Best Data Science Bootcamps Philadelphia, PA: Find Bootcamps & Certificates

Learn More About Philadelphia Data Science Bootcamps

Data science is an interdisciplinary field of study that brings together scientific principles, mathematics, statistics, and computer programming to collect, store, manipulate, analyze, and visualize data. For most in this field, the end goal of using data science is to draw out actionable insights from large, complex datasets. Those in roles as Data Scientists, Data Analysts, or Data Engineers often use patterns, trends, and insights derived from data to help companies and organizations become more efficient, plan for the future, and optimize workflows and business practices.

A variety of industries use data science, including finance, healthcare, education, retail, transportation, manufacturing, and technology. The manufacturing industry might employ data science to analyze the efficiency of a supply chain or notice defects in goods as they are being produced. Finance, by contrast, often uses data science to analyze risk and predict the outcomes of specific investments and financial strategies. Due to data science’s wide use and applicability, someone who can harness the power of data will find that their skill set is in-demand and can lead to many high-paying career prospects.

What Can You Do with Data Science?

Learning data science provides you with a very versatile skill set that is useful for starting down a career path or implementing data-driven decision-making in your own life. Many working in data science fields are using their skills to enhance how businesses and organizations use information. In education, for instance, data science can be useful not only to help the administration budget and plan to maximize their resources, but it can also be used to assess the strengths and weaknesses of curricula and even predict student outcomes based on outreach initiatives. This is one example of how an industry that already collects a large amount of data—about learning outcomes, students, district, state, and federal standards, and finances—could use data science.

Not only is learning data science useful professionally, but it is also something you can use in your own life. For instance, someone who wants to strengthen their finances could use data analytics to plan better for the future or assess the risks of certain investment opportunities. Data science training could also enable you to build your own recommendation tools or even aid local nonprofits by volunteering your services to help them optimize their practices.

Learning data science is something that can also allow you to pivot careers or start down a new career path. The foundational skills of data science, like mathematics, statistics, and coding, have uses beyond data science and can allow one to pursue a career as a Financial Analyst, Statistician, or Web Programmer. Learning AI and machine learning as part of a data science program will also open new career opportunities as artificial intelligence is a continually innovating and growing field itself.

What Will I Learn in a Data Science Class?

Data science bootcamps and classes will draw on one’s knowledge of math and statistics to teach learners how to collect, store, manipulate, and interpret data. Successful Data Scientists have a mix of both hard and soft skills, skills that one starts learning in a data science class. Some of the key concepts, skills, and tools that one learns in a data science course include Python, machine learning, collecting data and extracting insights, cloud computing, and problem-solving.

Programming

Python is the programming language most taught and used in data science classes. Python is prized for its ease of use, integration with other tools, and well-used libraries like Pandas, NumPy, Matplotlib, and scikit-learn. These libraries will allow someone to manipulate and analyze data, perform math operations, visualize data, and perform classification, regression, clustering, and dimensionality reduction which are essential for programming machine learning tasks. While bootcamps might not always teach SQL, this is a standard language for working with databases and it is commonly taught in longer classes or certificate programs.

Web Scraping & Data Wrangling

Not only will one learn Python and machine learning, but students in a data science class also learn a variety of methods to collect and work with data. Learners will often work on web scraping, which is creating and deploying bots that are coded to collect large amounts of data from the internet. One often also learns data wrangling, which involves cleaning raw data so that it can be analyzed. Data wrangling can include deleting unnecessary or missing data, identifying data outliers, and merging data from multiple sources.

Machine Learning & Data Mining

One of the things that sets data science apart from mere data analysis is teaching students how to build their own machine-learning models. Learners will need to use their background in statistics to develop and train these models that either are able to predict outcomes based on what you directly input or can move beyond your inputs to extract unseen patterns, trends, and data insights. It is common for some data science classes to also cover deep learning and neural networks.

Cloud Computing

Not all data science bootcamps will teach cloud computing along with Python and machine learning. However, it is common in some longer classes or certificate programs as learning cloud computing allows one to work with particularly large datasets, store and manage large amounts of data, and better automate workflows. It is particularly common for those specializing in Big Data or AI and deep learning to learn how to work with Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.

Problem-Solving

It can be useful to think of data science as a way to solve or address real-world problems using data and information. Learning data science will enhance your problem-solving skills as these classes allow you to practice applying data science principles to important problems. Many classes also allow one to define their own problem to solve by using predictive analytics and models.

How Hard is It to Learn Data Science?

