How to Learn Data Science Online

If you’re just starting to learn a new skill, you can find dozens of tips and resources online; learning data science is no different.

Data science is a broad, complex field encompassing disciplines like math, computer programming, and artificial intelligence (AI). Industries as varied as healthcare, retail, and banking rely on data science to analyze information, gain insights, offer conclusions, and even make predictions.

If you’ve always wanted to learn data science, there are plenty of options at your fingertips. From free tutorials to live classes, your options are outlined here so you can decide how to learn in a way that works best for you.

What is 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. 

What Can You Do with Data Science?

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:

• Banking, Financial Services & Insurance (BFSI) - Business Analysts and Data Scientists use data for everything from fraud detection to customized financial advice. Machine learning algorithms can assist with risk analytics, stock trading, and other tasks.

• Marketing & Advertising - Data Analysts and Marketing Analysts use data science in advertising to create targeted ad copy, recommend products and services, and leverage social media platforms. Programming languages like Python and R, often key to data science positions, help experts analyze data and make recommendations.

• In healthcare, Data Scientists create algorithms to create care plans and improve patient services. Using data analysis in medical imaging can help care providers with diagnoses and treatment decisions.

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.

Live Online Data Science Training

While some students prefer to learn in a classroom setting, others turn to live online bootcamps or certificate programs to learn data science. These immersive courses offer in-depth training in a condensed time frame, preparing attendees to begin new careers or level up from current roles. Online courses provide face-to-face training via teleconferencing: you can learn from the comfort of your home. Student engagement may be slightly lower, but many find the tradeoff worthwhile.

You can find a host of live online data science classes using Noble Desktop’s Classes Near Me search tool. They offer many of them at the NYC campus on Madison Avenue. However, participants outside the area can attend these programs from anywhere via teleconferencing. Consider the following data science bootcamps:

• Data Science Certificate - Noble’s Data Science Certificate program covers data science in detail, with topics like Structured Query Language (SQL) and Python programming for automation and machine learning (ML). The course is open to beginners and includes training in popular libraries like NumPy and Pandas. Check listings for more information. 

• Data Analytics Certificate - The immersive Data Analytics Certificate is the perfect launching pad for data sciences novices looking to qualify for entry-level data analytics or business intelligence analytics positions. It combines bootcamps in Excel, SQL, and Tableau with Python programming for data science, automation, and machine learning.

• Python Data Science & Machine Learning Bootcamp - As a subset of artificial intelligence (AI), machine learning has quickly become a top skill set for data science pros of all types. This immersive course includes a Python for Data Science Bootcamp, a Python for Automation module, and a Python Machine Learning Bootcamp. 

Other live online options include a Data Science Bootcamp from NYC Data Science Academy, Thinkful’s Data Science Immersion, and Online Data Science from Flatiron School.

On-Demand Data Science Classes

On-demand classes, also known as self-paced classes, provide another way to begin learning about data science. They typically fall into three categories: Free, fee-based, or subscription-based.

Data science courses on demand vary and include beginner, intermediate, and advanced training options. While some on-demand courses require payment, a few are free. But most require subscribing to a provider’s platform, like Udacity or Skillsoft. Current on-demand data science classes include Get Started in Data Science from Noble Desktop, Google’s Data Analytics Professional Certificate, and the ML Engineering Career Track program from Springboard.

The on-demand learning model offers certain advantages, but there are drawbacks as well. While many students choose to learn data science fundamentals on-demand first, the need for instructor guidance usually leads them to enroll in a classroom setting to move to the next level.

Free Intro Courses & Tutorials

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.

Comparing Online Methods with In-Person Learning 

Bootcamps or certificate programs can be an ideal way to learn data science. If your learning style requires a traditional classroom experience, an in-person course should be your first choice whenever possible.

This module covers the three primary training methods:

• In-person
• Live online
• Self-paced/on-demand

Among the three, students typically find online live and in-person courses the most engaging, interactive formats. You can ask questions and get real-time answers, receive guidance for your portfolio, and interact with like-minded peers, all in a dynamic setting.

Additional advantages of face-to-face training are that it offers networking opportunities, and course providers usually have dedicated computer labs with up-to-date software. You never have to worry about an equipment breakdown.

These days, many students and busy professionals avail themselves of virtual live bootcamps or certificates for their data science education. Like in-person coursework, live online training offers multiple benefits. You get immediate answers to your questions like in a traditional classroom, but you can learn from the comfort of your office or home. Expert instructors with experience in the field can give you feedback and even share your screen with permission. If there’s a drawback to online classes, it’s that some students need in-person engagement for an optimum learning environment.

