According to a recent study by Forbes, human beings are generatingapproximately 2.5 quintillion (2,500,000,000,000,000,000) bytes of data every day, and this has only risen in the past few years. As we generate more and more data, companies and organizations have begun collecting and analyzing that data to uncover trends and patterns that they can utilize to optimize their workflow and long-term strategies. Data Scientists are the professionals who build and maintain the systems that collect, organize, and interpret this data, projects that range from applications that simply scrape user data from visitors to a webpage to complex machine learning algorithms that can read and interpret data on their own. These skills are in high demand, and learning data science can be a productive career path to follow since, according to the Bureau of Labor Statistics, job openings in data science areexpected to grow 36% year over year during the next decade, which is over 700% faster than the national average.
Noble Desktop: Data Science Certificate Program
Key Information: This career-focused certificate program is available in-person or online. The course runs for four weeks full-time (weekdays), or 20 weeks part-time (evenings or Saturdays). Students enrolled in this course will receive professional development training, including one-on-one career mentoring sessions. Any students in the course can retake it for free within one year.
Students seeking a comprehensive, career-focused training program should consider enrolling in Noble Desktop’s live in-person or online Data Science Certificate program. In this course, students will learn the foundational theoretical and practical computer science skills that underlie complex data science projects. Students will learn how to read and write computer code using Python and how data scientists approach problems and plan solutions. Students will learn how to create and work with databases, and they will learn the foundational theories that are utilized in complex data science projects. This course provides students with a collection of skills that they can apply to any data science task, largely applicable to any field in which they find work.
This is a career-focused training program that aims to provide students with practical job skills that can help them find work as Data Scientists. Students will receive detailed instructions on how to utilize Python, the world’s most popular programming language, to collect and analyze large amounts of data. Instruction will cover major Python frameworks such as NumPy and Pandas, and students will learn to use Matplotlib to create vibrant data visualizations. Students will receive instruction in Structured Querying Language (SQL) to build, organize, and query databases. With these databases built and organized, students will then learn how Python can automate significant tasks (such as collecting data from online users to sorting data based on metatags). Finally, students will receive instruction on how Python can be used to write machine learning algorithms capable of interpreting and analyzing data without the need for a human operator. This course aims to provide students with a comprehensive, practical data science education that they can apply to various career paths.
Since this is a career-focused training program, all lessons are designed to serve as practical, hands-on introductions to the programming and data science concepts that students will utilize professionally. Students can attend the program in-person at Noble Desktop’s Manhattan campus, or they can attend classes in remote digital classrooms. Either way, students will receive top-quality data science instruction from Noble’s expert teachers and be able to interact directly with them in real time. Students can get feedback and assistance on difficult lessons, and they can get immediate responses to their questions. In addition to this hands-on instruction, students enrolled in the course will have access to Noble’s career services, including seminars in deploying data science projects so that employers can see your work and one-on-one career mentoring services to help prepare students for the job market. Any student enrolling in this course can retake it for free within one year, giving students extra opportunities to practice their data science skills.
Noble Desktop: Data Analytics Certificate Program
Key Information: This career-focused certificate-granting program offers in-person and online data analytics training to students of all skill levels. Instruction is available full-time (over six weeks) or part-time (over 24 weeks), and live, experienced instructors teach all classes. The course emphasizes professional development skills, and students will receive one-on-one career coaching. Students can retake the course, free of charge, within one year.
Data is only useful to individuals and businesses if they know how to make sense of it, and students looking to learn this skill should consider enrolling in Noble Desktop’s Data Analytics Certificate program. In this course, students will learn how to build databases, organize spreadsheets, query data, and use computer applications to help interpret and visualize that data. This course covers all of the lessons in Noble Desktop’s Data Science Certificate program and complements those skills with training in using Excel, Tableau (an industry-standard data visualization tool) and foundational data analytics principles. By the end of the program, students will be able to apply their knowledge to virtually any data science project they encounter in their professional lives.
The lessons in this class cover theoretical data analysis skills, including statistical analysis, forecasting and the practical business applications of data analytics, and technical computer science training in programming languages like Python and SQL. Students will learn how to use tools like Excel to build databases and how to program applications that automate aspects of the data collection and organization process. This training will give students the tools to draw actionable insights from huge data pools. Students will be trained in using data visualization tools like Tableau to help communicate these findings to invested audiences.