Data science is a multidisciplinary field, and learning it will involve mastering mathematics, statistics, computer science, and machine learning. Because of the complexity of the field, it will be much easier to learn data science if one starts with a solid math and statistics background and has some familiarity with computer programming. Anyone can learn data science, though it will take time and effort to master and it will take longer to learn for those without the right educational background.

What Are the Most Challenging Parts of Learning Data Science?

As long as someone has a background in mathematics and statistics, it should not be too difficult to learn the basics of computer programming and machine learning. One of the challenging aspects of data science is putting everything together and knowing how to use your knowledge to extract useful data insights from large datasets. One will learn standard practices in a data science course, but it will take continued practice to master this ability. Another difficulty is how frequently the field changes and updates based on technological innovation and developments in standards and techniques. Successful Data Scientists must update their learning continuously and remain on top of trends within the field, which can present a challenge.

How Long Does It Take to Learn Data Science?

How long it takes to learn data science depends on one’s educational background and skill level. Those with strong foundations in mathematics, statistics, and computer programming will be able to learn data science quicker than those without this foundational knowledge and these skillsets. Most can learn the basic principles and toolsets of data science in three to six months, though it will take longer for those who need to brush up on other concepts first. While one can learn the basics of data science in three to six months, it can take two to three years to become fully proficient in data science concepts and tools. After training in data science, one should continue to practice and put their skills to use to achieve proficiency and, eventually, mastery.

Should I Learn Data Science in Person or Online?

Whether to learn data science in-person or online depends upon your own learning needs as well as the availability and cost of the course. In-person classes are still considered the best way to learn and retain information. This type of education offers hands-on training from an instructor who can work with students one-on-one in the classroom and the classroom itself offers a focused, dedicated space for learning data science subject matter. Currently, many training programs are moving their data science courses online, so, not only is it harder to find in-person options outside of major US cities, but they can be more expensive options, as well.

Instructor-led online courses provide a suitable alternative to in-person learning. Most online classes offer expert instruction and a similar curriculum as an in-person class. While some students find online learning disengaging and distracting, online classes can be more cost-effective and accessible to a wider range of people. Those with full-time jobs and responsibilities or otherwise busy schedules will find that it is easier to take an online class as they are often scheduled in the evening, on weekends, and are available for part-time enrollment.

Can I Learn Data Science for Free Online?

While it is not recommended to learn data science entirely on your own, you can get a start learning data science basics on your own for free. A good entry point into learning about data science is Noble Desktop’s free Get Started in Data Science seminar which provides an overview of the field, what data science entails, and what you’ll learn in a data science course. Noble offers additional free seminars for important data science skillsets, including Intro to Python Fundamentals, Exchanging Excel for Python, and Intro to SQL.

In addition to these free seminars, you can find YouTube videos, blogs, tutorials, and short workshops online that will teach data science basics. Local libraries often offer free access to LinkedIn Learning for library patrons, and IMB SkillsBuild is a free online learning platform with introductory data science courses. Look for the most up-to-date tutorials and strategies, as these are the ones that will best prepare you for pursuing a career in data science.

Learning the fundamentals of programming and data science for free will set you up for success when taking a more in-depth and comprehensive data science bootcamp or certificate program. More advanced topics are best left for an instructor-led class, as one will need guided, hands-on training and individualized instruction to learn the more difficult applications of data science principles.

What Should I Learn Alongside Data Science?

Before learning data science, one must have a solid knowledge of mathematics and statistics. For those lacking this educational background, consider taking a quick class to learn or review these topics.

It is useful for data science learners to complement their knowledge with other programming languages. Most data science classes will teach or require learners to be familiar with basic Python syntax. In addition to Python, languages like R, Perl, or C can be useful to learn. Some data science classes (especially longer certificate programs) will teach the database language SQL, but, if they don’t, then data science learners will want to learn SQL on their own or take a short class in SQL to learn the basics.

Many who learn data science will need a firm grasp of data analytics and related software. Some of the most useful programs to consider learning are Business Intelligence (BI) software, including Power BI and Tableau. These software programs are used in a variety of industries including retail, healthcare, and finance, and allow one to perform data analytics, generate data visualizations, and collaborate with colleagues.

Industries That Use Data Science

While not all companies or organizations use data science, most industries do. Some of the top industries in Philadelphia, including healthcare, technology, manufacturing, and finance, are also the leading industries for data science professionals.

Healthcare

Slightly over a fifth of Philadelphia’s population is employed in the healthcare field, making it an essential industry. Data science is also being widely adopted in the healthcare industry. Not only can data science aid in optimizing workflows and setting budgets, but data science has a major role to play in predicting patient outcomes and creating individualized treatment plans.

