Analytics Certificate.
Other free online classes include Data Science Math Skills from Duke University, Data Processing Using Python from Nanjing University, and Algorithms, Pt. 1 from Princeton University.
Read about more free Data Science videos and online tutorials.
The biggest challenges in learning data science depend on what field you enter and how you use the skills and knowledge you gain. Data Scientists, Data Analysts, and Business Analysts alike need to know data visualization tools like Tableau or master an object-oriented programming language (OOP) like Python.
Data science prerequisites also vary. A solid background in high-level mathematics—probability, statistics, and algebra—can help but may not be required for every position. And while you may need Python or Tableau skills, you can learn them as part of a broader data science curriculum rather than as prerequisites to study.
Costs vary as well. Some data science novices begin with comprehensive bootcamps or certificate programs which can pave the way to an entry-level job in this growing field.
Read more about how difficult it is to learn data science.
Learning data science means different things to different people. For example, some students want to learn Python as part of a more comprehensive data science curriculum. Others, by contrast, will focus on Python or R only because they enroll in a back end development course. Programming languages like these apply to numerous fields, not just data science.
Data science can be challenging to learn in-depth: experts estimate around six to twelve months to master data science fundamentals, but expertise in the field takes years. For that reason, students interested in data science for its own sake often choose immersive bootcamps or certificate programs.
One area comparable to data science is management: you’ll need expertise in your sector to become a manager. Data science tools and skills vary among different sectors in much the same way.
For more on tools and skills among different roles, check out Noble Desktop’s Learning Resources.
When choosing the best way to learn data science, consider first how and for what you want to use the skills and knowledge you’ll gain. Beginners may not be ready to invest in formal training yet want a high-level overview of the field. In such cases, a free introductory class like Noble Desktop’s Intro to SQL may be the best way to start.
If you want to develop a working knowledge of data science or level up from your current position, check out a program like Noble’s Python for Data Science Bootcamp or Python Data Science & Machine Learning Bootcamp.
Want to master data science for a new career? Consider enrolling in a lengthier program like Noble’s Data Science Certificate or Data Analytics Certificate. These intensives cover topics like Python, SQL, and machine learning, to name a few.
Because data science is a broad field, targeted training can prepare you for a data-centered position or even help you choose a specific role. You might think you’ll need a four-year data science degree, but this isn’t necessarily so. The bootcamp or certificate educational model has become increasingly popular for data professionals, thanks to features like small class sizes, hands-on training from industry experts, and individual mentoring. Noble Desktop offers a wide range of data science programs to help get you started.
Check out all the Noble data science classes and bootcamps for additional options, like the Python Data Science & Machine Learning Bootcamp, Python for Data Science Bootcamp, or Python Machine Learning Bootcamp.