Best Data Science Bootcamps Live Online: Compare Remote Programs

Learn More About Live Online Data Science Bootcamps

The data science field sits at the crossroads between math, statistics, and programming. Along with business knowledge of your chosen industry, these disciplines are essential to enter the fields of data science, data analytics, or machine learning (ML). One of the most effective methods to learn the necessary skills is to enroll in a data science bootcamp or certificate program. These intensive courses provide the foundation you need for a data-centered career path.

Since a college or university degree can cost over $100,000 and last four years or longer, data science bootcamps offer a faster, more cost-effective way to enter the workforce with knowledge and practical experience. Bootcamp attendees can complete most programs in three to six months, and their cost typically ranges from $3,000 to $20,000—a fraction of what it costs to earn a formal degree.

Data science bootcamps and certificate programs are applicable to nearly every industry and sector, as the field focuses on helping businesses understand and analyze all kinds of information. In our data-driven society, most companies collect data in one way or another. Data science helps interpret and apply that data to make informed decisions. Read on to learn more about this engaging, high-paying field.

What is Data Science?

What Can You Do with Data Science Training?

What you choose to do with data science training depends on factors like your career goals and existing knowledge base and skill set. Many students new to data science learn a few tools and skills applicable to the discipline, like data visualization with Tableau or Power BI. However, if you plan to start a career as a Data Scientist or Data Analyst, you need to master a range of programming languages, databases, and other relevant skills. Consider the following beginner-level projects you can create:

Build a Detection System — The popular Python programming language is essential for many data science tools, and you can build a detection system using it. For example, a cancer detection system would make an impressive portfolio project for someone who wants to specialize in healthcare. You might use Python libraries like NumPy, Matplotlib, and scikit-learn.
Create a Weather App — You can also use Python to build a weather app. You will need a weather API (application programming interface), an account with an online weather data service like OpenWeather, and an understanding of Python fundamentals.
Build a Prediction Model for Loan Default — Finance professionals with a data analytics background may need to create a prediction model to determine how likely borrowers are to default on loans. This model relies on skills in Python, machine learning algorithms, and logistic regression.

Industries for Data Science Bootcamp Graduates

From multinational corporations to solo entrepreneurs, businesses today must make data-driven decisions. As a result, companies will continue to hire Data Scientists and Analysts to help them make sense of the large amounts of data they collect. However, data science isn’t only for business. Private and public organizations advertise for jobs in nearly every industry, including healthcare, marketing research, government, and more. Besides Data Scientists and Analysts, Data Science professionals also work as Machine Learning Engineers, Data Engineers, and Financial Analysts.

Data science bootcamps and certificate programs prepare students for entry-level data science roles as Junior Data Analysts, Data Scientists, Data Engineers, and other roles. Some data science careers, though, have prerequisites. Because data science requires a strong mathematical understanding of machine learning (ML) and automation, some employers expect Data Scientists to have a degree in computer science or a related field. However, most bootcamps and certificate programs do not require attendees to have a degree. Data science bootcamps are designed for career changers and are an excellent choice for those who already work with data in their current role.

Banking, Financial Services, & Insurance (BFSI)

Banking, financial services, and insurance, a sector abbreviated as BFSI, is one where data science is increasingly essential. Financial services adopted data analytics early, but insurance has also become a primary user. From risk modeling to customer segmentation, consider BFSI an ideal industry for Business Analysts, Data Analysts, Data Scientists, and Financial Analysts.

Cybersecurity

While not everyone associates cybersecurity with data science, one of the key tools in both fields is Python, the world’s most popular programming language. Security Engineers, IT Security Specialists, and Security Analysts are among the many professionals who use this essential programming language. Many Data Scientists also work for cybersecurity firms, creating models using machine learning algorithms.

Life Sciences & Healthcare

The life sciences and healthcare sector is another broad industry encompassing multiple sectors. These include biotechnology, pharmaceuticals, therapeutics, diagnostics, and traditional medicine. It also encompasses research and development (R&D), a vast network of organizations and companies focused on life, from plant and animal to human.

