Data Science Video Tutorials

Data science is a field of study that encompasses computer programming, math disciplines like probability and statistics, and tools like artificial intelligence (AI), including machine learning (ML). While the general public may not know much about data science or analytics, they’re increasingly crucial to industries like healthcare, retail, and digital banking.

Watching video tutorials online is a popular method of learning data science. Video tutorials and seminars can help both auditory and visual learners, as they typically offer spoken materials and data visualization. Most students move on to formal training either live online or in the classroom, but videos can be a great place to start.

This article will cover a range of data science videos, including what they teach and where to find them.

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.

Why Are Video Tutorials Helpful When Learning Data Science?

Video seminars and tutorials offer an appropriate starting point for many students, particularly those unfamiliar with data science fundamentals. Consider three of the most common learning styles to see why video tutorials can serve as valuable tools:

• Auditory - Most people’s learning style emphasizes either auditory or visual material, but it’s not uncommon for people to retain information only after hearing it—sometimes more than once. Video tutorials typically benefit auditory learners unless they only include slide decks with no audio. Best of all, auditory learners can pause and relisten as often as they like.

• Visual - Video seminars and tutorials benefit visual learners the most, as they need to see to learn. Blog posts or online articles can also benefit them. The primary benefit is that video tutorials can engage visual learners with text and other visual elements like charts and graphs.

• Kinesthetic - Kinesthetic learners, also known as tactile learners, learn best by doing. However, that doesn’t mean they can’t benefit from video training as much as auditory or visual learners. Some video tutorials include hands-on exercises, an obvious benefit for those whose learning style is at least partly kinesthetic.

Additional considerations about the benefits of video learning:

• You can watch them at your convenience.
• You can follow along with videos in real-time.
• You can rewatch them to reinforce what you have learned.
• They’re free.

Types of Data Science Videos

It’s not difficult to find data science and analytics video seminars and tutorials online. They range from short introductory videos to hour-long courses and can provide students with a solid introduction to the field—especially beginners. 

One of the most popular video resources on Noble Desktop’s website is its Intro to SQL seminar. This hour-long tutorial introduces students to Structured Query Language, with a deeper dive into its popularity among Data Scientists and Data Engineers. Other videos relevant to data science novices include Noble’s video tutorials on Python, such as their Making a Twitter Bot in Python tutorial.

Along with the free live and archived seminars on its website, Noble Desktop offers several tutorials on its YouTube channel. Check out the following videos, which can be relevant to data science or analytics:

• Get Started in Data Science
• Intro to Python Fundamentals
• Exchanging Excel for Python

Whether you plan to watch videos in conjunction with accompanying articles or rewatch them while taking notes, these data science seminars and tutorials can start you on the right track in your data science journey.

Why Learn Data Science?

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.

How Difficult is It to Learn Data Science?

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.

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.