Organizations hire Data Scientists to help them gain insights into big data and use data findings to inform their decision-making process. These professionals decide which questions their organization should be asking and devise ways to answer these questions with data. This process often involves creating predictive models for forecasting. On a daily basis, Data Scientists perform a range of tasks. They locate trends and patterns in data that can lead to deeper insights. They design data models and algorithms for theorizing and predicting outcomes. Data Scientists work with machine learning to improve the products being offered or the quality of the data being used. Once they’ve made data discoveries, they communicate recommendations based on them to other team members or senior staff within the organization. To perform these tasks, Data Scientists use tools and programming languages like data analysis, R, Python, SQL, and SAS. They also must stay current on data science best practices and innovations.
Pursuing a career in data science can lead to a range of high-paying career options in multiple sectors. This skill set has applications in many fields such as education, banking, and journalism. Organizations in almost every industry are interested in employing Data Scientists. Although many positions in data science are available, there aren’t enough applicants with the skill set needed to fill these openings. This is why those who excel at data storytelling, have computational and quantitative data skills and are clear communicators have a competitive advantage when applying for positions. Pay rates are competitive for qualified Data Scientists, averaging six figures nationwide. Additionally, this field is expected to continue to experience an above-average growth of 36% through 2031, which is much faster than other fields.
The Best On-Demand Data Science Classes
The following sections explore some current on-demand data science classes from top providers around the country.
Udemy—The Data Science Course: Complete Data Science Bootcamp
On-demand data science instruction is available from Udemy in its Complete Data Science Bootcamp. Those enrolled in this self-paced bootcamp are provided with a comprehensive toolbox necessary to pursue a career as a Data Scientist. A range of core data science skills and concepts are covered such as basic and advanced statistical analysis, Tableau, deep learning with TensorFlow, machine learning stats models, and Python programming with Pandas, NumPy, and Matplotlib. Those enrolled become familiar with how to pre-process data and study the math behind machine learning. Instruction is provided on using Python for logistic and linear regression, as well as statistical analysis. By the end of this bootcamp, participants will be able to apply the skills they acquire to real-life business cases. They will also be able to use deep learning frameworks like Google TensorFlowDevelop to solve various big data tasks.
Key Information
Tuition for this bootcamp is $110. This program provides 31 hours of video content. No prerequisites are listed for study.
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In addition to 31 hours of on-demand video instruction, this bootcamp program also includes 542 downloadable resources, 92 articles, and 122 coding exercises. All participants receive a certificate of completion for successfully graduating from this bootcamp.
Graduates of this program shared their feedback online. One learner wrote, “This is a very good course that covers almost everything.” Another shared that the “concept and formulas were nicely explained.” A third learner said, “This course provides a good introduction to data science with well-written videos and examples. They are shown in a way that stirs curiosity and makes someone want to learn more about the subject.”
Noble Desktop—Python for Data Science & Machine Learning Bootcamp
Noble Desktop’s Python for Data Science & Machine Learning Bootcamp is intended to teach participants a range of Python skills necessary for data science. Those enrolled learn how to work with Python to manipulate databases and perform different types of analyses on data. This bootcamp begins by covering fundamental Python programming concepts such as working with data science libraries Pandas, Matplotlib, and NumPy to analyze data. Those enrolled then progress into creating predictive models with scikit-learn and other machine learning packages. Instruction is provided on how to use Python to automate basic repetitive tasks like formatting, aggregating, and updating data. The last unit in this class covers Seaborn, Matplotlib, Dash Enterprise, and Plotly and how they can be used to create interactive dashboards and data visualizations. Graduates of this program will have the necessary skill set to apply for entry-level positions in data science and Python engineering.
Key Information
This bootcamp costs $3,495. Financing options are available. It takes 96 hours of live online class time to finish this program. No prerequisites other than basic computer skills are required.