The rise of AI has transformed life sciences and healthcare in ways we still need to absorb. Traditional physicians’ offices may have been slow to adopt digital technology, especially for their large reserves of patient records. Today, however, data science applies to everything from electronic health records to clinical trials, medical imaging studies, and improving the patient care experience. Consider this sector a priority if you want to specialize in scientific or medical data science or analysis.

Retail

Retail is another industry that people should consider when discussing data science. It remains one of the top sectors for data pros, especially Data Scientists and Data Analysts. Retailers can use data science tools for every aspect of in-person and online customer journeys, from initial product awareness on the front-end to optimizing production, improving services, and managing and tracking losses on the back-end.

Retail also includes numerous digital products and services, from smartphones to streaming platforms. Data science, particularly ML algorithms, can track customer engagement and renewals or repurchases, providing recommendations such as Because You Watched on Netflix or Recommended Deals for You on Amazon.

Telecommunications

The telecommunications industry collects and analyzes enormous datasets around the clock. Just as AI is reshaping the data science field, data science has already reshaped the telecom industry. Details like call length, repeated calls, network data, and texting are among the many aspects of telecommunications relevant to Data Scientists and Analysts.

Telecom companies track data usage and identify data from billing systems, routers, cell towers, or other network infrastructure. The complexity of these systems requires skilled, knowledgeable data pros who can sort, manage, and analyze all the data. Data Science professionals use sophisticated ML algorithms to gain insights about customers' previous and likely future behaviors.

While these are all top industries for data science and analysis pros, they are by no means the only ones. Additional industries with an urgent need for data science and analytics pros include agriculture, automotive, digital marketing, and energy.

Data Science Job Titles and Salaries

Data science and analytics roles vary by industry, organization, and even by the specific responsibilities of the position. While the titles listed below are among the most common, consider variants like the following:

AI/ML Engineer
BI Data Visualization - Tableau Developer
Computer Vision and Machine Learning Engineer
DevOps / Machine Learning Ops Engineer
Director, Data Scientist—Fraud Identity Analytics
Employee Benefits Data Analyst
Junior Data Scientist/Engineer
Oracle Data Analyst
Senior Business Data Analyst
Senior Power BI Developer

Consequently, you may need to run multiple searches using varied keywords to find all the relevant data-centered roles in your area.

Business Intelligence (BI) Developer

The Business Intelligence Developer role has become one of the most essential in multiple types of organizations. BI Developers may need to manage data analytics platforms, collaborate with cross-functional teams, and develop reports and visualizations. This role can require diverse skills and tools, from platforms like Zoho Analytics to visualization software like Tableau or Power BI. Salaries for Business Intelligence Developers in the US often exceed six figures, with the average base salary running at around $102,000 annually.

Data Analyst

Data Analysts often progress into Data Scientist roles, though this isn’t always the case. The urgent need for skilled data analytics professionals is particularly acute in the healthcare and financial services industries. Nationwide, a Data Analyst can expect to earn a base salary of around $79,000 annually, not including additional compensation such as bonuses, retirement plans, or profit sharing.

Data Scientist

Data Scientists are among the most respected data professionals, and for good reason. These highly skilled professionals must master a wide array of tools and platforms such as Python programming, machine learning algorithms, SQL, and Jupyter Notebook. Many also have industry-specific knowledge that makes their candidacy attractive to recruiters and hiring managers. Salaries for Data Scientists in the US average around $122,000 annually and are often higher in major metropolitan areas.

Enterprise Architect

Enterprise Architects are somewhat atypical in data science. They typically work on database or network architecture, so they are not the first role to come to mind when most people consider data science positions. However, these highly trained professionals have many skills that overlap with standard data science training. For example, they may specialize in data management, have previous experience as Business Analysts or Financial Analysts, or master risk consulting. Salaries vary depending on the industry, location, and experience, but the average annual base salary for Enterprise Architects in the US is around $147,000.

