This information is useful because it helps the organization make decisions and plan for the future. This multidisciplinary field combines skills like statistics, programming, AI, advanced analytics, and machine learning. Data Scientists work with algorithms, scientific methods, and systematic processes to transform raw, unstructured data into useful information. These data can reveal insights like trends in the business that can help executives make informed decisions designed to help their company grow and provide the best care or services for their customers.
Data science is important to companies of all sizes, particularly large organizations that may otherwise find it difficult to make informed decisions without data to support them. Data Scientists are well paid for their contributions to their organization and often earn six-figure salaries. Not only are Data Scientists in-demand now, but this field has a projected job outlook that is expected to grow 36% from 2021 to 2031, well above the national average for other fields of employment. Those with a background in data science can explore a range of career opportunities in data analytics, machine learning, data science, database administration, business intelligence, data engineering, and data architecture. These professionals work in a range of sectors, including manufacturing, finance, healthcare, automotive, retail, and telecommunication.
General Assembly—Data Science Immersive (Live Online)
Data Science Immersive, available from General Assembly, is a full-time data science bootcamp in which expert instructors provide training on a range of core data science skills. Students learn how to transform complex data into useful insights. They receive instruction in working with data analysis, statistical modeling, and Python. Additionally, those enrolled explore machine learning algorithms of varying complexity such as decision trees and random forests. They also become familiar with neural networks and natural language processing. Participants in this bootcamp complete five projects and assemble a professional-grade portfolio that contains data visualizations and stakeholder presentations. The capstone project in this class involves using machine learning models to tackle a real-world data challenge.
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Tuition for this bootcamp is $16,450 when the fee is paid upfront. This reflects a $450 discount. This fee can also be paid in installments, loans, or income-share agreements. As a prerequisite to enrolling in this intermediate-level class, students should have a basic understanding of Python and programming basics.
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In addition to hands-on training in data science, Data Science Immersive also provides 12 hours of online tutorials for pre-work to prepare students for the bootcamp. This pre-work includes instruction on exploratory data analysis, data science fundamentals, machine learning models, and statistical modeling. This bootcamp also includes office hours sessions with TAs, where students receive individual guidance and feedback. Students also have access to career services, which can help with the job search or salary negotiations. In addition, those enrolled also receive technical interview prep. This program requires several weeks of full-time study to complete.
Those who have already completed this bootcamp shared their reviews online. One learner noted, “The best thing about my program was the sense of community. The instructors remain close colleagues, and the same for students. I’ve made friends and gotten jobs from meeting people at events held at GA.”
NYC Data Science Academy—Data Science with Machine Learning (Live Online)
NYC Data Science Academy’s Data Science With Machine Learning is an immersive bootcamp that provides participants with a range of real-world data skills necessary to pursue a data science career. Those enrolled learn how to work with tools and skills like R and Python, machine learning, data analytics, and data visualization. Participants receive instruction on how to create statistical models and work with tools like Spark, Hadoop, and AWS. This bootcamp is unique in that it covers both Python and R for data analytics and visualization. Students complete four application projects that involve real-world business considerations and datasets. In addition, the capstone project is typically sponsored by a New York City company. By the end of this program, students will be able to work with the main tools and skills needed for machine learning and data analysis.
Key Information
This bootcamp takes 12 weeks to complete and costs $17,600. Tuition can be paid upfront or via third-party financing options. Two merit-based scholarships are available: Women in Data Science Scholarship and Post-Doctoral Student Scholarship.
As a prerequisite, students are provided with 40 hours of online work, which includes more than 200 exercises. This content prepares learners to work with Python and R, as well as use basic mathematical concepts in calculus, statistics, and linear algebra.
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In addition to live online instruction, tuition includes lifelong career support. Students can take advantage of one-on-one resume reviews, networking opportunities with hiring partners, and interview training.
Participants who graduated from this program shared their experiences online. One learner wrote, “Within a few weeks after graduating, I was offered my first full-time job as a Data Engineer. NYC Data Science Academy is very successful at getting their students fluent in the tools and technologies of data science and prepared for finding a great job in the field.” Another said, “The opportunity to network was incredible. You are beginning your data science career having forged strong bonds with 35 incredibly intelligent and inspiring people.”