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In addition to hands-on training in the interactive virtual environment, tuition includes added perks like the option of a free bootcamp retake for up to one year. Students also receive four one-on-one mentoring sessions in which they can help with their job application materials, professional portfolios, resumes, or LinkedIn profiles. All lessons are recorded and available online the day after they are taught. These lessons are available for students for up to a month after completing this course. Those who graduate from this bootcamp receive a verified digital certificate.
Coursera—Data Science: Statistics and Machine Learning Specialization
Data Science: Statistics and Machine Learning Specialization is a flexible course that allows participants to decide the speed at which they learn statistics and machine learning. Students in this course learn core data and statistical skills such as how to create and apply various prediction functions, how to perform regression analysis, and how to execute least squares and inference with regression models. Those enrolled will gain skills like knowledge of R programming, familiarity with GitHub, machine learning, and data visualization. This class is broken into five sections: Statistical Inference, Regression Models, Practical Machine Learning, Developing Data Products, and Data Science Capstone. Industry experts teach this course and provide students with hands-on projects.
Key Information
Those interested in taking Data Science: Statistics and Machine Learning Specialization can enroll for free. This intermediate-level course takes three months to complete at a ten hours/week pace. As a prerequisite, those interested in enrolling should first complete the Data Science: Foundations Using R specialization to gain the necessary foundational knowledge.
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Those who graduate from this program receive a career certificate from Johns Hopkins University.
Graduates of this Coursera program shared their experiences. One learner said, “Being able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood.” Another noted, “I directly applied the concepts and skills I learned from my course to an exciting new project at work.”
Udacity—Programming for Data Science with Python
Programming with Data Science with Python is intended for those who wish to pursue a career in data science. This class covers a range of core data science skills and tools, like using SQL, Python, Git, and Command Line. Those enrolled receive introductory-level SQL instruction in topics like working with aggregations, JOINs, and subqueries. They also become familiar with how SQL can be used to find solutions to complicated business problems. Learners then progress into basic Python programming training and work with variables, data structures, functions, and loops, as well as libraries like Pandas and NumPy. Next, learners progress into working with version control and have the chance to share their work with others who work in data science.
Key Information
This beginner-friendly course is available as a platform subscription. The first month costs $399; three months of access costs $1,017. It takes three months to complete this class for students who work at a ten hours/week pace. There are no required prerequisites beyond basic computer proficiency.
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All students who enroll in this class have access to career support as well as on-demand help with coursework.
Students who took this course wrote online reviews to share their experiences. One participant noted, “The projects were very effective in helping me apply the lessons I learned in this course. I especially appreciated the Python project. To say that I highly recommend this course would be an understatement!” Another student shared, “I really liked this class and think things were very well explained. The classes are not long, so they never get boring.” A third participant said, “I had a terrific experience going through this program. The program’s content is excellently structured with an approach that breaks down complex concepts into tiny portions to aid assimilation.”
Udemy—Statistics & Mathematics for Data Science & Data Analytics
Statistics & Mathematics for Data Science & Data Analytics is available from Udemy for those interested in self-paced data science content. Participants in this program receive instruction on core statistical concepts and how they apply them to data analytics and data science. Instruction is provided on probability theory and descriptive statistics. Students work with various probability distributions such as poisson distribution and normal distribution. Those enrolled explore topics like p-value, type 1 and two errors, and hypothesis testing. They also work with multiple linear regression, logistic regression, and regression trees. By the end of this program, learners will be familiar with RMSE, coefficient of determination, MAE, and correlation. This program is intended for those who wish to pursue a data science career, as well as for individuals interested in learning the necessary statistics required to analyze data and master statistics and probabilities for data science.
Key Information
Tuition is $90. More than 11 hours of on-demand video instruction are provided. No prerequisites are required to enroll in this class save for an eagerness to learn.
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In addition to over 11 hours of on-demand video content, those who enroll in this course also have access to five downloadable resources and three articles. They also receive a certificate of completion upon graduating.
