Best Online Masters Programs in Data Science

The data science online masters program offered by Harvard University offers a flexible curriculum with both online and on-campus courses, emphasizing practical skills to tackle real-world data challenges. Core topics include machine learning, data processing, big data systems, and data engineering. Elective courses cover areas like artificial intelligence, wearable devices, data structures, and cloud computing. Students can study part-time, tailor their courses to their schedule and career goals, and engage in collaborative learning through group projects and discussions, culminating in a capstone project.

The benefits of getting an online Data Science master’s degree program are:

• Graduates will have a deep understanding of data science methods and be well-equipped to analyze and manage large datasets.
• The program emphasizes critical thinking, ethical considerations, and effective communication, preparing students to make data-driven decisions and communicate their findings clearly.
• Stackable certificates allow for specialization and career flexibility.
• The team-based capstone project offers practical experience and the opportunity to work on real-world problems.
• Entrepreneurial and research opportunities enhance students' career prospects and contribute to their skill development.
• Membership in the Harvard Alumni Association provides a valuable network for future career opportunities.

This comprehensive online program comprises 11 out of a total of 12 carefully curated courses, each designed to equip students with invaluable knowledge and skills in the dynamic field of data science. This meticulously structured curriculum empowers learners to embark on a transformative educational journey, all while balancing academic excellence with accessibility. One of the remarkable features of this program is its flexibility. With a per-course cost of $3,220, it provides students with an affordable and manageable way to pursue their data science aspirations.

The capstone project, the culmination of the program, allows students to apply their acquired knowledge and skills to real-world challenges. It is a testament to their growth and development throughout the program and a reflection of their ability to tackle complex data-rich problems. With the support of their dedicated team, students kickstart their capstone project with the confidence and expertise gained through their educational journey.

The University of Chicago's Master's in Applied Data Science program offers both in-person and online options to accommodate diverse student needs. The in-person program, eligible for OPT STEM, is ideal for early career professionals and can be completed full-time in 12-18 months, with part-time options available. The online program provides flexibility with in-person Immersion Weekends twice a year, fostering networking opportunities. The curriculum consists of 12 courses, including core, elective, and Capstone Project courses, ensuring relevance in the dynamic data science field. Students can choose part- or full-time study schedules to fit their lifestyles and career goals. The program emphasizes interactive learning through synchronous online classes and leverages advanced technology for collaboration.

The benefits of this online Data Science program are:

• Combines online study with in-person immersion weekends
• Weekly synchronous classes for live interaction
• Comprehensive curriculum includes core, elective, and Capstone Project courses
• Curriculum reviewed annually to stay current in data science
• Part-time and full-time study options available
• The in-person program is OPT STEM-eligible

At University of Pennsylvania, you can take your career in data science and engineering to greater heights with their Master of Science in Engineering in Data Science (MSE-DS) Online degree. Not only will you learn from prestigious Ivy League faculty who are renowned researchers as well as educators, students will have access to collaborative opportunities like real time interaction with professors and group projects with classmates from around world. UPenn provides an environment perfect for connecting various industries and diverse perspectives that are evolving data science.

You have the flexibility to commence this program either in the fall or spring, and you can choose between full-time or part-time attendance. Lectures are pre-recorded, eliminating the need for mandatory synchronous sessions. Additionally, you have the option to extend your studies into the summer or take a break during that period. The completion timeline is also adaptable: you can achieve graduation in as little as 16 months or extend your program up to five years. Typically, most working students complete their coursework within 20 to 30 months. To earn your MSE-DS Online degree, you will successfully complete ten (10) course units, comprising four core course units, four technical elective units, and two open elective units. All courses are offered entirely online, and there are no obligatory real-time sessions.

Some of the benefits of this program are:

• Taught by Ivy League faculty renowned in research and education.
• Access to real-time interaction with professors and global group projects.
• Program intake in fall or spring, with options for full-time or part-time study.
• Lectures are prerecorded, and no mandatory synchronous sessions.
• Flexible completion time, ranging from 16 months to five years.
• Typical completion for working students is 20-30 months.
• All courses are fully online, and there are no required real-time sessions.

