Study machine learning through data-driven courses that introduce AI principles and applications. You’ll explore algorithms that power predictive and analytical models.
Master Python for data analysis, machine learning, and automation. Build predictive models, create dynamic dashboards, and unleash the power of data visualization. Launch your career in data science and Python engineering, equipped with Python, NumPy, Pandas, and Matplotlib.
Learn Python, SQL, automation, and machine learning to become a Data Scientist. Gain Python programming, data analysis, SQL querying, and predictive modeling skills. Perfect for beginners, this program prepares you for entry-level data science and Python engineering roles. Unlock high-paying job opportunities in the field of data science.
Learn the fundamentals of machine learning, including regression analysis and classification algorithms, in this practical, hands-on course. Gain the skills needed to solve real-world problems using machine learning, with a focus on Python programming and data science libraries.
Machine learning is the science of getting computers to act without being explicitly programmed once initiated. Machine learning is so pervasive that it’s probably used throughout most people’s days without them even realizing it. In just the past few years, our society has seen the rise of self-driving cars, practical speech recognition, vastly improved web searching, and a better understanding of the human genome. When computers can use past data and inputs from programmers to begin to perform appropriate pre-planned actions on their own, then machine learning has succeeded.
Machine learning is a subset of artificial intelligence, with computers taking the directions they’ve previously been given once and combining them with data analysis to predict what should be done next. The result can be seen in everyday applications such as movies, music, and products that are recommended to individuals based on what they’ve liked or used before.
The level of complexity involved in machine learning projects depends on the task and the algorithm needed to accomplish it. Regardless of the scope of a task, a machine learning model is a computer looking at data and identifying patterns, then putting those insights to work to better complete the goal.
There are advantages to the advancements machine learning offers to the workplace. One example is how machine learning handles intelligent big data management. The sheer volume and variety of data that floods companies every minute of the day would be impossible to now be handled solely by human computations. The way machines can interact with technology to process and draw insights through machine learning makes doing business at an optimal level possible.
Above all, data science is one of the most connected areas with machine learning. It is imperative that those in data-rich fields, including FinTech, computer science, cybersecurity, e-commerce, and similar areas, can wrangle the amount of data that would be overwhelming to humans alone. Machine learning in data science fields is an essential part of the foundation for creating meaningful data-backed results. For those who work in any big-data realm, machine learning is now the cornerstone of what they do.
Machine learning is used extensively in the finance industry, which is incredibly strong in Virginia. It’s important for credit-risk modeling and customer behavior predictions. It’s also important for algorithmic decision-making and fraud detection. At companies like Capital One and Freddie Mac in McLean, these roles are highly sought-after.
It’s no secret that the government industry reigns supreme in Virginia, especially in the northern part of the state that’s much closer to Washington, D.C. Machine learning professionals work in government to predict outcomes for policies, detect anomalies in security systems, and handle large and complex data sets with ease. Government contractors like Booz Allen Hamilton in Reston will hire Machine Learning Engineers to support their government programs.
Virginia is home to start-ups and major companies alike, such as Leidos Inc. in Reston. These professionals work with data engineering and model deployment, which is essential for client-based solutions.
For those with careers in machine learning, moving a tech-obsessed society in the right direction is a responsibility they relish as it evolves and presents new challenges regularly. Here are a few careers that Virginia-based machine learning experts may want to explore.
The average base salary for a Virginia Machine Learning Engineer is $146,000. This is an incredibly high salary, but still well below the national average. However, most places in Virginia have a lower cost of living compared to other states. Even so, those living in places like Arlington and McLean report salaries closer to $165,000 to $169,000, so it does depend on where you’re living.
Virginia-based Software Engineers earn an average of $123,000 each year, which is similar to the national average. It all depends on location, though -- in Fairfax, this number is closer to $117,000, whereas in Herndon, you could expect salaries closer to $141,000.
The average salary for a Data Scientist in Virginia is seven percent higher than the national average, resting at around $138,000. However, among 176 salaries reported in McLean, the average is closer to $153,000.
Machine learning expertise raises a tech professional’s career to amazing heights. Having the ability to learn machine learning through live, online classes offers direct machine learning knowledge for data science, finance, cybersecurity, and other data-related careers. Live virtual courses allow students to have the freedom of choosing where they’d like to take their courses, perhaps at home or the office. Having a space that is distraction-free when taking immersive Python bootcamps is an ideal option. Students even have the option to share their computer screen with the instructor for additional assistance.
Noble Desktop’s Python for Machine Learning Bootcamp expands students’ skills in Python to encompass a comprehensive understanding of machine learning and algorithms that can independently learn patterns and make decisions. Students start by learning linear and logistic regressions and move forward with algorithms with different theoretical bases, such as k-nearest neighbors, decision trees, and random forests. Additionally, students gain abilities in statistical concepts such as bias, variance, and overfitting, as well as how to measure the accuracy of models and tips for choosing effective features and algorithms.
Noble Desktop also offers an intensive program called the Python for Data Science Bootcamp. This bootcamp takes students from the basics of Python to advanced topics and applications to be able to create data visualizations and use statistics to create machine learning models. Students begin by learning Python to write basic statements and expressions, create variables, understand different data types, and work with lists.
Understanding data science is necessary for a career in machine learning, so you may want to explore beyond a bootcamp. Earning a certificate from Noble Desktop’s Data Science Certificate provides students with the opportunity to gain all the information they need to move into this lucrative career. In this program, students discover how to analyze tabular data with NumPy and Pandas, create graphs and visualizations with Matplotlib, make predictions with linear regression, and apply machine learning algorithms to data. Additionally, students will learn how to clean and balance data in Pandas, evaluate the performance of machine learning models, combine information across tables with join statements, and explore advanced techniques such as subqueries and stored procedures.
