When you complete a certificate or certification, you’ll receive specialized training in specific aspects of data science and gain practical experience with important tools, methods, and techniques. Getting a data science certificate shows that you’re dedicated to always learning and that you’re an expert in a rapidly evolving field. Data science can be applied to all kinds of business processes – you can use data to optimize sales funnels or learn which products or promotions customers prefer. Data science can also be applied to the internal operations of a company to enhance its productivity.
NYC is the single largest regional urban economy in the U.S., and is the leading job hub for banking, finance, and communication in the country. NYC is also a major manufacturing center and shipping port and has a thriving technology sector. Data science helps businesses in a wide variety of industries make sense of vast datasets and gain market insights, understand consumer trends, and derive answers to the most pressing problems facing the organizations. Data scientists in NYC earn $80,000 to $201,000 annually. Employment of data scientists is projected to grow 35 percent from 2021 to 2031, much faster than the average for all occupations.
Noble Desktop: Data Science Certificate
Key Information: In the Data Science Certificate at Noble Desktop, you’ll learn the tools to become a Data Scientist with hands-on training and mentoring from industry experts. The course spans four weeks full-time on weekdays, or 20 weeks part-time on evenings or Saturdays. Classes are starting every month, so you can begin whenever you are ready. Tuition for the program is $3,995, which you can pay upfront, in installments, or with 12-month, zero-percent financing. You’ll receive 114 hours of hands-on instruction, plus one-on-one mentoring outside of class, and you can retake your course for free within one year. When you are finished, you’ll receive a verified digital certificate of completion licensed by the NYS Department of Education. Attend this program in-person in NYC or live online via Zoom. You can switch between live and on-line as needed, even after the course has started.
You’ll learn how to manipulate databases and perform data analysis in this beginner-friendly program, and you’ll be ready for entry-level positions in data science or Python engineering. This program will teach you to analyze data with Python, create machine learning models and interactive visualizations, and query databases with SQL. You’ll learn how to read and write complex database queries, prepare and clean data for analysis, and use Python to automate everyday tasks such as aggregating, updating, and formatting data. Then, use your data to build machine learning models and evaluate their performance. Clean and balance your data with Pandas, apply machine learning algorithms with the scikit-learn library to solve real-world problems, and analyze the results to detect areas for improvement.Â
Finally, you’ll learn to build and present dynamic dashboards and other data visualizations. Learn to use Python’s major plotting and dashboard libraries like Matplotlib, Seaborn, Plotly, and Dash Enterprise. Deploy your projects online with GitHub to demonstrate your analytical abilities to employers. At the end of the course, you’ll have real-world projects to add to your portfolio, and you’ll receive assistance with your job search, resume, and portfolio development in one-on-one mentoring sessions with an experienced Data Scientist.
City College of New York: Certificate in Data Science Studies
Key Information: The ten-week Certificate in Data Science Studies from City College of New York provides an introductory-level understanding of data science and how the discipline can solve a variety of challenges in business and beyond. The course uses a hybrid online/offline model with hands-on assignments and activities, and flexibility to complete assignments on your schedule. There are optional weekly group homework sessions and office hours with the instructor, as well as 12 hours of highly-produced video lectures by The Great Courses. There are no prerequisites to enroll and new courses begin about every two weeks, so you can get started whenever you’re ready. The certificate program costs $599.Â
The ability to collect, manage, and analyze data is growing exponentially, and mastering these tools is a sure path to success in your career. Master these new concepts and learn how to put them to work in your business or job with the CCNY Certificate in Data Science Studies. The program introduces you to the key concepts, methods, and accomplishments of this versatile approach to problem-solving.
In this certificate program, you’ll learn about big data and its applications in the world today. The class covers patterns, algorithms, and infographics along with data preparation and political polling. You’ll learn about regression, artificial intelligence, and anomalies. Master overfitting and sentiment and text analysis. Learn to use data compression and recommendation systems, decision trees, and clustering. Finish your program with a study of degrees of separation, social networks, and challenges of privacy. Expert instructors have years of experience in the classroom and real-world experience with data science. CCNY also connects students with internships and helps them make career connections with employers who are actively hiring.