A master's in data science through the online program at Johns Hopkins Engineering for Professionals can help you become a leader in today's digital world. Gain the skills needed to qualify as an expert data scientist; courses focus on computer science, applied mathematics, and more. After completing your studies, you'll be able to launch yourself into a variety of specialized roles that leverage data pipeline and storage plus statistical analysis. The demand for these types of skilled professionals is ever-growing - make sure you have the credentials to join their ranks.

Gaining an online master's degree in data science is a great way to be prepared for specialized roles across many disciplines such as data pipeline, storage and statistical analysis. With busy professionals in mind, this course provides an array of modern online classes that will help extend your knowledge and pave way for new career paths in areas like Machine Learning, Data Visualization, Game Theory, and Large-Scale Data Systems. Led by experienced engineers and data scientists, you'll be trained through scenarios that reflect real-world situations you may already face or come across as part of your job.

The benefits of this online masters in Data Science from JHU are:

• Students gain practical skills for a career in data science.
• Students can balance theory and practice in applied mathematics and computer science.
• Students will able to analyze and manage large-scale data sets.
• Discover insights in complex data through information manipulation.
• Create automated models to solve real-world problems.
• Customize your degree with courses of interest.
• Develop confidence as a data scientist and leader.
• Explore various data science degree options.

Northwestern's online Master of Science in Data Science (MSDS) program helps to equip its participants with analysis and leadership skills essential for success in the data-driven world. MSDS pupils gain valuable knowledge on how to make use of relational, document, and graph database systems along with open-source analytics software such as R, Python, Go, TensorFlow and Keras. With traditional statistics and machine learning methods being taught too, participants feel empowered knowing they can generate accurate predictions with confidence.

The MSDS program at University offers five unique specializations for those seeking to pursue a master's degree: Analytics and Modeling, Analytics Management, Artificial Intelligence, Data Engineering, or Technology Entrepreneurship. Within each specialization, learners can customize their studies with electives such as financial machine learning, analytics systems engineering, deep learning and business process analytics. As part of the curriculum, three languages are taught: Python, R and Go - so that graduates of the program could opt to specialize in one language or have an understanding across all three.

Students may pursue a data science master's degree through either part-time, nonresidential study or an accelerated full-time program. With various specializations available, you can customize your curriculum to meet your ambitions. Renowned faculty are at hand to provide instruction and mentorship throughout each course of study. Depending on your preference, you can opt for 100% online classes in a part-time program or take advantage of an accelerated option that fuses online and on-campus sessions over one year.

For those aspiring for a career in data science, the Master of Science in Data Science degree provides the essential skills needed after completing 12 courses. This includes notably core classes, specialized training, a leadership or project management course, and also culminating with a capstone project or thesis. Students can pick between the part-time and accelerated options as their curriculum may differ marginally from one another.

Use our comparison chart to learn the benefits each program has to offer.

Health Data Science is a crucial, rapidly growing field, blending biostatistics, programming, and advanced computational and classification algorithms like machine learning to address complex challenges within the biomedical, biobehavioral, public health, and clinical care sectors.

The program offers a robust, interdisciplinary education focused on theory and application, preparing students for both academia and the private sector.

Compare the Education Experience Between Our On-Campus Online MS program.

Students will complete a 10-week capstone course to work on a real-world health data science challenge.

Brown University Online Certification Training Course Provider.

Explore the frontiers of Data Science, AI Gen AI.

Enhance your Data Science and AI career with our immersive program. Learn top skills and tools via expert instruction and practical learning. Dive into a cutting-edge curriculum with a focus on Generative AI.

Master the future of technology with Brown University Applied AI Data Science Program. Experience a rich blend of AI tools, practical projects, and expert insights in this transformative program.

Certificate of completion from the School of Professional Studies at Brown University.

Progressive curriculum including AI framework, data science tools, and Generative AI.

Data scientists turn raw data into compelling stories that drive strategy and innovation. They employ statistical knowledge and an understanding of machine learning to decipher complex datasets. They enable companies to navigate the market and customer behaviour for smarter business decisions.