Students can attend this course in-person at Noble’s Manhattan campus or online in a private remote classroom. Either way, students will be taught by Noble’s expert instructors in real-time and they will be able to receive immediate answers to their questions and feedback on their work. Students who enroll in the course online can even give their instructors permission to interact directly with their screen, adding another layer of interactivity to the program. Since this is a career-focused program, all lessons are geared toward giving students the tools they need to find work as Data Analysts. This includes hands-on, practical instruction and professional development programs and workshops such as an industry overview course in which students learn about the practical application of data science and one-on-one career mentoring sessions during which students can receive personalized assistance from data science professionals. Students who enroll in the course can also retake it within one year, giving them even more chances to learn data science skills.
NYC Data Science Academy: Data Science Bootcamp
Key Information: This advanced data science training program is offered in full-time live sessions or full- or part-time distance learning sessions. In-person and online full-time instruction last 12 weeks, and online learning programs provide four to six months’ of content. Regardless of modality, students will participate in career development activities, including one-on-one mentoring sessions. The course does have an entrance exam designed to test students' familiarity with computer programming and statistical analysis.
NYC Data Science Academy is a specialized professional training center that offers a range of certificate-granting programs, including a comprehensive Data Science Bootcamp. In this course, students will learn foundational data science programming skills, including how to write data analytics code in Python and R. The course covers a wide range of data science programming libraries, including NumPy, SciPy, Pandas, scikit-learn, Keras, TensorFlow, and SpaCy, each of which have unique roles to play in complex data analytics projects. Students will learn how machine learning algorithms work, how they can write them in Python, and how businesses and organizations utilize machine learning to improve workflow and efficiency. This course concludes with lessons in advanced data science topics, including concerns about scalability, advanced statistical analysis and techniques, and data visualization skills.
This program is offered in full-time in-person sessions and full-time or part-time online sessions. These programs are taught by live instructors who can assist students in real-time, providing them with feedback and answering their questions. This is a detailed course with content that is informed by current trends and best practices utilized by professional Data Scientists. In addition, students enrolled in this course will receive professional development assistance through NYC Data Science Academy, including one-on-one career mentoring, multiple guided rounds of resume review sessions and access to networking opportunities with alumni, data science professionals, and prospective employers. While there is no formal requirement for enrollment, Data Science Academy recommends students have advanced knowledge of science and mathematics and a basic familiarity with computer programming.
Byte Academy: Data Science Bootcamp
Key Information: This comprehensive data science program offers a hybrid learning model and options for part-time or full-time online training. Students will work with live instructors who can guide them through coding difficulties and they will have substantial free time to watch pre-recorded video lectures and work on coding projects at their own pace. In addition to lessons and career services, like one-on-one mentorship, all students in the course will participate in a four-week data science internship.
Byte Academy offers an industry-recognized Data Science Bootcamp to provide students with a comprehensive education in practical, career-focused data science skills. The program offers full-time live training and part-time hybrid training options for students looking to learn data science online. The course covers foundational data science skills, including advanced Python and SQL programming, statistical analysis and linear mathematics, data visualization and machine learning. This program heavily emphasizes machine learning skills such as how to train neural networks, build effective databases to feed ML algorithms and how to test these algorithms to ensure that their output is effective and actionable. By the end of the course, students will have completed multiple data science projects that they can take onto the job market as examples of their training and proficiency.
This course promises students a personalized education in which class sizes are small enough for instructors to monitor progress and work with students one-on-one. The course aims to provide students with career-focused training in the kinds of data analytics skills they need to find work in the field. The course offers a hybrid instructional model wherein students will work with instructors in small groups at the beginning and end of a class session and be given time to engage with pre-recorded material and assignments at their own pace. This model gives students more flexibility to engage with the material on their own time and in the manner that they find best fits their learning goals. Included in the course is a four-week industry internship that will give students practical, real-world experience working with data analytics professionals on the kinds of projects that companies and organizations regularly undertake. The course does have a proficiency entrance requirement. Students can either enroll in Byte Academy’s Introduction to Python course or complete an exam demonstrating their skills with the language. ByteAcademy also offers a tuition deferral program wherein students won’t have to pay anything until hired as data science professionals.
Certified Analytics Professionals: CAP™ Certification
Key Information: The CAP™ Certification exam is a professional certification test offered by Certified Analytics Professionals, a leading provider of data analytics accreditation. The exam is intended for students with significant, high-level data analytics training and on-the-job experience. CAP™ Certification is expected to require three-to-five years of data science training, though an associate exam is available for students with less experience. This certification lasts three years but can be extended through various programs.