Noble Desktop—Data Science Certificate (In-Person in NYC & Live Online)
Data Science Certificate is available for those interested in taking a deep dive into the skills and tools needed to pursue a career in data science. This beginner-friendly, hands-on program teaches students how to manipulate and analyze data, as well as the skills needed to pursue entry-level Python engineering or data science roles. Those enrolled in this certificate program work with Python’s main data science libraries for data analysis. They write and read database queries, clean data for analysis, and work with Python to automate repetitive tasks like updating, formatting, and aggregating data. Learners also create machine learning models based on data and study their performance. By course completion, students will be able to create and present data visualizations and dashboards using Seaborn, Dash Enterprise, Plotly, and Matplotlib. They will also deploy these projects on GitHub so they can be shared with potential employers.
Key Information
Tuition for this certificate program is $3,995. It takes learners 114 hours to complete this certificate. This class can be completed in four weeks of full-time study or 20 weeks of part-time coursework. Tuition can be paid upfront, through installments, or with 12-month financing.
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In addition to small class instruction in the in-person or live online environment, students also receive six one-on-one mentoring sessions. This time can be used to work on professional portfolios, revisit complicated class concepts, improve resumes or LinkedIn profiles, or for other professional development. All students can retake this class for up to one year at no additional cost.
Graduates of the Data Science Certificate Program shared their reviews online. One learner wrote, “I started with no prior knowledge of Python and by the end of the course, I was able to complete a machine learning project using Python.” Another said, “Having no prior knowledge or experience in computer/data science, this course prepared me to use and apply Python.” A third graduate noted, “This was an excellent class that provided me with a deep and valuable understanding of Python and data science.”
Flatiron School—Data Science Bootcamp (Live Online)
Data Science Bootcamp is available for those interested in exploring emerging data science technologies and the most current AI tools used in this field. This class begins with prework in data science foundational skills. Students then progress into working with Python and SQL. Instruction is provided on how to work with real-world datasets that are often messy and extract insights that can then be shared as data visualizations. Students also work with Python’s scientific computing tools such as Pandas, SciPy, and NumPy, to create high-quality data reports. The machine learning portion of this program provides guidance on using statistical models to form predictions about unseen data, as well as instruction on AI theory that includes overfitting, regularization, and data leakage. By the end of this bootcamp, those enrolled will be familiar with advanced AI models, model interpretability, and deployment.
Key Information
Tuition details for Data Science Bootcamp are available upon request on Flatiron School’s website. Three payment options are available: upfront payment, loan payment, and monthly installment plans with no interest. This course can be completed in 15 weeks of full-time study in the live online format or 40 weeks of self-paced asynchronous study for those interested in part-time coursework. No prerequisites are listed as a requirement for study.
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Students in this course all complete a capstone project that draws from everything they’ve learned in the class. This independent machine learning project can be included in a professional portfolio and shared with potential employers. As part of tuition, students also have access to Flatiron School’s career services team. Career coaching is available to all students. In addition, learners have access to a national network of hiring partners.
Graduates of this bootcamp shared their experiences online. One student said, “I felt that I had so much support. I was a beginner studying Python and SQL. Every project applied what we just learned to real-world problems, and that ended up impressing my interviewees. Especially the final project.” Another student wrote, “I was most surprised by how quickly it went and how much I learned in such a short time. There were many occasions when I told my partner, ‘A week ago, I had never heard of this technique, and now I’m doing it.’”
NYC Data Science Academy—Data Science with R: Data Analysis and Visualization (Live Online)
Data Science with R: Data Analysis and Visualization is available for those interested in a comprehensive overview of working with the R programming language. This program commences with a basic overview of R. Students learn how to process, manipulate, analyze, and visualize data. They also receive instruction on creating data reports. Those enrolled explore how to treat basic data elements and work with “dplyr” for data manipulation. They become familiar with how to generate graphs, write functions, and fit data into basic statistical models. By the end of this program, those enrolled will be able to design their own basic and complex data visualizations such as time-series diagrams, mosaic plots, and violin plots.
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Tuition for this program is $2,190. It takes five weeks to complete this class and requires seven hours/week of in-class time. This is a beginner-friendly program. It is helpful if those who enroll have basic computer programming knowledge as a prerequisite.