Earn School of Professional Studies at Brown University Certificate.

Induction for Brown Applied AI and Data Science program.

Get started with the AI Data Science program, exploring all of the content. Kick-start your journey with this induction session and get to know what this carefully curated program offers.

Get started with the Applied AI Data Science program and extensively explore essential AI data science concepts. This introductory course will provide an of the program structure, curriculum, learning outcomes, and other important details.

Continue your learning journey by exploring the fundamentals of statistics and Python, which will lay a strong foundation for your data science knowledge.

Model preparation involves the crucial steps and techniques required to prepare the data for model training and evaluation. Dive deep into various supervised learning techniques, including but not limited to linear and logistic regression, decision trees, and random forests.

Model training plays a vital role in the data science workflow as it enables the creation of predictive or descriptive models that can provide accurate predictions and valuable insights. Gain proficiency in assessing the performance of models by utilizing established evaluation measures and matrices commonly employed in the industry.

This branch of artificial intelligence focuses on creating models capable of generating new and original data samples. Discover the concepts of variational autoencoders, generative adversarial networks (GANs), diffusion models, and transformers.

This module covers topics that will help prepare you for what lies ahead. By completing this module, you will acquire valuable insights and knowledge that will equip you to thrive in the rapidly evolving field of data science.

The capstone project will allow you to implement the skills you will learn throughout this program. You will solve industry-specific challenges by leveraging various AI and Data Science techniques learned across various modules in the program. This project will help you showcase your expertise to potential employers.

Tell us a bit yourself and why you want to do this program.

Selected candidates can begin the program within 1-2 weeks.

Demand for Applied AI Data Science Course in 2024.

The demand for professionals skilled in AI and data science is surging as businesses increasingly rely on sophisticated algorithms and data analysis to drive decision-making. The rapidly growing AI market, poised to expand to over half a trillion dollars by 2024, signifies a paradigm shift toward data-centric business models. This growth is creating a vast gap between the and demand for experts trained in AI and data science, indicating the need for robust educational programs.

Brown University Applied AI Data Science online course is an excellent resource for aspiring professionals. It merges rigorous academic theory with practical skills in applied machine learning, preparing students for a dynamic workforce. Graduates emerge with a prestigious certificate from the School of Professional Studies at Brown University, enhancing their employability in a market hungry for trained AI and data science experts.

At a high level, this Applied AI and Data Science course provides learners with the theoretical and practical training required to master working with top AI frameworks, data science tools, and generative AI. Learners will gain job-ready skills to apply artificial intelligence in real-world situations in this comprehensive online applied AI data science course.

The applied AI data science course fee is $2,499.

Practical experience working with top AI and data science tools through real-world, industry-specific projects in integrated labs.

A certificate of completion from the School of Professional Studies at Brown University.

This applied AI data science course stands out because of its immersive, blended learning format and comprehensive curriculum. Through theoretical learning and practical training, you will gain job-ready skills to apply AI in real-world situations. You also get into the weeds with some of the top AI and data science tools and frameworks, including, but not limited to, Python, pandas, NumPy, SciPy, and ChatGPT. On top of that, you will have access to insights from some of the top minds in the field from the School of Professional Studies at Brown University through live masterclasses.

The prerequisites for admission to this applied AI and data science course include:.

To ensure money is not a limiting factor in learning, we offer financing options to help make this Applied AI and Data Science Program financially manageable. You can pay in 12 monthly installments using Affirm, Splitit, Klarna, or Climb.

Real-world projects included in this applied artificial intelligence course are industry-specific use cases. These include retail sales analysis, employee turnover analysis for HR, loan repayment prediction, and credit card fraud identification for the financial services industry.

Gaining a certificate from the School of Professional Studies at Brown University, will earn you recognition globally.

AI and data science will be helpful, if not required, in many future careers. Today, job roles you can pursue with the skills you learn in this applied AI data science program include Data Scientist, Machine Learning Engineer, AI Engineer, and .

You can study at your own pace according to your schedule, meaning you can complete this program without quitting your job.

No,there are no scholarships for the Applied AI and Data Science course.