Graduates of this class shared their experiences online. One participant said, “Thank you for this opportunity to learn. It was insightful and interesting.” Another shared, “This teacher was great. He chose the important concepts and illustrated them with examples, followed by step-by-step solutions and good computer models.” A third participant noted, “The material and modules are very well structured.”
Skillsoft—Data Science Core Concepts: Data Science Beginner
Data Science Core Concepts: Data Science Beginner is a fifteen-part, on-demand course that covers a range of data science skills and concepts. Those enrolled in this program receive instruction on topics like how to scrape, filter, and integrate data. They also explore fundamental data analysis and visualization concepts. Once these basics are covered, learners then progress into more complicated data science training with big data, machine learning, and streaming data. Students also explore how to work with R for exploratory data analysis, as well as how to implement predictive modeling with machine learning. By course completion, those enrolled will be able to share their data findings with various audiences.
Key Information
This course is available as part of a platform subscription. Subscription packages are available starting at $19/month for individuals. This twelve-part class consists of 14-plus hours of video content. This beginner-friendly class does not require any prerequisites.
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Those enrolled have access to nine books and one audiobook containing relevant data science material. All learners receive a digital badge upon completing this class.
Udacity—How to Become a Data Scientist
How to Become a Data Scientist is an intermediate-level course that teaches a range of data science skills such as Python programming, SQL, statistics, and machine learning. This course is broken into five units: Solving Data Science Problems, Software Engineering for Data Scientists, Data Engineering for Data Scientists, Experiment Design and Recommendations, and Data Science Projects. This program begins with instruction in creating data visualizations and presenting data findings. Students then learn about data pipelines and data engineering. Those enrolled study best practices to design and test experiments. At the end of this course, those enrolled will complete a capstone project to showcase their newly acquired data science skills.
Key Information
This on-demand program is available via platform subscription. It takes most people four months to complete their studies at a ten hours/week pace. As a prerequisite, those interested in enrolling should be familiar with machine learning concepts such as those covered in Udacity’s Machine Learning Nanodegree Program. Additionally, students should also have a background in probability, statistics, and Python programming.
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In addition to on-demand data science lessons taught by industry experts, tuition to this class includes real-time support that allows students to receive instant assistance with their learning while in the classroom. Participants also have access to career services, including LinkedIn profile assistance and a GitHub portfolio review.
Those who completed this program shared their experiences through online reviews. One learner said, “The program is comprehensive, with all the aspects that you expect for Data Scientists. I love the teachers at Udacity, who make the program really fun and keep me highly motivated.” “Another participant shared, “I will always recommend Udacity programs to people. They are information-packed and full of knowledge. The hands-on mode of teaching makes it even more interesting. Kudos to the Udacity team!” A third graduate noted, “This program is definitely everything that I expected and more.”
Coursera—Introduction to Data Science Specialization
Coursera’s Introduction to Data Science Specialization is available for those interested in learning the basics of machine learning and data science, as well as the various tasks Data Scientists perform in the workplace. Participants receive hands-on training using various data science tools such as R Studio, Watson Studio, GitHub, and JupyterLab. Those enrolled also cultivate a data science mindset in which they follow a methodology to approach data science problems. Instruction is also provided on how to write SQL statements and use Python from Jupyter Notebooks to query cloud databases. In addition, those enrolled gain familiarity working with relational database management systems.
Key Information
Introduction to Data Science Specialization is available for free. Because this is a beginner-level class, no prior experience in data science is required. It takes learners two months to complete coursework if they devote ten hours a week to study.
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All learners who complete this class are given a digital certificate to showcase in their resumes.
Graduates of this program shared their impressions online. One student said, “When I need courses on topics that my university doesn’t offer, Coursera is one of the best places to go.” Another student noted, “Learning isn’t just about being better at your job. Coursera is one of the best places to go.”
