Deepen your understanding of data science and data analytics with this extensive guide. Discover the types of careers that commonly use data, the value of various job positions, and how you can kickstart your learning journey towards a high-demand, high-paying role.
Raw data is the foundation of data analytics and data science. Professionals use data to understand patterns, identify opportunities, measure success, and plan improvements. If you’ve always wanted to learn data 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, free resources to take advantage of, and the types of careers that commonly use data.
Data refers to facts and statistics collected for reference or analysis. Data allows businesses to track finances, marketing campaigns, market share, efficiency, and more. Today, data management systems can sort complex data from numerous sources using artificial intelligence and machine learning, giving businesses unparalleled insights. Some data management systems can also make future projections based on existing data. These forecasts assist businesses in planning budgets, setting goals, determining deadlines, and more.
We all use data daily, but some professions specialize in gathering, analyzing, storing, and managing data. These careers include Data Analysts, Data Scientists, Machine Learning Engineers, Business Intelligence Analysts, Data Architects, Marketing Analysts, Business Systems Analysts, and more. Whether you wish to pursue one of these careers or simply want to understand the data systems and strategies that impact your business, online and in-person classes can teach you valuable skills.
Read more about what data is and why you should learn it.
Data has nearly endless uses. Data measures the effectiveness of marketing campaigns, determines budgets, forecasts company growth, and highlights industry trends, trends within an organization, and more. Understanding data science and data analytics can help business owners better manage their organizations, help marketing teams become more efficient and effective, assist business leaders in determining goals, or help launch your career as a Data Analyst or Data Scientist.
Data science jobs include Python Engineers, Data Journalists, Data Engineers, Business Analysts, and more. Data Scientists create machine learning models that help process raw data, giving a company better insights. Analysts interpret and track this data to continuously improve processes. Data helps organizations make the most of every minute and every dollar, which is one reason Data Scientists and Data Analysts are in such high demand.
Data is used by Marketers, Business Owners, and more, so learning essential data tools and skills can benefit anyone. Advanced data science and data analytics skills can launch your career as a Data Scientist or Data Analyst.
What does a data science career entail? Data science job titles include Data Scientist, Machine Learning Engineer, and Data Engineer. A Data Scientist collects, organizes, and analyzes data to inform decision-making. This data provides crucial insights into the company’s historic, present, and future success by tracking budgets, projecting earnings, detecting trends, and more. Data Scientists earn anywhere from $120,000 to $140,000 on average. Machine Learning Engineers use computer programming and data science to develop systems that automatically learn and perform tasks through artificial intelligence. Machine Learning Engineers earn around $120,000 annually. Data Engineers format data infrastructures that Data Scientists use in their analysis. A Data Engineer earns an average of between $120,000 and $130,000 per year.
A Data Analyst collects, processes, and analyzes data, then translates that knowledge into insights and actionable recommendations. Data Analysts can choose to work in almost any industry, including government, healthcare, finance, retail, and tech. Data Analysts in metropolitan areas earn around $100,000 annually.
Why should you learn data? Data informs business decisions by displaying the numbers behind the business. Data reveals how much money a business spends, how efficient company processes are, the effectiveness of marketing efforts, the cost to obtain a customer, how much revenue the company has coming in, and more. Reliable data is crucial to any organization’s health and success, whether the organization is a multinational company or a local nonprofit.
Data science uses scientific methods, systematic processes, and algorithms to filter, sort, organize, and manage raw data from numerous sources. Data Scientists and Data Analysts are in high demand and have high earning potential. The U.S. Bureau of Labor Statistics found the 2021 median pay for Data Scientists was $100,910 per year, with anticipated job growth of 36% over the next decade. Even if you do not wish to pursue a career as a Data Scientist or Data Analyst, data plays a critical role in marketing, project management, team leadership, and more.
Read more about why you should learn data.
Live classes include in-person and live online courses. Both types of training are led by an expert instructor, which offers several benefits. Instructor-led courses allow you to have your questions answered on the spot and allow for real-time feedback. In-person classes allow you to network with local professionals, while live online classes offer the convenience of remote learning. You can explore in-person and live online data classes to find the course that works best for you.
On-demand/self-paced classes include pre-recorded video courses you can watch anytime. Some video courses include supplemental material such as documentation and assignments. You can use free YouTube video courses to gain a high-level overview of a topic, such as learning data. Learning platforms like Udemy, Coursera, and LinkedIn Learning offer on-demand classes through paid subscriptions. The primary advantage of asynchronous classes is that you can learn on your schedule. You choose the time, place, and pace at which you learn. The main disadvantage of on-demand classes is the lack of instructor access. You may have an instructor you can email or meet with at specified times, but both options require waiting several hours or days for a response. For this reason, many people use on-demand courses as a starting point to better understand a topic, then follow up with an instructor-led course. Explore on-demand data classes to find free and paid training options.
Noble Desktop offers free resources to help you advance your data skills. Noble’s Data Learning Hub includes articles, tutorials, and other resources all in one place. You can gain an overview of data science with the free video seminar Get Started in Data Science and watch other free videos through the Python, Data Science, & SQL YouTube playlist.
Noble also has Learning Hubs for specific data tools and skills, including Tableau, SQL, Excel, and Python.
You can research and compare multiple in-person and online data class options to find the best training options with Noble Desktop’s Classes Near Me tool.
Read the full guide on how to learn data.
