Learn More About Data Science Classes in Boston
Data science is an exciting, complex field, combining disciplines like math, programming, and artificial intelligence (AI). Data Scientists use their analytical and statistical skills to sort, manage, and interpret large datasets to provide insights. U.S. News & World Report listed Data Scientists among the top ten in its 100 Best Jobs of 2024 survey, and the field continues to show a dramatic growth rate for the foreseeable future. Intensive training is essential if you’re planning a data science career.
In this overview, you’ll learn more about data science—what you can do with it, who uses it, and how to add data science tools to your professional toolbox.
What Can You Do with Data Science Training?
What you choose to do with data science training depends on factors like your career goals, existing knowledge base, and skill set. Many students new to data science learn foundational tools and skills applicable to the discipline, like data visualization with Tableau or Power BI. However, if you plan to start a career as a Data Scientist or Data Analyst, you need to master a range of programming languages, databases, and other relevant skills. Consider the following projects you can create using data science training.
- Create a Recommendation Tool—You might wonder how Amazon or Netflix creates their “You may also like” search tools. A recommendation tool analyzes user data such as previous viewing or purchase history, types of programs or items, and standard market research data like age and location. You can create a recommendation system with a programming language and a specific dataset.
- Make a Word Cloud—Word clouds are more common than ever, and you can make one using data visualization tools. The popular Python programming language is ideal for creating word cloud visualizations. Top Python libraries for data visualization include Matplotlib, Seaborn, and Plotly.
- Build a Chatbot—Another project you can do with Python is to build a chatbot. The Python chatterbot library allows data science pros to use machine learning algorithms to build a chatbot that creates automatic responses to varying queries. It’s an excellent beginner-level project for data science novices.
What Will I Learn in a Data Science Class?
Data science is such a broad subject that what you learn in a class depends on numerous factors—from the length and tuition cost to whether the curriculum is beginner-level, intermediate, or advanced. Some data science novices take courses in individual subjects like Python or Tableau that can be applied to data science. Others dive right in, enrolling in immersive data science or analytics bootcamps or certificate programs. These longer courses often cover multiple topics with a data science focus, including Python, SQL, machine learning (ML), and other relevant subjects. Read on to learn more about how these tools apply to data science.
Python
Python is the preferred programming language for Data Scientists and Data Analysts for several reasons. First, Python fundamentals are easy to learn. Data science and analytics trainees often learn Python as their first programming language. Second, typical uses for Python include data manipulation, machine learning, and automating repetitive tasks. And third, Python is already established as an essential language in this field. Check job descriptions for data analysis roles, and you’ll find Python prominently featured.
SQL
SQL stands for Structured Query Language, a popular data analysis language. Like Python, you can find SQL listed as a data science or data analysis language on numerous job postings. Data science professionals use varying types of SQL databases, the most popular being MySQL, Microsoft SQL Server, and PostgreSQL, although there are many others. SQL is essential for writing queries for relational databases. Although SQL is considered a programming language, data management is the primary use for SQL.
Python Frameworks & Libraries
Learning a computer programming language involves more than just the language itself. Learning popular languages like Python and JavaScript requires learning related databases, libraries, and frameworks. Data science requires you to know Python frameworks like Django, Flask, and CherryPy, and Python libraries like NumPy, scikit-learn, and TensorFlow. These assist in everything from manipulating and cleaning data to applying machine learning algorithms.
How Hard Is It to Learn Data Science?
The challenge of learning a new discipline depends on factors like your current skill set and previous experience. However, data science is not a single tool or platform like Excel or HubSpot. You can familiarize yourself with data science in a few days, but to become an expert can take years. If you plan to work as a Data Analyst or Data Scientist, consider enrolling in an immersive program that at least prepares you for an entry-level role.
What Are the Most Challenging Parts of Learning Data Science?
Data science encompasses skills like Python, ML algorithms, and data visualization with Tableau. Different people have different experiences with these subjects. For some, the most challenging aspect is integrating varying tools and skills. Others find a single skill challenging. To get the best results with the fewest difficulties, you should take a class or program where each section or unit builds upon previous ones, like the Data Science Certificate from Noble Desktop.
How Long Does It Take to Learn Data Science?
Like the degree of difficulty, how long it takes to learn data science tools and skills depends on where and how you plan to use them. If you want to learn a skill like Tableau for data visualization, you can accomplish your goal in a few days or hours. However, training to become a Data Scientist can take several months or even years. Plan on a class schedule of at least a month full-time or five to six months part-time to qualify for an entry-level data science role.
Should I Learn Data Science In Person or Online?