Technology

The tech industry sees major growth potential in Philadelphia and Philadelphians working in the tech industry boast some impressive salaries above the national average. Data science is a natural fit with tech, as most Data Scientists, even those who work in other industries, will be identified as tech workers. Data Scientists are able to build the technologies that allow businesses and organizations from all industries to make data-driven decisions.

Manufacturing

Philadelphia is a manufacturing hub and many Philadelphians find themselves working to make and transport goods in various sectors of the manufacturing industry including biopharmaceutical, aerospace, food, chemical, and plastics. Data science has broad use in manufacturing. It can help companies assess and optimize supply chains and data science can even be used to detect abnormalities in products as they are being manufactured.

Finance

Finance, banking, and FinTech are strong sectors of Philadelphia’s economy. Most financial institutions are using some amount of data science currently and risk assessment is often one of the first applications. Data science can help the finance industry determine which investments are risky and predict the potential payoff and outcome for a variety of different kinds of investment opportunities.

Data Science Job Titles and Salaries

Most people have heard that data science is one of the hottest 21st century jobs. This is backed up by data, as the U.S. Bureau of Labor Statistics suggests that data science professions are expected to grow by 36 percent between the years 2023 and 2033. Those learning data science can find stable and high-paying jobs working not only as a Data Scientist but also as a Data Analyst, Business Analyst, or Machine Learning Engineer. Someone with training in data science can find themselves working in a variety of industries in Philadelphia including healthcare, technology, manufacturing, biotech, and finance.

It is common for those with data science training to find jobs as Data Analysts. This is a role that works well with one’s training, as Data Analysts collect, store, analyze, visualize, and clean data for different companies and organizations. What one is tasked to do in this role can be industry-specific and flexible to the needs of one’s employer. Data Analysts in Philadelphia make slightly above the national average at $85,000 a year. Business Analyst (or BI Analyst) is a related role, though, here, one is often tasked with using data to optimize a business’s performance and making data-driven recommendations. In Philadelphia, Business Analysts make an average yearly salary of $96,000.

The Data Scientist role is usually considered a more senior position that one earns after years of on-the-job experience. In Philadelphia, Data Scientists are making above the national average with yearly average salaries of around $125,000. Those in specialized roles can often earn more than the standard Data Scientist. This is true for Machine Learning Engineers who are making an average of $135,000 yearly in Philadelphia. Machine Learning Engineers have studied data science and have specialized training in machine learning, deep learning, and AI and spend much of their time designing, building, testing, and managing predictive models.

Data Science Classes Near Me

Noble Desktop offers live online classes for those in the Philadelphia area. All Noble classes provide small class sizes, hands-on training from an expert instructor, effective curricula, a free retake option, and a guarantee that you will learn the skills covered in the course. Data science and programming beginners should consider enrolling in the 30-hour Python for Data Science Bootcamp. This is a no-experience-necessary entry point into learning data science fundamentals. Students in this bootcamp can expect to learn the basics of Python programming and machine learning, as well as how to work with data. By the end of the course, learners will know how to analyze data using common Python libraries like Pandas and NumPy, visualize data with Matplotlib, and use scikit-learn for machine learning.

Learners with Python experience should instead enroll in the 30-hour Python for Machine Learning Bootcamp which builds on one’s programming knowledge to cover more advanced data science topics. Among other topics, students in this course will learn to build and evaluate their own machine-learning model. Both bootcamps are offered as an all-inclusive, comprehensive 96-hour Python Data Science & Machine Learning Bootcamp. This bootcamp not only covers the material from Python for Data Science and Python for Machine Learning but also delves into introduction topics like automation and data visualization techniques. This training option is also a certificate program that aims to provide students with career-ready data science knowledge and toolsets.

The Community College of Philadelphia and Temple University’s Fox School of Business both offer on-demand data science bootcamps. Rather than being instructor-led, these institutions offer self-teaching course materials that learners can work through at their own pace. The Community College of Philadelphia’s AI Machine Learning Bootcamp is a comprehensive six-month course of study where students will receive access to 300 hours of course materials. The bootcamp covers fundamental AI, machine learning, and Python principles and prepares students to pass the Microsoft Azure AI Engineer Certification Exam AI-102: Designing and Implementing an Azure AI Solution. By contrast, Temple’s Data Analytics Bootcamp: Python is a 10-15-hour course covering how one can collect, organize, and analyze data to solve problems and optimize decision-making processes. This low-cost bootcamp could be a good entry point into Python and data science for beginners, students, and working professionals looking to make a career change.