Certified Analytics Professionals is an industry-recognized data analytics certification organization that offers a CAP™ Certification exam for professionals looking for data analytics accreditation. This program allows experienced data science experts to demonstrate their skills in practical and theoretical data science concepts. The exam is balanced between practical data problem-solving skills and demonstrations of technical proficiency in using data science applications and programming languages. The exam questions are built around real-world business data concerns, including model building and deployment, lifecycle management and business intelligence. There is also an Associate CAP™ Certification Exam offered for students with less on-the-job experience.
To sit for the exam, students must meet a minimum requirement set out by Certified Analytics Professionals. This includes an interview with an employer who can speak to an applicant’s soft skills and a minimum amount of professional experience (three years for CAP™ Certification and no minimum for the associate exam). Then, students will have the chance to sit for the exam. After passing the exam, students are awarded a professional certification that lasts for three years, though there are options for alternative methods of re-upping one’s certification. The exam costs approximately 700 dollars, though students can reduce this cost with membership in a few professional data science organizations. No formal training is offered, but signing up for a CAP™ Certification exam does include study guides and preparatory material.
Data Science Council of America: Associate Big Data Engineer Certification Exam
Key Information: Data Science Council of America is an industry-recognized third-party vendor offering varying levels of professional certification in data science and analytics skills. Exams consist of single-answer multiple choice questions covering practical and technical data science knowledge. Each exam lasts 100 minutes, and students who pass the exams will be certified for three years. Exam guidebooks and study materials are included in the cost of the exam.
The Data Science Council of America offers a range of professional certification exams for students and professionals of varying disciplines and skill levels, including their Associate Big Data Engineer Certification (ABDE™). This certification exam tests students' understanding of the hardware, software, and infrastructure involved in data science projects and frameworks. This exam covers topics such as data science foundations, analytics basics (like Python and R), Machine Learning, and data architectures. The exam covers a range of different topics that professional Data Scientists and Engineers regularly utilize, and the program will ask students to demonstrate theoretical understandings of data science skills and the practical application of those skills in real-world contexts. The Data Science Council of America also offers more advanced certification exams for Data Scientists and certification for analysts and project managers.
Each exam lasts roughly 100 minutes and consists of between 70 and 85 multiple-choice questions. All of the exams are available online and provided through a reputable online examination platform. Recommended requirements will vary from exam to exam, though DSCA recommends that most students have two years of on-the-job experience or a bachelor’s degree in a related field before taking an exam. The price of each exam varies depending on the associated level of accreditation, but all of the exams come with significant supplemental training materials and study guides to help students prepare themselves for the exam. Students will need to renew their certification every three years, but alternative paths are available to students who do not wish to retake the exam every few years.
Microsoft Certified: Azure Data Scientist Associate
Key Information: Microsoft offers a wide variety of different certification opportunities for students looking to demonstrate their skills in data science and analytics skills. The Azure Data Scientist Associate Certification emphasizes machine learning programs and their place on the Microsoft Azure platform. Exams take about two hours to complete, and Microsoft offers various free and paid exam prep resources
Another path for students to receive professional certification is through first-party vendors providing certification in the specific data science tools they maintain such as the Microsoft Azure Data Scientist Certification exam. This certification exam emphasizes machine learning modeling and training processes, emphasizing the use of Microsoft’s Azure platform for training a model and preparing it for deployment. The certification also covers practical implementation concerns such as creating suitable working environments for machine learning applications, implementing pipelines and monitoring performance to create scalability solutions. This exam provides users with a badge of completion that they can use to demonstrate their Azure machine-learning skills to potential employers. While the exam primarily focuses on the Azure platform, it is also a good way to demonstrate your understanding of machine learning skills.
These exams last approximately two hours, including traditional exam questions and practical demonstrations of Azure skills. The exams are available online and typically include between 40 and 60 exam questions. Microsoft offers two options for candidates preparing for the exams, self-paced individual lessons that cover exam content and practice exams and paid instructor-guided lessons that walk students through the important concepts covered in the examination. Certifications do expire (the time they last varies depending on the exam level), but Microsoft offers multiple routes for students to keep up-to-date on their certifications.
General Assembly: Data Science Immersive
Key Information: This career-focused certificate granting program provides students with hands-on, practical data science training. General Assembly offers in-person or online training, and the full-time program lasts approximately four months. Students will attend one-on-one career mentorship sessions and have access to expanded networking opportunities.