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Those who successfully complete this course are awarded a certificate at the end.
Alumni from this program shared their experiences through written reviews. One graduate wrote, “The instructors we have are AMAZING! They are so knowledgeable and very passionate about data science. TAs are the most hard-working group of people I know! The students are impressive as well.” Another student shared, “In my mind, there is no such thing as a perfect bootcamp, but NYC Data Science Academy got as close to perfect as it can get for me. This curriculum is the most comprehensive of all the data science bootcamps available.”
Digital Workshop Center—Data Science Certificate Program (Live Online)
Data Science Certificate is an advanced-level data science class that prepares students to work with a range of core tools, programming languages, and data skills. Students learn how to work with R software in this program. Instruction is provided on how to clean and organize data, as well as spot key data features. Participants write functions, plot data, and work with a basic linear regression model. They also become familiar with practical applications of statistics in the business sector. This certificate program teaches those enrolled how to automate repetitive tasks and design automated reports. By the end of this program, those enrolled will have a basic understanding of optimization and machine learning.
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This certificate costs $5,995. It takes most learners between three and four months to complete their studies. All students have up to one year to finish coursework once they are enrolled. As a prerequisite to study, students should have completed Microsoft Excel Level 2 and Microsoft Excel PivotTables and PivotCharts or have a similar knowledge base. It is also suggested that students interested in enrolling know basic programming concepts and how to apply them in a business setting. This class also requires a pre-assignment that must be completed before the first meeting.
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In addition to in-class work, all participants can retake this course for free for up to a year. Students receive one-on-one mentoring while enrolled in classroom training and can continue with this mentoring for a month after completing this class. Those enrolled have the option of completing a capstone project that can be included in a professional portfolio. Toward the end of this certificate, students work closely with expert career coaches to begin their job search. They can use career services like job search workshops and one-on-one resume writing sessions.
Practical Programming—Data Science Immersive (In-Person in NYC & Live Online)
Python for Data Science Immersive is a fast-paced course that teaches students a range of practical Python applications in the field of data science. Participants study foundational programming concepts such as loops, objects, and functions. They also work with various types of data, like lists, strings, and integers. Instruction is provided on using conditional statements to selectively alter control flow when programming. Those enrolled in this immersive class become familiar with how to use Python libraries Pandas and NumPy to analyze tabular data and how to work with Matplotlib to visualize data. By the end of this class, learners will be able to use scikit-learn to predict outcomes.
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Tuition is $1,495. It takes five full days of study, or ten part-time sessions, to complete this 30-hour program. There are no prerequisites to enroll in this class.
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All participants receive a verified certificate of completion for graduating from this program and can retake this class for free for up to one year. Remote setup assistance is available for those who need it. Class recordings are available for up to one month following the completion of this course.
Those who graduated from Data Science Immersive shared their reviews online. One student wrote, “If you’ve never programmed and are looking for a school with classes that will get you up to speed quickly in a way that’s easy to follow and understand, this is the school to do that.” Another participant said, “This course was very helpful for people looking to advance in their careers. The instructor was very patient and helpful.” A third student shared that “This is an excellent class. It taught me Python’s building blocks. I highly recommend this class.”
Data Incubator—Fall Data Science Essentials Program (Live Online)
Those who are interested in learning core data science skills can enroll in Data Incubator’s Fall Data Science Essentials Program. This live online course provides those who are new to data science with hands-on training in a range of core techniques and skills. Students learn how to use Python to gather, clean, and analyze data. They also use its libraries to create predictive models capable of making informed decisions. Students gain training in creating machine learning models and working with relational databases. This program is intended for those who are new to working with Python and want to learn more about this language, as well as professionals like Software Engineers, Data Engineers, Data Analysts, Researchers, and Economists interested in gaining experience working with quantitative analysis and machine learning.
Key Information
Tuition for this program is $1,000 for those who book early. This fee increases to $2,895 for those who wait until the week before class to enroll. As a prerequisite, students should have a basic understanding of statistics, as well as the fundamentals of programming. This program spans 16 sessions, each of which is two hours long.