Machine Learning Engineer

Machine Learning Engineer is one of the highest-paying roles that requires data science training. These skilled professionals learn Python programming, and their expertise with ML algorithms may exceed that of a Data Scientist or Data Analyst. Additional skills include SQL, AWS Services, Spark, and Git/GitHub. The average annual base salary for Machine Learning Engineers in the US is $161,000, though it can be significantly higher in densely populated metro areas where demand is high.

Virtual Data Science Bootcamps & Certificate Programs

Live online data science bootcamps and certificate programs are an excellent alternative to in-person courses, as they offer similar levels of engagement. They are interactive and hands-on, like in-person training, but you can take them from anywhere with a reliable internet connection. In live online bootcamps, students ask questions in real-time, and the instructor can even access their screen and monitor progress or help with any questions, with permission.

Noble Desktop, the creator of this guide, offers several live online options. In their Data Science & AI Certificate program, students learn Python programming fundamentals, how to analyze data, read and write complex queries and use Python to aggregate, update, and format data. Students learn the necessary programming skills to manipulate databases and perform various levels of data analysis. The 114-hour Data Science & AI Certificate prepares students for entry-level data science and Python engineering positions.

The 30-hour Python for Data Science Bootcamp that kicks off the Data Science & AI Certificate is also available as a separate program. It gives students practice with foundational programming concepts like loops, functions, and objects. This hands-on course shows students how to clean and combine data, generating insightful statistics and visualizations. The final sessions focus on using linear regression to extrapolate from data and make predictions. Students can save by taking the Python for Data Science Bootcamp as part of the Data Science & AI or Data Analytics Certificate programs.

Another highly valued Noble Desktop class is their Python for AI: Create AI Apps with Flask & OpenAI. This 30-hour training module covers Flask basics, including how to use it with HTML and CSS and set up the OpenAI application programming interface (API). The course does have a prerequisite. Applicants should have Python knowledge comparable to that gained in Noble's Python for Data Science or Python Programming Bootcamp. You can also save by taking Python for AI as part of the Software Engineering, Python Developer, or Data Science & AI Certificate programs.

Metis, General Assembly, and Flatiron all offer 90-day bootcamps designed to prepare students to begin careers in data science. These courses typically attract participants with a background in math and some familiarity with Python programming. Students learn Python fundamentals and programming tools such as GitHub, programming concepts like NumPy, use Unix commands, use Pandas to clean and extract data, and web scraping tools.

Galvanize also offers a 13-week, immersive data science bootcamp divided into four modules. For a shorter time commitment, Data Science Dojo hosts a hands-on five-day Data Science Bootcamp in which students learn data wrangling, visualization, probability, statistics, machine learning, experimentation design, and data mining.

Virtual Data Science Classes

While some bootcamps require a degree in computer science or a related field that provides a strong mathematical foundation in machine learning and automation, a live online data science class is an excellent choice for those who are interested in data science but are not yet sure how far they want to go with it. Data science classes are a good fit for those who are not quite ready to commit to a full bootcamp but want to start learning about data science.

Noble Desktop offers students numerous choices for classes related to data science. Students can take the hands-on SQL Level 1, an eight-hour beginner-level course that provides foundational skills in Relational Database Management Systems (RDBMSs), SQL code, and Microsoft SQL Server. Once students have mastered the Level 1 course, many will be interested in SQL Level 2, an intermediate-level course focusing on using SQL to analyze data.

Another highly valued Noble Desktop class is their Python for AI: Create AI Apps with Flask & OpenAI. This 30-hour training module covers Flask basics, including using it with HTML and CSS and setting up the OpenAI application programming interface (API). The course does have a prerequisite. Applicants should have Python knowledge equivalent to that gained in Noble’s Python for Data Science or Python Programming Bootcamp. You can also save by taking Python for AI as part of the Software Engineering, Python Developer, or Data Science & AI Certificate programs.

Noble’s Data Analytics Certificate program takes a different approach. This program is available for six weeks full-time or 24 weeks part-time. It includes the Data Science & AI Certificate curriculum plus courses in Data Analytics Foundations, Excel for Data Analytics, and a Tableau Bootcamp. Participants get eight 1-on-1 mentoring sessions and can receive a bonus Python for AI: Create AI Apps with Flask & OpenAI training module at no additional charge.