No, one can not transfer credits from other programs into this one.

The comprehensive curriculum in this applied AI data science program starts with fundamental concepts and moves on to advanced ones, Topics covered include the fundamentals of statistics, Python programming fundamentals, data science and artificial intelligence, machine learning fundamentals, algorithms, and models, deep learning, supervised and unsupervised learning, neural networking, generative AI, and .

A portfolio of degree, certificate, and executive programs span across disciplines and formats, offering an array of educational opportunities for learners at all career stages.

The School of Professional Studies at Brown University is collaborating with Simplilearn to deliver select online programs.

Rice University offers a non-thesis MDS degree that requires students to commit to 31-35 credit hours of coursework. Those studying for this master's degree must fulfill certain obligations, including:

• Depending on the course choices, the degree requirements must be satisfied with a minimum of 10–13 courses (31–35 credits).
• A minimum of 31 graduate semester credits, or coursework with a 500 level or higher, are required for graduation. 
• The student must enroll in a minimum of 24 graduate semester credits at Rice University.
• Standard or traditional courses must be taken for a minimum of 24 graduate semester credits.
• A minimum of one semester of part-time graduate coursework at Rice University either the autumn or spring semesters.
• A maximum of two courses with transfer credit, totaling six graduate semester credits.
• A cumulative GPA of 2.67 or higher across the board for all Rice coursework.
• A minimum program GPA of 2.67 or higher in all Rice coursework that satisfies requirements for the non-thesis master’s degree.
• All Rice courses must have a minimum program GPA of 2.67 or higher in order to satisfy the requirements for the non-thesis master's degree.

Having completed the MDS program, graduates will be equipped with the knowledge and skills to:

• As a graduate student, gain an advanced comprehension of the numerical and statistical principles of Data Science.
• Study in detail to achieve expertise in either one of the principal methods or one application aspect of Data Science.
• Start by applying Data Science techniques to complex, real-world issues with raw and unclean data and finish by providing comprehensible information to non-experts which can be used for actionable purposes.

The online Master of Data Science program is tailored for non-traditional graduate students seeking a balance between their educational pursuits and the demands of work and family responsibilities. In this program, you'll have the flexibility to uphold your work-life commitments while pursuing your degree part-time in an exceptional, adaptable, and engaging learning environment. Part-time students typically complete the flexible online Master of Data Science program in a span of 2 to 3.5 years. Alternatively, for full-time students with strong prerequisites, the program can be completed in a more accelerated timeframe of 18 to 24 months.

Data Science Boot Camp with Washington University in St. Louis.

Learn the Data Science Method, choose from one of three specializations and build a portfolio-worthy capstone project.

Our world is overrun with data. Businesses are inundated with overwhelming amounts of data that need sorting from online payment portals to social media platforms. Data scientists are the ones hired to fix this problem. They sort and analyze data so companies can make informed business decisions, whether resource management or marketing strategies. The field of data science is relatively new, yet job opportunities continue to blossom. The U.S. Bureau of Labor Statistics estimates a 36% increase in data scientist jobs by 2031, amounting to 40,500 new openings. A career in data sciences will provide ample job security while promising intriguing, mentally stimulating work.

Foundations will cover the basic data science concepts, such as the most applicable programming languages (including Python). This solid foundation will lay the groundwork for your success throughout the program.

The Core material units include fundamental data science concepts and will teach you the skills needed for each. The individual units are built out with lectures, theory, hands-on projects, coding exercises, real-world concepts in the field and reading exercises.

The units center around the Data Science Method. This method involves six steps:.

Python has become the lingua franca of data science. In this section of the course, you'll learn program in Python, follow best coding practices and start using an ecosystem of useful and powerful Python-based tools.

In other words, you'll use queries to understand the data contained in databases.

A data story is a powerful way to present insights to your clients, combining visualizations and text into a narrative. Storytelling is an art and needs creativity. This section will try to get your creative juices flowing by suggesting some interesting questions you can ask of your dataset. It will also cover a few plotting techniques you can use to reveal insights.