The self-paced or on-demand learning format can be more of a wild card than in-person or virtual live training. These can range from free two-hour videos to eight-month programs costing thousands of dollars. While you might think a self-guided program of such magnitude would be ideal, many students report that the lack of accountability for assignments makes it difficult to stay engaged. On the other hand, a short, low-cost, or free on-demand seminar often serves as the perfect introduction before committing to a full-length certificate program.

Tips to Succeed when Learning Data Science Online

Self-discipline, setting and following a schedule for assignments, and working toward measurable goals are all essential components of learning data science via teleconferencing. While a class in the traditional in-person setting might emphasize student accountability, if you prefer to get your data science training education live online, you’ll have to have a plan that ensures your success.

The following points can all help you get maximum benefits from online learning, but it’s by no means comprehensive. Consider your learning style, as you may feel more like part of the class during training but then feel more like you’re on your own after everyone signs off. Keep in mind that help is available to students after class, whether from your instructor, classmates, or other online tutorials or seminars.

• Create a plan and follow it. One of the biggest hurdles remote students report is creating and maintaining a schedule. After any online session, you must schedule times for completing assignments and reviewing and studying course materials. If you enroll in a certificate program for three months part-time, you’ll have more flexibility in your schedule than if you need to immerse yourself full-time in a program for three weeks. Use a calendar app like iCal or Google Calendar to stay on track with assignments and planned study sessions. Working with classmates? You may need your schedule to line up with group meetings via Zoom or Slack.

• Learn from others. If you’re new to data science, you will most likely learn alongside other novices in the field. However, that doesn’t mean no one else in the class has expertise in a related field. Your instructor and even some of your classmates may know quite a bit about Python programming, SQL, or other topics essential to data science. If you plan to start a career as a Financial Analyst and a classmate works in finance, they might be the perfect study partner for you.

• Work smarter, not harder. Many students, especially those with busy professional lives or family obligations, can start feeling overwhelmed by an immersive online program. So one of the most effective methods for studying and completing assignments is to work in short, scheduled sessions. Two intense 15-minute study sessions with a 15-minute break in between them can be more effective than an uninterrupted 30-minute session. To ensure you work smarter, not harder, consider the following additional tips:
  • Avoid multitasking. When it’s time to study, focus only on the material in front of you.
  • Use your body’s internal calendar. Are you a morning person or a nighthawk? Schedule tasks based on your effectiveness at that time of day (or night).
  • Don't overbook. While enrolled in an online course, you might need to avoid extra engagements—especially if you’re juggling work and family obligations.

The last point may be the most important for some students. When you reach the edge of your limitations, pushing to the next level of data science expertise can seem daunting. Take care of essentials first, focus on self-care, and enjoy the challenge of learning in this exciting field. 

Learn Data Science with Hands-on Training at Noble Desktop

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.

• Data Science Certificate - The comprehensive Data Science Certificate provides all the skills required for entry-level data science, data analytics, or software engineering roles. Students learn how to write complex queries and build machine learning models while preparing a portfolio on a real-world basis. Skills covered include Python, SQL, NumPy, Pandas, and Jupyter Notebook, to name a few.

• Data Analytics Certificate - The comprehensive Data Analytics Certificate program offers the perfect training ground for Data Analysts, Business Intelligence Analysts, and Marketing Analysts. With a heavy emphasis on Tableau data visualization software, you’ll learn skills like Python programming, SQL, and machine learning, among others. Registrants of the Data Analytics Certificate or Data Science Certificate can also attend Noble’s Power BI Bootcamp at no additional charge.

• Python for Data Science Bootcamp - The Python for Data Science Bootcamp covers everything from programming fundamentals to data visualization. Students can save by taking this course as part of Noble’s Data Science Certificate, Data Analytics Certificate, or FinTech Bootcamp.

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.

Key Insights

• Data science is a broad, complex field encompassing disciplines like math, computer programming, and artificial intelligence (AI).
• Virtually every industry today uses data science to analyze information, gain insights, and offer conclusions to everyone from Product Managers to C-suite executives.
• Top data science positions include:
• Business Analysts
• Data Analysts
• Data Scientists
• Enterprise Architects
• Financial Analysts
• Machine Learning Engineers
• Marketing Analysts
• Software Engineers
• Web Developers
• Top sectors for data science include:
• Automotive
• Banking, Financial Services & Insurance (BFSI)
• Business Analysis
• Cybersecurity
• FinTech
• Healthcare
• Marketing & Advertising
• Media & Entertainment
• Retail
• Software Engineering
• Telecommunications
• Web Development
• In-person and live online courses seem to have the highest engagement levels.
• On-demand classes, free seminars, and online video tutorials offer the lowest cost entry points to learning but have the lowest overall engagement.
• Noble Desktop offers an array of data science courses for beginners and working professionals looking to upskill in a specific area.