General Assembly offers a robust, live Data Science Immersive program that provides students with career-focused guidance and an industry-recognized certificate of completion. In this program, students will learn to solve practical data science problems, and be introduced to data science in fields like robotics, finance and public policy. The course covers training in data science fundamentals, including programming with Python, traditional statistical modeling skills and machine learning models. The course aims to provide students with a well-rounded data science education that they can apply to the problems they need to solve regardless of their career path. This is an intermediate course, so students will either need a background in mathematics and computer science or they will need to complete General Assembly’s self-paced preparatory classes to become familiar with the basics of Python.
As a career-focused training program, the lessons that students learn will be geared toward real-world scenarios in which data science plays a major role. In addition to practical lessons applicable in diverse fields, students will complete a capstone project that combines their training in data modeling, wrangling, visualization, and forecasting that they can show to prospective employers. Students will receive one-on-one career mentorship and guidance, including assistance with mock technical interviews, whiteboard challenges, and difficulties in the job search. General Assembly also aims to provide students with networking opportunities with top employers and cohort members.
Google Career Certificates: Google Data Analytics Professional Certificate
Key information: The Google Data Analytics Professional Certificate program is an on-demand data science training program that Google anticipates will take students approximately six months of part-time study to complete. All the work is asynchronous and online, but students who complete the program will have access to Coursera career support services.
Offered through the Coursera online learning platform, the Google Data Analytics Professional Certificate is an on-demand professional development program for students looking to learn data science and analytics skills. Students will learn immersive lessons covering the day-to-day job responsibilities of data analytics and data science professionals, and they will learn how to use programming languages like SQL and R to complete data-related tasks. Students will also learn the basics of data visualization using tools like Tableau and Excel to turn the raw data they collect into understandable graphs and charts. Finally, they will receive hands-on practice and experience analyzing and organizing datasets that mirror the kinds of work they will do in real-world professional contexts.
This course operates on an on-demand model, so students can learn and study at their own pace. The certificate program compiles eight courses, including a capstone case study project and totals approximately 190 hours of course content. When outside work is factored into this, Google anticipates that part-time students who dedicate ten hours per week will complete the program in about six months. Upon completion of the course, students can access Google’s career services programs which include opportunities for students to receive resume reviews, mock interviews, and access to Coursera’s job search guide.
Flatiron School: Data Science Bootcamp
Key Information: This data science bootcamp is offered in-person or online as a full-time training program (lasting 15 weeks) or online as an asynchronous training program (approximately 40 weeks). Students enrolled in either version of the course will receive career mentorship assistance through Flatiron.
Flatiron School offers an in-person and online Data Science Bootcamp with full- and part-time scheduling options. This course aims to provide students with a robust data science education that they can apply to diverse professional contexts. The course introduces students to the data science functionalities of Python and SQL, trains them in using computers to solve complex statistical and mathematical problems and introduces them to the foundational concepts of machine learning. The class concludes with a capstone project that brings together all of the previous lessons and allows students to build a working data science project that they can take onto the job market. By the end of the program, students will be prepared to start a new career in data science or return to their existing career armed with the skills to apply data science fundamentals to their projects.
The course offers two modalities. Students can enroll in a live, online version of the course that runs for fifteen weeks full-time, or they can enroll in an asynchronous online version of the course. The asynchronous version of the course is designed to be completed in approximately forty weeks, depending on student engagement. In either case, students will have the opportunity to work with live instructors during office hours and receive career-focused advice and support, including one-on-one mentorship and extended networking opportunities. Regardless of the modality that students opt for, they will need to complete asynchronous preparatory work to ensure they are familiar with the basics of computer science and programming with languages like Python and SQL.
Frequently Asked Questions
Are Certificates and Certifications Different?
Students looking to become certified data science professionals may be surprised to learn that certificates and certifications are not the same things. They are both methods of demonstrating a student’s proficiency in data science skills, and they are both ways of becoming certified, but they gauge a student’s proficiency in different ways. Certifications are awarded to students who pass skills proficiency exams offered by first- and third-party vendors. These exams tend only to last a few hours, and they test students’ practical and theoretical knowledge of data science concepts. Certifications tend to expire after a fixed period of time, so students will need to take updated versions of the exams, and these certifications rarely come with live skills training.
On the other hand, certificates are more akin to diplomas and are awarded to students who successfully complete industry-recognized training programs. These training programs are meant to help students who don’t have a background in data science learn the skills they need to succeed professionally. Many programs are designed for students with no prior programming experience. Certificate programs tend to be longer and more expensive than certification exams, but they serve different purposes since they aim to teach skills while certification exams aim to test skills.
What Kind of Credentials Should I Pursue?