Statistics is the mathematical foundation of data science. Inferential statistics are techniques that help us identify significant trends and characteristics of a dataset.

Machine learning combines both computer science and statistics to extract useful insights and predictions from data. Machine learning lets us make valuable predictions and recommendations and automatically finds groups and categories in complex datasets.

This track will prepare you to take on versatile data science roles across a wide variety of business domains and geographical locations.

This track aims to teach you advanced data visualization and business analytics skills to extract actionable business insights. While you will have the ability to build predictive machine learning models, you'll primarily focus on learning identify insights and effectively communicate recommendations.

This track aims to teach you advanced machine learning skills and concepts, including deep learning and the deployment of machine learning models on standard industry platforms. If you want to broaden your machine learning skills, this track may be the right one for you.

Your first capstone project comes up fairly early in the course. This first capstone builds your foundational understanding of each of these critical steps while also allowing you to practice each step before applying your knowledge to your second capstone.

Use exploratory data analysis techniques to understand that data.

Accountability: Our mentors hold you accountable for sticking to your career and program goals.

Students with no coding experience, but who are skilled in math and statistics, will be given units that cover the core data science concepts, like Python, which is necessary for doing well in the program.

Data science boot camps are worth it if you are looking to switch careers or learn new programming languages and tools. The fast-paced environment of a boot camp can be beneficial if you have the motivation to learn and apply yourself.

The Washington University Data Science Boot Camp provides access to a 1-on-1 industry mentor, optional career curriculum and a career coach to help prepare you for the next step in your career.

Data science is the process of extracting knowledge from structured and unstructured data. It involves using mathematical, statistical and computer science techniques to analyze data, identify patterns and relationships and propose insights that can help organizations make better decisions.

Data science is used in a wide range of industries, including finance, healthcare, manufacturing, marketing and retail. It an important tool for making informed decisions everything from product pricing to inventory management to customer segmentation.

A data scientist uses their knowledge of statistics and computer programming to clean data, create algorithms and models and analyze large data sets, looking for patterns and correlations that can help them understand what happening within the business.

Once they have identified any trends, a data scientist will then create reports and presentations that explain their findings in a way that is easy for non-technical people to understand. This allows business decision makers to make informed choices improve their business based on the data that has been collected.

How long it takes to become a data scientist depends on your background and prior experience. A data scientist typically has a mathematics, statistics, computer science, or engineering degree. However, there are many self-taught data scientists who have no formal education in these areas.

A data scientist can get up to speed fairly quickly if they are familiar with Python and have some basic knowledge of machine learning algorithms.

Our boot camp can help you prepare to become a data scientist in less than nine months.

The salary range for a data scientist can vary based on experience, location and company. According to Lightcast, the annual median advertised salary for data scientists in the US is $118, 967.

Data scientists are in high demand. The U.S. Bureau of Labor and Statistics (BLS) reports an expected change in employment of 22% between 2020 and 2030, which significantly outpaces the average of all occupations: 8%.

Data science boot camp costs vary, but can be anywhere between $10,000 and $20,000. The Washington University Data Science Boot Camp is $9,900 when paid upfront.

From UC Berkeley's School of Information (I School) comes a highly innovative Master of Information and Data Science program - delivered 100% online. This WASC-accredited course provides students with an unrivaled level of flexibility, offering them a multidisciplinary curriculum that encompasses computer science, social sciences, statistics, management, and law. In just 12 months you can complete this 27-unit program with experienced faculty from leading data-driven companies guiding your journey as you work with real-world data to solve complex problems and gain valuable insights.

The program is offered in 3 paths: accelerated, standard, or decelerated.

• The accelerated path gives students the opportunity to take three courses per semester to complete the program in as few as 12 months.
• The standard path is designed for working professionals and can be completed in 20 months, with two courses per semester.
• The decelerated path allows students to drop down to one course per semester after the first term and complete the program in no more than 32 months.

A wide range of courses in the MIDS program gives students a thorough grasp of how data science may be utilized to support decision-making in their businesses. Students will finish programming-focused courses, such as the ones shown below, along with other courses that emphasize the ethical implications of data science and the best ways to present findings.