Artificial intelligence is one of the fastest-developing areas in technology today. It makes sense to boost your team members’ abilities in the field by providing a focused look at machine learning by investing in an onsite corporate machine learning training session. Noble Desktop will send an expert instructor to the workplace to provide training or arrange a live video conferencing session. If it is more convenient to allow employees to attend sessions on their own schedules, vouchers can be purchased for them to enroll in a public open enrollment session. There are discounts on the purchase of multiple vouchers. Contact Noble Desktop for more information.
Virginia’s professional community is, without a doubt, an impressive one. The state is home to some of the largest companies in the world, and with its proximity to the nation’s capital, its connections to the government and public service sectors are undeniable. Needless to say, those looking to gain new skills in tech, data, business, or design are well-positioned to do so.
Virginia students can take classes at the modern facilities located at 600 Maryland Avenue SW, Washington, D.C., 20024. This is right off L’Enfant Plaza. It’s a professional yet welcoming environment that allows students to jump right into their studies. If you’re coming from Virginia, you’ll have no trouble getting here. While the trip will depend on where you’re coming from within the state, those in the Northern Virginia (NOVA) region can hop on the Virginia Railway Express to Union Station and take the Metro for a short ride to L’Enfant Plaza. Driving is still an option, with various parking garages available to make the trip easier. Otherwise, there are bus routes connecting from NOVA to D.C. With so many options, attending classes and workshops in D.C. is convenient and simple.
Machine learning helps Virginia’s organizations identify patterns, automate processes, and improve analytics. With this, students at Noble Desktop have an opportunity to learn foundational modeling and evaluation techniques from instructors who make advanced topics approachable. The school's instructors offer decades of experience and insight into the field that enables you to make a real difference in the Old Dominion.
A seasoned educator and training leader, Brian brings ample experience to the classroom, particularly in designing and delivering learning programs in project management and emerging technologies, like AI. He has created adaptive learning models that blend instructor-led lessons, live experiences, and self-paced study, making professional development flexible and accessible to everyone. Brian has also focused heavily on integrating AI into training, which helps organizations and professionals by applying AI to real-world situations that can fix challenges, assist leadership, execute projects seamlessly, and make more informed decisions. Beyond teaching, he has led curriculum development, managed large-scale training initiatives, and implemented collaboration tools that have led to higher retention rates and increased engagement from students.
Clarissa has over 25 years of experience as a corporate trainer, Project Manager, and Business Consultant. She has designed and delivered highly effective training sessions for federal agencies, private corporations, and international organizations, making her a well-versed and experienced trainer and educator. She is currently the President and CEO of Projections Training Solutions, which has trained over 10,000 professionals worldwide, including clients like the Department of Defense, NASA, Microsoft, and FEMA. Not to mention, her work has taken her to places like China, Japan, South Korea, Africa, Singapore, and the Caribbean. Her programs span subjects like leadership, project management, business analysis, and emerging technologies. At Graduate School USA, Clarissa is a trusted and well-respected instructor who teaches and helps develop several programs.
As a retired combat veteran who served as both an Air Force enlisted member and a Navy officer, Alan brings more than 30 years of experience across federal and commercial sectors. His background consists of work in budgeting, auditing, programming, operations, global logistics, supply chain management, and IT acquisitions. He has worked extensively with federal, state, and local governments, such as the Executive Office of the President and various departments (such as the State, Defense, Health and Human Services, and Education Departments, to name a few). Alan’s consulting work includes strategic planning and business development with the D.C. government, federal agencies, Lockheed Martin, and more. Overall, he’s a well-equipped educator due to his experience and expertise, but he also holds a teaching certification from Harvard’s Bok Center for Teaching and Learning. His expansive background makes him a perfect fit to teach subjects like finance, accounting, and project management.
With more than fifty-five years of experience in federal and non-profit financial management, Johnny is a retired senior Federal Manager and Vietnam combat veteran. His degrees are from Herbert H. Lehman College and St. John's University. He has been working as an adjunct faculty member at the Graduate School USA since 2011, teaching Appropriations Law, as well as a range of federal budget-related courses, including finance and accounting. His career also includes leadership roles, such as the Chief of Budget Execution for the IRS Office of Chief Counsel and the Budget Officer for the Small Business Administration’s Office of Inspector General. His impressive career experience and education allow him to share his wisdom with others, fostering a supportive and structured learning experience.
Charles Byrd is an experienced Employee and Labor Relations Consultant with a strong background in federal human resources management and legal counseling. He obtained his B.A. in Business Administration and Political Science from Loyola University and received his Juris Doctorate from the University of Baltimore School of Law before diving further into his career. Over the years, he has advised agencies on complex HR and labor matters, managed HR programs, and represented organizations in legal proceedings. In addition to this, Charles has developed and delivered specialized training in subjects like project management and human resources. He has been recognized for his professional excellence as well as his teaching abilities and leadership skills, acquiring awards and accolades throughout his decades-long career.
Natalya has been a part-time instructor at Graduate School USA for over 15 years, where she teaches project management, leadership, and human resources courses. She has developed original curricula, including Change Management Workshops and specialized project management programs. In addition, Natalya has served as an action learning coach and facilitator in government leadership initiatives. She runs her own consulting business, offering coaching and training for public and private entities. Moreover, she created the Define and Achieve Your Goals Process and is a certified Birkman Method Consultant. Her M.S. degree in Project Management from George Washington University’s School of Business provides her with the credibility and skills that have allowed her to excel in this field for so long. Between her experience and knowledge in the field, she’s well-equipped to provide insight into the project management field.