The digital skills training center General Assembly also offers remote, online data science bootcamps. Both their 10-week Data Science Short Course and 12-week Data Science Bootcamp cover data science fundamentals like Python, machine learning, and data analysis and visualization techniques. The bootcamp, however, will also cover topics like statistical modeling and neural networks, whereas the short course focuses on data-based storytelling. Both courses are best for intermediate learners, according to General Assembly, who should have a grasp of computer programming and basic Python syntax.

Another set of options for learning data science are those offered by Certstaffix Training. Rather than offering a comprehensive instructor-led data science bootcamp, Certstaffix has a series of short classes that provide training in data science essentials like Excel, Python, SQL, and BI software. A good place to start for beginners is their Python Combo course, an intensive, week-long bootcamp that teaches both basic and advanced Python. For those who want a self-paced option, Certstaffix does offer a six-month, on-demand Data Science Programming Essentials e-learning Bundle Course which covers data science and programming with both Python and R.

For younger students aged 13-17, iD Tech offers the summer program Python Camp: Intro to Coding & AI. This summer camp is an in-person option that teaches students coding and data science in a fun, immersive environment. Students will learn Python and machine learning basics and get to explore OpenAI technologies while building their own rock-paper-scissors model and designing a personalized AI system. ID Tech’s camps take place on university and college campuses and those in Philadelphia can find this Python camp offered for day and overnight sessions at Villanova University.

Data Science Corporate Training

If you are looking to upskill or reskill your workforce, consider Noble Desktop’s corporate training options. Noble Desktop offers data science classes, bootcamps, and certificate programs that will help your employees learn important skillsets like Python, SQL, and machine learning. Training can be scheduled onsite at your location, live online, or in-person at Noble’s Manhattan facility.

Discounted bulk vouchers are available for in-person classes at Noble’s training facility. Employers can decide which courses to make available for employees and employees are then able to choose which courses to take based on their training needs and schedule. Email corporate@nobledesktop.com for more information and to schedule a free consultation for your business or organization.

Featured Classes from Noble Desktop

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Featured Classes from Noble Desktop

Top Certificate Programs

Featured Classes from Noble Desktop

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Featured Classes from Noble Desktop

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Data Science Bootcamps Philadelphia, PA

Data Science & AI Certificate Learn The Skills Guarantee™

Noble Desktop Data Analytics Certificate

Noble Desktop Python for Data Science Bootcamp

Noble Desktop Python Machine Learning Bootcamp

Key Insights

Learn More About Philadelphia Data Science Bootcamps

What Can You Do with Data Science?

What Will I Learn in a Data Science Class?

Programming

Web Scraping & Data Wrangling

Machine Learning & Data Mining

Cloud Computing

Problem-Solving

How Hard is It to Learn Data Science?

What Are the Most Challenging Parts of Learning Data Science?

How Long Does It Take to Learn Data Science?

Should I Learn Data Science in Person or Online?

Can I Learn Data Science for Free Online?

What Should I Learn Alongside Data Science?

Industries That Use Data Science

Healthcare

Technology

Manufacturing

Finance

Data Science Job Titles and Salaries

Data Science Classes Near Me

Data Science Corporate Training

Philadelphia Data Science
Corporate & Onsite Training

Top Certificate Programs

Top Courses

Top Certificate Programs

Top Certificate Programs

Top Courses

Top Certificate Programs

Top Courses

Data Science & AI Certificate Learn The Skills Guarantee™

Noble Desktop Data Analytics Certificate

Noble Desktop Python for Data Science Bootcamp

Noble Desktop Python Machine Learning Bootcamp

Key Insights

Learn More About Philadelphia Data Science Bootcamps

What Can You Do with Data Science?

What Will I Learn in a Data Science Class?

Programming

Web Scraping & Data Wrangling

Machine Learning & Data Mining

Cloud Computing

Problem-Solving

How Hard is It to Learn Data Science?

What Are the Most Challenging Parts of Learning Data Science?

How Long Does It Take to Learn Data Science?

Should I Learn Data Science in Person or Online?

Can I Learn Data Science for Free Online?

What Should I Learn Alongside Data Science?

Industries That Use Data Science

Healthcare

Technology

Manufacturing

Finance

Data Science Job Titles and Salaries

Data Science Classes Near Me

Data Science Corporate Training

Philadelphia Data Science Corporate & Onsite Training Noble Desktop

Philadelphia Data Science
Corporate & Onsite Training