Udemy—Python for Data Science and Machine Learning Bootcamp
Udemy’s Python for Data Science and Machine Learning Bootcamp offers training in how Python can be used to complete a range of machine learning and data science tasks. Participants in this asynchronous class work with Spark to perform big data analysis. They become familiar with how to use NumPy to handle numerical data, as well as Pandas for analyzing data. Instruction is provided on performing Python plotting using Matplotlob and statistical plotting with Seaborn. Students also become familiar with how Plotly can be used to create interactive data visualization and how scikit-learn can aid with machine learning tasks. By the end of this program, those enrolled will also be familiar with natural language processing, spam filters, neural networks, and linear regression.
Key Information
Tuition for this bootcamp is $100. Participants receive 25 hours of on-demand video content.
As a prerequisite, students should have some prior experience in programming. They also must have administrative permissions on their device to download the necessary course files.
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In addition to 25 hours of video content, students in this bootcamp also have access to 13 articles and five downloadable resources. Those who successfully finish this program receive a certificate of completion.
Graduates of this bootcamp shared their reviews online. One learner said, “This is an excellent course for beginners and is easily understandable. I recommend it for anyone interested in learning machine learning and data science.” Another wrote, “This is a great course! Even though I already had some knowledge of Pandas and Matplotlib, the sections dedicated to these libraries were still useful and refreshed my memory.” A third student shared, “This course is very good and practical. I love that there was a project to tackle after each topic or section.”
CareerFoundry—Data Analytics Program
Data Analytics Program, which is offered by Career Foundry, provides rigorous training in a range of data skills such as testing, analyzing, and visualizing data. Participants also learn how to create dashboards, execute queries, and solve real-world customer problems. Coursework helps students build a technical skill set and master many of the tools commonly used for data analysis and visualization, as well as statistical evaluation. By the end of this program, learners will be familiar with Python and its library, Pandas, as well as Excel, and Tableau.
Key Information
Those who pay for this program upfront can do so for $7,505. Monthly installment payment plans are also available, and those who opt for this payment form will require an upfront payment of $1,400 and ten months of payments of $650.This flexible program prepares participants for a career in data in eight to ten months of part-time study. Those who opt for full-time coursework can complete this class in five months. No prerequisites are required.
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All students have lifetime access to the curriculum following completion of this class. Tuition also provides participants access to a team of active industry experts who are available for one-on-one mentoring for each assignment and project review, as well as the capstone. Those enrolled can tailor their studies around their professional needs and choose between Machine Learning with Python or Data Visualization with Python. Participants also have the chance to gain hands-on apprenticeship training with CareerFoundry partners like Democracylab, TechFleet, or Digital Product School. Those enrolled can also take advantage of one-on-one career specialist guidance through Career Support Services. If a graduate of this program is not offered a job within six months, they are eligible for a full tuition refund.
One graduate of the program shared their gratitude for their apprenticeship experience. They wrote, “I am beyond grateful for the apprenticeship, as it actually led to me landing a full-time job.
Frequently Asked Questions
Is an On-demand Data Science Class Worth It?
Deciding whether to pursue data science training through on-demand coursework will likely depend on several factors. Since on-demand content doesn’t include a live training component, this format requires that learners be self-motivated. Those enrolled may need to find answers to questions on their own and will not have the support of a cohort of learners or an instructor. This can make it challenging for some individuals, especially those who are new to data science, to fully master complex material.
Another important consideration when deciding whether to enroll in self-paced data science coursework is why the learner wishes to acquire this training. For those looking to fill a skill gap or learn data science basics, on-demand content can be a low-stakes way to receive basic training. However, for those wishing to study data science for professional reasons such as to complete a work project or to apply for a new data-related career, self-paced study may not suffice. Eventually, a more structured learning format such as an in-person bootcamp or a live online certificate program, may be necessary to fully learn advanced data science skills and programming languages.