Columbia Video Network: Data Science Certification
Key Information: The online Certificate of Professional Achievement in Data Sciences from Columbia Video Network prepares students to expand their career prospects or change career paths by developing foundational data science skills. Applicants must submit official transcripts, a personal-professional statement, three letters of recommendation, a resume, and a $150 application fee. Prerequisites include a bachelor’s degree, prior quantitative coursework like calculus or linear algebra, prior introductory computer programming coursework, and a minimum undergraduate GPA of 3.0. This certification program requires the completion of four graduate-level classes within two years with a minimum GPA of 3.0. CVN tuition is $2,462 per credit hour, plus a $395 fee per course and a $105 transcript fee. The estimated total cost of the program is $31,229.
You’ll complete four courses to earn the Data Science Certification. Algorithms for Data Science covers methods for organizing data, like hashing, trees, queues, lists, and priority queues. You’ll learn streaming algorithms for computing data statistics and basic graph models and algorithms for searching, shortest paths, and matching. Learn programming methods and large-scale applications that are the foundation for your studies. In Probability and Statistics for Data Science, you’ll learn the fundamentals of probability theory and statistical inference used in data science. Topics included probabilistic models, random variables, use distributions, expectations, law of large numbers, central limit theorem, statistical inference, point and confidence interval estimation, hypothesis tests, and linear regression.
Machine Learning for Data Science offers an introduction to machine learning, with an emphasis on data science. Topics include least squares methods, Gaussian distributions, linear classification, linear regression, maximum likelihood, exponential family distributions, Bayesian networks, Bayesian inference, mixture models, the EM algorithm, graphical models, hidden Markov models, support vector machines, and kernel methods. Part of the course will be focused on methods and problems relevant to big data problems. Exploratory Data Analysis and Visualization requires completion of statistics study with a basic knowledge of R. This course covers visual approaches to exploratory data analysis, with a focus on graphical techniques for finding patterns in high dimensional datasets. You’ll consider data from a variety of fields, which may be continuous, categorical, hierarchical, temporal, and/or spatial in nature. In addition, you’ll cover visual approaches to selecting, interpreting, and evaluating models/algorithms such as linear regression, time series analysis, clustering, and classification.
LaGuardia Community College: Certificate in Data Analytics
Key Information: The Certificate in Data Analytics at LaGuardia Community College provides the skills you need to succeed in the booming information technology and analytics marketplace. The ability to gather, prepare, analyze, and display data is one of the most sought-after skill sets in the information technology marketplace, with demand spanning across sectors that include healthcare, finance, retail, real estate, and even gaming. This program offers beginner, intermediate, and advanced-level data analytics courses, which may be taken individually or as part of a series. Tuition ranges from $490 to $830 per class and partial tuition scholarships are available for eligible students. As a LaGuardia Community College student, you’ll have access to the services offered by the Career & Technical Education Assistance Center.
There are three paths available. Path 1 for beginner students is a Certificate in Data Analytics comprising four courses totaling 168 hours of study, including Data Analytics Foundations; Python for Data Analytics; Data, Databases, and SQL; and Data Visualization with Tableau. Path 2 for beginner students is a Certificate in Advanced Data Analytics comprising three courses totaling 156 hours of study, including Data Analytics Foundations, Python for Data Analytics, and Predictive Analytics: Machine Learning. The third option, Path 1 for students with previous experience with Python, is a Certificate in Advanced Data Analytics consisting of a single 60-hour course, Predictive Analytics: Machine Learning.
In this program, you’ll discover how data is useful and learn all about data, databases, and SQL using PostgreSQL. Explore how to extract data from databases so you can manipulate, transform, visualize, and answer questions. Data visualization involves presenting data in a meaningful and impactful way to tell an easy-to-understand story. Learn to create visualizations and dashboards using Tableau and communicate data analytics findings. You’ll become familiar with Python, SQL, and Tableau, and learn to gather, prepare, analyze, and display data from structured and unstructured sources. Then, build on your knowledge by learning advanced Python and take a deeper dive into machine learning and modeling. You’ll use machine learning to train various types of models to make predictions on large datasets.Â
FAQ for Data Science Certificates
What is the Difference Between a Certificate and a Certification?
Certificate and certification are often used interchangeably, but they have different meanings. A certificate is granted upon completing a course, workshop, or training program, and can be provided by various institutions like schools, online platforms, or training centers. These certificates vary in duration, ranging from a few hours to several weeks or months, catering to individuals at all skill levels. They enhance your expertise in a specific area and enhance your resume.