The question of what kind of credentials you should pursue depends largely on your personal background in data science. Students with college degrees in mathematics or data science or who have significant on-the-job training or experience will probably want to pass a certification exam, since this is the most cost and time-efficient way of demonstrating the skills you already possess. Certification exams tend to provide students with self-paced exam preparation materials so students can brush up on their skills.
Certificate-granting programs are best suited for students who want to work in data science but don’t have a professional background in the field. These courses provide students with a robust education in the important concepts they would be tested on in a certification exam. Some programs do have prerequisites (such as being comfortable with basic Python), but most courses are open to fairly inexperienced students. If you don’t have on-the-job experience or a related degree, enrolling in a certificate-granting program will likely be your best long-term option. Students who complete these programs will likely have the skills they need to pass certification exams to complement their training.
Do I Need to Be Certified in Data Science to Find a Job?
While this will vary from job listing to job listing, as a general rule, data science jobs won’t require applicants to be certified to be hired (though some that deal with specific kinds of sensitive data may require some tangential certification). However, becoming certified is still a good way to signal your skills and proficiencies to employers and set yourself apart from other applicants during the job search process. Passing a certification exam can verify your resume credentials, and completing a certificate-granting course can signal to employers that you have the necessary training to succeed in the position even without a college degree.
What Certificate Program is Right for Me?
Students who opt to complete a certificate-granting program must explore their options for professional training. There are a lot of different certificate-granting training providers out there, and their courses all differ in content and modality. While the ideal course will differ from one student to another, there are enough commonalities among delivery methods that students can generally make an informed decision about what kind of course they want to look for when they start their search. The two major questions are whether you want to learn in-person or remotely and whether you want a live or asynchronous training program.
Which is Better: In-Person or Online?
In recent years, online education has exploded in popularity and has made tremendous strides in the quality of content being delivered. Many training providers now offer in-person and online versions of their courses, and students should seriously consider online learning as a viable and equitable alternative to traditional in-person learning. Each option has advantages and disadvantages, so students should take seriously the question of whether or not online learning is an ideal alternative.
Many students find that they prefer in-person learning since the space of the classroom helps keep them focused and attentive on their materials. Students find it helpful to work in the same space as their instructors since they can ask them questions directly and receive hands-on assistance. Students also find it helpful to work alongside their classmates since it offers additional opportunities for collaboration and networking. The drawback to these courses is that students will be restricted from enrolling in courses offered by nearby training providers, which can greatly limit a student’s options if they don’t live near major cities.
Online courses address this concern by letting students learn from anywhere in the country, provided they have an internet connection. Online classes are taught in a variety of modalities, but students can enroll in live online classes and still have the opportunity to work alongside instructors who can provide them with feedback on their work and assistance on their programming. These courses let students learn from their personal workspaces and give them the flexibility to find the right curriculum. The drawback to these courses is that students need to do more work outside of the classroom to ensure that they succeed, and students will need more self-motivation to complete the course (particularly if there is a lot of asynchronous material or homework involved).
Which is Better: Live Online, On-Demand, or Hybrid?
Students who opt to learn online will then need to decide whether to enroll in a live online course, an on-demand course or a course that includes a hybrid of the two. Live online instruction is just like classroom instruction in that courses meet at regular intervals and are taught in real-time by instructors delivering content in a digital format. On-demand classes are courses that students enroll in and receive pre-recorded course material that they can utilize at their own pace. Hybrid classes include some combination of the two, though most hybrid classes lean more toward self-paced learning options.
On-demand classes tend to be best suited for students with significant scheduling concerns looking for introductory data science lessons. These courses let students learn at their own pace, which can be invaluable for students who don’t have the ability to attend a regularly scheduled course for months on end. It also lets students with the time learn more quickly when their schedules open up. However, since there is no live instruction component to these classes, students may find that they need to be far more self-reliant when it comes to addressing problems and overcoming challenges in their training. There is no one for them to turn to ask questions or to provide feedback on their work. This can make the process even more time-consuming and can cause many students to give up on their training entirely. In addition, since data science technology develops rapidly, even reputable on-demand courses can fall behind trends and contain outdated information. Students who enroll in on-demand courses must ensure that their program has been updated recently.
Live online courses let students work directly with expert instructors who can provide personalized feedback and immediate answers to their questions and concerns. These classes are administered over telecommunications programs, and students can interact directly with their instructors and classmates, mirroring the advantages of an in-person training course. Students will also be confident that the material they receive is up-to-date and accurate. These courses do tend to be more expensive, and they will require students to conform to a schedule (though many providers offer part-time enrollment options), but for anyone looking to change their careers or build a long-term data science skill set, live online classes are preferable to on-demand training.