What Will I Need for an On-demand Data Science Class?
Those who decide to learn data science through on-demand study will need several tools to help them succeed. First, a computer with a stable internet connection is required to complete lessons and coursework. Additionally, a comfortable study space that’s free of distractions such as a home office, is important for facilitating study.
Data science is a multidisciplinary field that requires several tools and programming languages. When students study in-person at a training facility, these are usually installed on the provided computers. However, for remote learners, it’s important to ensure these tools are available before commencing studies. It’s important to check with the educational provider prior to starting coursework to see what tools or software are required for study. Some of the most common tools in data science are SQL, Python, R, Tableau, and Excel. MySQL is an open-source relational database management system that can be downloaded for free. Python is also open-source and free to download. Additionally, R is also an open-source programming language that’s available as a free download.
Those who enroll in data science classes that cover data visualization may also use tools like Tableau and Excel. Tableau is available for purchase or as a free trial directly from the manufacturer. Excel can be downloaded from Microsoft’s website. Those interested in downloading Excel can purchase it as a stand-alone application or as part of the Microsoft 365 suite of productivity apps.
Can I Learn Data Science On-demand for Free?
Studying data science doesn’t have to cost hundreds or thousands of dollars. A large amount of online content is available in data science, much of which is offered as on-demand training material. Some educators offer coursework for under $100; others provide free classes. Those who are interested in acquiring basic data science skills such as learning the basics of data analysis and visualization, or are interested in an overview of the field of data analytics, can gain introductory-level training through free asynchronous training materials. Since no monetary commitment is required, this learning format is a low-stakes way to begin studying data science. Those who enroll in free on-demand coursework can discontinue studies at any point without accruing any debt. They can also explore a range of data science tools and techniques such as working with R, data cleansing, or machine learning, without enrolling in a costly and time-intensive certificate program.
A variety of free on-demand data science content is available. Some training material is short such as YouTube videos that span just several minutes and hone in on one specific tool or skill. Other programs take weeks or months to complete and offer more robust, intensive data science training. It’s important when studying through free on-demand materials to select content that’s up-to-date and reflects the current best practices and most-used tools. Free, self-paced study material is often a good starting point when beginning to study data science. However, for learners who are interested in exploring data science for professional reasons, enrolling in live coursework down the line may be a more effective way to fully master this complex field.
Is It Better to Learn Data Science in a Live or Self-paced Class?
Deciding whether to study data science through live coursework or self-paced study is another important consideration for learners. Both have their own benefits and drawbacks.
Live study, whether in-person or in the online format, is the most engaging and interactive way to learn data science. Students benefit not only from the expertise of an instructor with industry experience but also from the support of a cohort of learners who are studying alongside them. Live study allows participants to ask questions as they arise and receive instantaneous clarification and support. One important consideration of live study is that it requires attending class at regularly scheduled times. This may mean having to take off work to accommodate data science study. It also may require commuting to class for those who elect to learn in the in-person environment. Because live data science coursework occurs in real-time, it is paced at the speed the instructor chooses, which ensures lessons will be completed on schedule and all content will be covered during the duration of the program.
Self-paced coursework is taught asynchronously, which means an instructor pre-records lessons, and students can access them later. Unlike live training, those enrolled in self-paced study can choose not only when and where they wish to study but also how long they want to devote to their training. Some students may only have time on the weekend to learn data science, whereas others may wish to spend 30 minutes a night on coursework. Self-paced study is the most flexible way to learn data science. Participants can pause and rewind video content as often as necessary to fully understand data science concepts. They can also rewatch entire lessons or videos to reinforce the skills they are learning. For those who have busy work schedules or must schedule data science study around travel personal commitments, self-paced material offers a platform in which students can still receive training without committing to regularly scheduled class meetings. While it can be challenging to learn advanced data science skills without the benefit of a live instructor, on-demand content is a good way to begin exploring data science before committing to more structured coursework.