If you aren’t ready to dive into an entire course and want to begin with an overview of data, you can begin with free introductory data courses online. Noble Desktop offers a free online seminar to get you started in data science. You can watch this video on demand at any time.
Paid learning platforms like Udemy and Coursera offer a free trial during which you can start data classes. You can view video courses on data science, data analytics, machine learning, SQL, Tableau, Excel, and more.
Read about more free data videos and online tutorials.
The difficulty level of learning data varies considerably based on your educational and professional background, familiarity with data concepts and tools, and the specific skills you wish to gain. Read on to learn more about the difficulty, prerequisites, and cost of learning data science and data analytics.
Because much of data science depends on having a background in science, mathematics, and sometimes engineering, data analytics can prove a more accessible place to start. Many professions use data analytics daily, even if “analyst” is not in the job title. For example, Marketing Specialists, Marketing Managers, and other marketing professionals depend on data analysis to gauge the effectiveness of digital marketing strategies. Because so many professions use at least a basic level of data analysis, just about anyone can benefit by taking a data analytics course with broad applications, such as Noble Desktop’s Google Analytics Bootcamp or Excel for Data Analytics class. Individual, focused courses such as these tend to cost around $600 to $700.
Longer courses have an increased cost, with certificate programs often the most expensive due to their length and the instructor’s active involvement. Noble’s Data Analytics Certificate program costs around $5,000, with flexible payment plans available. Some companies cover the cost of classes as part of an employee’s internal professional development, so it is always worth checking with your employer about their reimbursement policies.
Data science is a challenging, multidisciplinary field involving statistics, business knowledge, and computer programming. Prerequisites include understanding mathematical modeling, machine learning, and other means of extracting valuable insights from raw data. Businesses of all sizes, from startups to government agencies, hire Data Scientists. Data science skills include learning Python, SQL, machine learning, and more. The complexity of data science makes it extremely difficult to learn independently, so an instructor-led course often provides the best way to learn. The best way to establish foundational data science skills and knowledge is through an instructor-led program such as Noble Desktop’s Data Science Certificate program. Certificate programs like this cost around $4,000 and up, depending on the school, the length of the program, and more.
Read about how difficult it is to learn data.
The difficulty of learning data compared to other fields depends on the data analytics and data science skills you wish to gain. Some skills are easier to learn and do not require a science or mathematics background. Just about anyone can learn how to use Excel and Google Analytics. Many professionals without a science or mathematics background use these tools daily. Tools like Tableau, however, prove trickier to learn if you do not have a background in sorting and analyzing data.
Data science skills like Python programming are much harder to learn than other fields, such as learning to code with HTML and CSS, because Python is a more complex coding language. A background in coding with a different programming language can make learning Python easier. It also helps to learn from an instructor rather than go it alone. You can gain an overview of Python and explore training options using Noble Desktop’s Python Learning Hub.
The cost of Data Science classes is comparable to courses in other subjects. Shorter classes cost a few hundred dollars, while longer courses and certificate programs cost around $4,000.
Deciding the best way to learn data starts with knowing what you want to do with your acquired skills. Are you looking to advance your current career or start a new one? Are you building on existing skills or starting from scratch? Do you want to focus on data analytics, data science, or both? You can opt for a broad approach or focus on a niche area. Research specific job titles to find a training method that caters to the skills required for that role.
There are a few different data training methods to explore. On-demand data analysis and data science classes consist of pre-recorded videos and textual content that students progress through at their own pace. These classes are the most affordable of the paid options but have the significant drawback of limited guidance or feedback. The lack of access to an instructor can leave students stuck on a question or technical issue for hours or days. Due to their affordability, on-demand classes on paid subscription services like Coursera and LinkedIn Learning can be a good starting point for learning data.
If you are just starting out and not ready to commit to a paid class or program, you can gain a high-level overview of data with free introductory classes. Noble Desktop offers free resources, including the Get Started in Data Science video course and Python, Data Science, & SQL YouTube playlist. Free video courses can introduce you to a topic. But because of the complexities involved in learning data analytics and data science, an instructor-led program often works best once you’re ready to dive deeper.
If you want to develop a solid working knowledge of data, plug a skill gap, or grow within your current career, a bootcamp can help you upskill quickly. Some bootcamps focus on specific topics within data science, such as Noble Desktop’s Python for Data Science & Machine Learning Bootcamp and Python for Data Science Bootcamp. You can also look into data analysis bootcamps such as Noble’s Data Analytics Technologies Bootcamp.
If you want to master data for a new career or pivot to a new industry, a certificate program can help pave the way. Noble Desktop offers a Data Analytics Certificate program and a Data Science Certificate program with live online classes, small class sizes, setup assistance, flexible payment plans, one-on-one mentoring, and a free retake.
Noble Desktop offers hands-on training in data science and data analytics. These courses are led by expert instructors and include hands-on projects, small class sizes, and free retake options. Noble offers a Data Analytics Certificate and Data Science Certificate. Both certificate programs include one-on-one mentoring, setup assistance, flexible payment options, and career preparation.
You can also focus on learning specific data science or analytics skills through classes and bootcamps. Learn how to write SQL queries, join tables, aggregate data, and filter results with SQL Bootcamp. The Tableau for Data Visualization course shows you how to convert raw data into interactive visualizations.
You can explore multiple data analytics and data science training options here.
In this article, we are going to look at how Data Analysis with Statistics can be done efficiently through the use of Microsoft Excel.
In this article, we are going to look at how to use the Analyze Data Tool in Microsoft Excel.
showing 2 of 2 entries