Students new to data science may choose to start learning through the six-hour Python for Automation course. This class focuses on automating time-consuming tasks using Python, such as automating data collection from the internet. Applicants should have Python knowledge equivalent to that gained in Noble’s Python for Data Science or Python Programming Bootcamp. You can also save by taking Python for Automation as part of the FinTech Bootcamp, Data Analytics Certificate, or Data Science & AI Certificate.

Other training options include the following:

Byte Academy offers a 35-hour Intro to Data Science course delivered over a 4-week period that introduces students to data science basics. It covers Python, object-oriented programming, and data structures.
New Horizons is another course provider offering multiple data science training programs live online. Their Data Wrangling with Python course is a three-day immersive led by a virtual instructor. Topics covered include arrays, dataframes, and web scraping. They also offer multiple SQL-centered classes, including NoSQL and Microsoft Azure SQL.
General Assembly offers introductory data science training, including a two-evening workshop titled Programming with Python Fundamentals. This six-hour course covers Python basics, conditional statements, data dictionaries, and custom functions.
Pragmatic Institute offers a seven-hour Data Science for Business Leaders course. This program is available for corporate teams or as a live online course via teleconferencing. Topics include acquiring and curating data, leveraging data expertise to provide business value, and delivering actionable insights.

Choosing a Data Science Bootcamp

There are several factors to consider when choosing a coding bootcamp. Generally, data science bootcamps offer hands-on learning experiences that help students acquire a solid foundation in a short time. It is important to note, however, that while some data science bootcamps are designed with the beginner in mind, employers often require a degree in computer science or a related field. Data science bootcamps are a great fit for those with a math or technology background and career changers who already work with data in their current job.

Most data science bootcamps teach Python or R, SQL, automation, and basic machine learning. Tuition for data science bootcamps varies, from as low as $7,000 to as high as $20,000 or more, and they last between a few weeks to a few months. Bootcamps with a more in-depth focus on machine learning are often longer in duration. One of the additional advantages of taking a bootcamp is the job support that is often included in the program. Some programs offer job mentoring while others even offer job guarantees. Many bootcamps offer installment plans, monthly payment options, and income share agreements, which allow students to delay payments until they are employed. Students can also look into scholarships and employer reimbursements.

Data Science Corporate Training

If you're planning to instruct or upskill your current staff in data science or analytics, Noble Desktop has multiple corporate and onsite data-centered options, any of which can be tailored to suit your organization. Noble can send expert instructors to your location to take your team’s data skills to the next level. They can also deliver remote classes via teleconferencing.

Would you prefer that your employees have greater flexibility in when and where they complete their data science training? Noble Desktop also offers discounted vouchers for its open-enrollment group classes. Employers receive discounts when purchasing these vouchers in bulk. Featured courses include the Python for Data Science Bootcamp, Data Science & AI Certificate, SQL Server Bootcamp, and Python Machine Learning Bootcamp. Noble can also create a customized training package to meet your team’s specific needs.

If you want to learn about the different data science courses Noble Desktop can provide for your staff, contact a corporate sales specialist for more information or to schedule a free consultation.

Top Certificate Programs

Top Courses

Top Certificate Programs

Top Certificate Programs

Top Courses

Top Certificate Programs

Top Courses

Data Science & AI Certificate Learn The Skills Guarantee™

Key Insights

Learn More About Live Online Data Science Bootcamps

What is Data Science?

What Can You Do with Data Science Training?

Industries for Data Science Bootcamp Graduates

Banking, Financial Services, & Insurance (BFSI)

Cybersecurity

Life Sciences & Healthcare

Retail

Telecommunications

Data Science Job Titles and Salaries

Business Intelligence (BI) Developer

Data Analyst

Data Scientist

Enterprise Architect

Machine Learning Engineer

Virtual Data Science Bootcamps & Certificate Programs

Virtual Data Science Classes

Choosing a Data Science Bootcamp

Data Science Corporate Training

Live Online Data Science Corporate & Onsite Training Noble Desktop

Related Bootcamps

Live Online Data Science
Corporate & Onsite Training