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Students who successfully complete this program automatically qualify for admission into the TDI Fellowship cohort. The price paid to attend Fall Data Science Essentials Program will be deducted from tuition for those who pay upfront.
Net Com Learning—Designing and Implementing a Data Science Solution (Live Online)
Designing and Implementing a Data Science Solution provides students with training in how to use Azure services for developing, training, and deploying various machine learning solutions. Students begin with an overview of which Azure services support data science. This course then progresses into how to use Azure’s Machine Learning service for automating the data science pipeline. Those interested in attending this class should already be familiar with the data science process because this course focuses exclusively on Azure. The target audience for this program is Data Scientists who work to train and deploy machine learning models.
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This program is available for $2,495. Those interested in enrolling should have a basic understanding of data science concepts like how to prepare data and train models. They should also be familiar with how to program with Python and use libraries like Pandas and Seaborn. It is also suggested that students complete Microsoft Azure Fundamentals, a one-day class, before enrolling. It takes four full days of study to complete this class.
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In addition to classroom training, students also receive PDFs of all courseware and lab manuals.
NYC Career Centers—Python for Data Science Bootcamp (In-Person in NYC & Live Online)
Python for Data Science Bootcamp takes participants from Python programming basics up through machine learning. This hands-on program teaches those enrolled how and why Python is used in data science. Students learn how to handle data with Python, create programs and data visualizations, and work with statistics to create machine-learning models. Fundamental Python concepts are covered such as writing basic expressions, understanding various types of data, creating variables, and using indexing and lists. IDLE programming and object-oriented programming are also taught. Part two of this class teaches learners to work with control flow tools and conditional statements. Instruction is provided on using dictionaries, writing loops, and creating functions. In part three of this class, those enrolled study data science operations and tools. Participants use Pandas and NumPy to import and clean data. They then analyze and visualize data using Matplotlib, Pandas, and NumPy.
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Tuition for this bootcamp is $1,495. It takes 30 hours to complete this program.
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Tuition includes the option of a free class retake for up to one year. All participants receive a digital certificate of completion upon graduation and can keep their proprietary workbook.
Frequently Asked Questions
What Are the Different Types of Online Data Science Classes?
Learning data science in the online environment is an excellent way to acquire this in-demand skill set. Online coursework is available for those who are new to data science and working with data in general, as well as seasoned data professionals interested in acquiring advanced training for work-related reasons or pursuing a new career path entirely. Students interested in learning data science online can select from live coursework and on-demand classes.
Live online data science classes provide learners with real-time access to an instructor. Participants connect with an expert instructor via teleconferencing platforms like Teams or Zoom. Not only does this training format allow students to connect with a live teacher, but it also provides an opportunity to engage with other learners. Those enrolled can ask questions in real-time and even share their screen with the instructor (with permission) to receive additional guidance or support. Live online classes require that participants attend regularly scheduled classes, which may be challenging for some learners with busy work schedules or personal commitments. However, since all coursework can be completed remotely, no commute is required, and participants can complete data science study from the comfort of their home or office space.
Live online data science classwork is available in a specific data science concept or skills such as Python for Automation, or can provide an overview of the field of data science in general and a range of tools, languages, and processes used in it. Students can select from skills courses, which provide introductory-level instruction and take just a day or so to complete online. Coursework is also available in data science bootcamps and certificate programs, which are longer and also offer additional benefits such as career counseling, resume support, or one-on-one mentoring, depending on the provider. Live online data science classes typically cost the same as in-person study and range in price from several hundred dollars for short skills classes to thousands of dollars for bootcamps or certificate programs.
On-demand data science training is also available from many top educators. This is the most flexible way to learn data science for those with busy schedules. On-demand content is pre-recorded, which means that an instructor taught the lessons at an earlier time, put them online, and those enrolled can access them remotely. This learning format allows students to not only choose where and when they wish to study but also dictate their learning speed. Since no scheduled days and times for class meetings are required when learning through self-paced material, students can spend as little or as much time on their data science studies as they want. This type of learning allows participants to complete coursework after work, while traveling, on weekends, or even during lunch breaks. Students can choose to study for fifteen minutes at night or spend an entire weekend cementing more complex data science concepts such as machine learning. Additionally, learners can pause, rewind, and rewatch content as often as needed to help reinforce concepts.