In contrast, a certification is more demanding and comprehensive. Typically associated with professional fields, it validates that you meet the criteria established by a recognized organization to demonstrate your competence. Certifications validate your proficiency in a particular field and showcase your mastery. They often entail strict prerequisites such as passing an examination, possessing years of experience, fulfilling specific educational requirements, and adhering to professional ethics. Certifications are acknowledged within their industry and elevate both your professional standing and career opportunities.
Should I Pursue a Certificate or a Certification?
Deciding between a certificate and a certification relies on your objectives and desired level of learning. If you seek targeted knowledge or skills, or if you aim to provide proof of your capabilities, a certificate might be the better choice. Certificates typically demand a shorter time commitment than certifications and concentrate on hands-on skills relevant to your role. They promptly bolster your resume and enable you to delve into fresh domains. On the other hand, if your goal is to exhibit substantial proficiency and earn acknowledgment within your industry, a certification could be a more fitting option. It showcases your mastery in your professional domain and opens doors in a competitive employment landscape.
Do I Need to Become Certified to Find a Job?
Determining the necessity of certification for your career path hinges on your specific field and desired role. In sectors such as healthcare, technology, and finance, certification holds significant importance as it aligns with industry benchmarks. Take, for instance, the IEEE Professional Software Developer Certification, which centers around programming expertise. This certification entails the completion of Proficiency Certificates in critical domains like Software Engineering Requirements, Design, Construction, and Testing, culminating in an online examination. Qualifying for this certification typically requires a minimum of two years of college-level education in computer science or a related discipline, in addition to two years of relevant industry experience.
Nevertheless, not all professions mandate certification. Some prioritize your competencies and understanding more than formal qualifications. Acquiring a certificate pertinent to your field can effectively highlight your essential proficiencies and pave the way for new avenues in your career trajectory.
What Certificate Program is Right for Me?
Which is Better: In-Person or Online Classes
When you're deciding between attending classes in-person or online, it's essential to consider your learning preferences, scheduling flexibility, personal preferences, and the subject you're studying. Each learning method has its own advantages and disadvantages that will shape your educational experience.
Opting for in-person classes allows you to directly engage with your instructors and fellow students. This is especially beneficial for subjects that involve hands-on activities, like science experiments, art, or sports. In-person classes enable you to build relationships with peers and teachers, which could lead to future job prospects. Being physically present in the classroom often fosters a sense of responsibility and motivation for completing assignments. However, there are downsides to consider. Attending in-person can be more costly and time-consuming due to commuting, and it might conflict with other commitments. It could also pose challenges for individuals with mobility issues or those residing in remote areas.
On the other hand, online classes offer the flexibility to learn at your own pace and convenience. This is advantageous if you have a busy schedule or work irregular hours. Online learning permits you to study from anywhere with internet access, providing access to courses that might not be locally available. Furthermore, online courses typically come at a more affordable price point than in-person classes. Yet, there are additional factors to take into account. Online classes might have slower response times for inquiries or connecting with peers. You'll need self-discipline and motivation to stay focused and effectively manage your time. If you're not well-versed in technology, navigating online classes could present challenges. Ultimately, the right decision hinges on what aligns best with your needs.
Which is Better: Live Online or Asynchronous Classes?
If you thrive on immediate engagement, group discussions, and teamwork, you might find live online classes to be a good choice. Well-organized classes ensure accountability and receiving real-time feedback aids in effectively grasping new topics. Live sessions often foster a sense of community, providing opportunities for social interaction and networking. However, it's important to be aware of the limitations associated with live online classes. Fixed schedules could pose challenges if you have a busy lifestyle or irregular work hours. Additionally, differing time zones might result in inconvenient class timings.
Conversely, asynchronous classes offer a high level of flexibility. You can learn at your own pace and adjust your studies to fit around your commitments and schedule. The ability to access course materials anytime and anywhere empowers you to have greater control over your learning journey. Asynchronous classes are especially beneficial for individuals with demanding schedules and multiple responsibilities. Nevertheless, it's crucial to balance this convenience with potential drawbacks. Communication might experience delays, making it more difficult to address questions or collaborate promptly with peers. Without a set schedule, maintaining self-motivation and strong time management skills becomes essential to stay on top of your coursework. You might also experience a lack of structure and challenges with procrastination.
The decision between live online and asynchronous classes depends on your specific preferences and circumstances. Take into account your learning style, available time, and the significance of real-time engagement in your educational experience. In certain scenarios, a hybrid approach that combines live classes with asynchronous content can offer a middle ground, providing a balance between structure and flexibility.