If you can find a data science class in Boston that meets your needs, you might prefer learning in person rather than virtually. However, consider including online courses in your search, which expands your options.
In-person courses are a popular choice for many data science novices. Learning face-to-face holds a unique advantage over other alternatives, that of the highest level of student engagement. However, the need to commute to class provides an obstacle for some students.
Online learning offers benefits comparable to in-person training. One of the best things about including online training in your search is that it expands your options. This type of training also lets you learn from the comfort of your home or office. The only downside is a slightly lower engagement level.
On-demand or asynchronous training typically consists of prerecorded videos, which means it offers the lowest level of engagement. However, this method can be a good alternative for students who work non-traditional schedules, like the second or third shift. Consider on-demand training if you need a different schedule than live classes.
What Should I Learn Alongside Data Science?
Learning skills and tools alongside data science is rarely necessary. A comprehensive data science or analytics program will cover the most essential subjects. However, some relevant skills may fall outside your curriculum. Consider the following tools you may need before starting a data science position:
- Microsoft 365—Many employers take for granted that you know your way around MS Excel, Word, Outlook, and other software. Make sure your Office skills are up-to-date.
- Adobe Experience—While you might know Adobe only as a PDF program, the Adobe Experience software suite is also popular. Get acquainted with its Data Science Workspace and Adobe Analytics.
Boston Industries That Use Data Science
Top industries in Boston include healthcare, technology, finance, and government. Consider the following sectors for data science or analytics roles:
Healthcare & Social Assistance
Healthcare is a significant source of employment in Boston, with hospitals like Boston Medical Center and Boston Children’s Hospital at the forefront. Data analytics in healthcare ranges from tracking diseases to medical imaging.
Professional, Scientific & Technical Services
Many graduates from Boston’s famed colleges and universities (Harvard, MIT, Wellesley) land high-paying jobs in this sector. Think biotech or tech startups for data science and analytics.
Banking, Financial Services & Insurance
Boston is one of America’s high-finance districts, with companies like State Street, Putnam, and Fidelity Investments. Jobs in finance and insurance requiring data analysis skills include Financial Analyst, Business Analyst, and Data Analyst.
Data Science Job Titles and Salaries in Boston
Boston data science and analysis salaries are slightly higher than the national average.
Data Analyst
A Data Analyst in Boston can expect to earn an average annual salary between $76,000 and $121,000. These skilled professionals perform statistical analysis for companies, helping them identify trends and make data-driven decisions.
Business Analyst
Business Analysts in the Boston area can expect to earn from $81,000 to $127,000. They may liaise between internal staff and key stakeholders, supporting or leading projects and recommending procedural improvements.
Financial Analyst
Often confused with Business Analysts, Financial Analysts track an organization’s performance to help management make data-driven decisions. A Boston-area Financial Analyst can earn from $85,000 to as much as $133,000 annually.
Data Scientist
Data Scientists are among the most respected and highest-paid data science workers. In Boston, they command salaries from around $127,000 to as high as $216,000 annually.
Data Science Classes in Boston
The Data Science and AI Certificate from Noble Desktop is an immersive program designed to equip students with in-demand skills in Python, machine learning, and data visualization. Through a series of hands-on projects, participants learn to apply data science techniques to real-world problems and gain practical experience analyzing and interpreting data. The curriculum explores essential Python libraries such as Pandas, NumPy, and scikit-learn, ensuring a strong foundation for work across multiple industries. Classes are led by experienced industry professionals who provide expert guidance, mentorship, and real-world insights to help students succeed in today’s data-driven world.
The Python for Data Science Bootcamp is an ideal program for anyone looking to strengthen their Python programming skills, specifically for data science applications. This course provides an in-depth introduction to using Python for data analysis, guiding students through essential tools such as Jupyter Notebook and powerful visualization libraries like Matplotlib and Seaborn. By the end of the bootcamp, participants will have the ability to clean, organize, and analyze datasets efficiently using Python. With its blend of interactive instruction and personalized support, Noble Desktop offers a structured, hands-on learning experience that helps students build both confidence and practical expertise.
Data Science Corporate Training in Boston
Would your team benefit from expanding its data science skills? If so, consider onsite and corporate training from Noble Desktop. Noble provides multiple training alternatives and can tailor a program to your needs and preferences. Corporate and onsite training is available live online via teleconferencing, and Noble’s expert instructors can even conduct training at your location.
If you want your team to have more flexibility with their training, Noble offers discounted vouchers for its open enrollment courses. Employers get a discount when they purchase the vouchers in bulk. Classes include Python, SQL, and machine learning training. For more information and a free consultation, contact Noble Desktop today.