There are several important factors to consider when selecting self-paced data science training material. Since the material is pre-recorded, no live instructor is available. This may make it challenging for some students, especially those who are new to data science, to grasp complicated concepts. Because so much on-demand content is currently available online, it can also be challenging for some learners to select that which is the most up-to-date and reflects the current best practices in data science. This is why it’s important to do a bit of research before enrolling in a self-paced class to make sure it’s at the right learning level, is taught by a reputable educational provider, and is current.
Asynchronous data science coursework is often a more affordable alternative than live content. Some providers offer courses for under $100; others even provide free training materials, like YouTube videos or online tutorials. For those who aren’t certain whether data science is their choice field, self-paced material can provide a low-stakes way to get started without having to invest thousands in coursework. It can also be a great starting point for data professionals interested in brushing up on their skills. However, for those who intend to apply their training to their current profession, or to pursue a new career path entirely, more structured data science coursework such as an in-person certificate program or live online bootcamp, may ultimately be a more effective way to acquire advanced training.
What Will I Need for an Online Data Science Class?
Those who are interested in studying data science in the online environment must have a reliable computer with a strong internet connection. In addition, most programs will require students to work with several programming tools and languages. One of the most common data science programming languages is Python. This open-source language is free to download. In addition, many data science programs also teach students to work with SQL and servers like SQL Server, which are also available as a free download. Depending on the program requirements, other software and tools may be required to study data science such as Microsoft Excel for data organization or Tableau for data visualization. Excel can be purchased from Microsoft. A free trial is also available. Tableau is available for purchase and can also be downloaded as a free trial.
Whereas in-person study provides students with a computer lab with these programs and languages already installed, those who elect to learn online will have to ensure they have the necessary tools. Some educational providers offer students instructions on downloading the needed software or programming languages. It’s important to check with the educator offering a course to ensure that you have the required software, programs, and coding languages on your device before the beginning of class.
Can I Learn Data Science Online for Free?
In addition to for-pay online data science training, free material is also available online from some top educators. Providers like Coursera, Udemy, and Noble Desktop offer free YouTube video content, webinars, and training classes designed to help students start studying data science. Since no monetary investment is required, these resources provide a good way for learners to explore this topic without having to invest hundreds or thousands of dollars into coursework.
Those interested in exploring free training material can select from short online videos that teach one specific skill such as data cleaning, or can opt for more comprehensive instruction that provides an overview of the field of data science and the most commonly used tools. Learners can choose one or multiple free resources as necessary. However, since free data science material was pre-recorded, no instructor is present. This means that it can be difficult for participants to receive clarification about complex data concepts and skills in this format. For this reason, to truly learn up-to-date data science skills, it’s important for most learners to enroll in live coursework at some point in their studies.
Is It Better to Learn Data Science in a Live or Self-paced Class?
Those who are committed to studying data science online may wonder whether it’s more effective to enroll in live study or to opt for self-paced content. Both have their own advantages as well as drawbacks.
Since live online data science classes occur in real-time, they provide an interactive way for students to study this topic. Participants receive hands-on training from an instructor with industry experience using a range of data science tools and have the opportunity to ask questions as they arise and receive immediate support and clarification. Additionally, live study also offers participants the benefit of connecting with other learners, which can be a chance to network and connect with like-minded professionals. This type of training requires participants to attend regularly scheduled classes, which may mean having to take time off of work or make scheduling arrangements to accommodate data science study. The benefits of learning in the live environment, however, make it worthwhile for students to consider studying in this format. Learning in the live online environment makes it easier for most students to fully grasp course material and have the necessary support to learn complicated topics.
On-demand data science class is an even more flexible learning option than live online content. Students can choose when and where to complete training. They can devote fifteen minutes a week to coursework or devote full days to learning data science as their schedule permits. Unlike live online content, in which the instructor sets the learning pace, those who opt for asynchronous training material can determine their own learning speed and devote as much time as needed to a concept before moving on. Since no live instructor or cohort of learners is present, though, those who opt to study data science through self-paced materials must be able to learn independently and seek answers to questions they have to truly get the most out of coursework.