Explore machine learning and AI applications through Python, predictive modeling, and data-driven projects.
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 told what to do once a training period has been accomplished. It’s used throughout most people’s days without them even knowing. For instance, in just the past few years, society has seen the rise of self-driving cars, practical speech recognition, vastly improved web searching, and a better understanding of the human genome. The results of machine learning can also 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. When computers are able to use past data and the inputs a programmer structures to begin to perform appropriate pre-planned actions on their own, machine learning is the result.
Machine learning falls under the category of artificial intelligence as one of the processes by which a computer or other machine begins to learn how to predict, therefore “think” for itself. It uses two types of techniques: supervised learning, which trains a model on known input and output data to predict future outputs, and unsupervised learning, which finds hidden patterns or intrinsic structures in input data.
The level of complexity involved in machine learning projects depends on the task and the algorithm that is required for it to happen. Regardless of the scope of a task, a machine learning model is a computer looking at data and identifying patterns and then putting those insights to work.
There are advantages that machine learning offers to the workplace. One example is how machine learning handles intelligent, extensive data management. The sheer volume and variety of data that floods companies every minute of the day would be impossible to handle solely by human computation. The way machines can interact with technology to process and draw insights through machine learning makes doing business at an optimal level possible.
Data science is one of the areas most connected with machine learning, although other areas in business now rely on basic machine learning functions. Machine learning in data science fields is an essential part of the foundation for creating meaningful data-backed results. However, it has become increasingly important that those in any data-rich field, including FinTech, computer science, cybersecurity, ecommerce, and similar areas, can wrangle the amount of data that would be overwhelming to humans alone. For those who work in any big-data realm, machine learning is now the cornerstone of what they do.
Orlando has become a major hub for industries that rely heavily on machine learning to enhance operations, improve customer experiences, and develop cutting-edge technologies. One of the most prominent sectors is defense and simulation, where companies like Lockheed Martin Missiles & Fire Control and Siemens Energy use machine learning to optimize system performance, improve predictive maintenance, and support advanced modeling for training and simulation. These firms leverage data-driven algorithms to enhance decision-making and streamline complex engineering processes, making machine learning integral to their innovation pipelines.
The healthcare industry in Orlando also employs machine learning extensively to support patient care and operational efficiency. Large healthcare systems such as AdventHealth and Orlando Health use machine learning models for diagnostic support, patient risk prediction, medical imaging analysis, and workflow optimization. By integrating intelligent algorithms into their electronic health record platforms and care delivery systems, these organizations improve both accuracy and speed in clinical decision-making. Machine learning also enables them to forecast staffing needs, manage hospital resources, and personalize treatment plans.
Orlando’s entertainment, gaming, and tourism sector is another major adopter of machine learning technologies. Companies like EA Tiburon, known for developing the Madden NFL franchise, use machine learning to enhance game physics, player behavior modeling, and quality assurance testing. Major theme park operators, including Walt Disney World Resort and Universal Orlando, apply machine learning to personalize guest experiences, optimize crowd flow, forecast demand, and power intelligent virtual assistants.
Salaries for those in machine learning are substantial. A Machine Learning Engineer in Orlando has an average salary of about $150,000. An Orlando Data Scientist earns approximately $112,000 yearly, and a Data Engineer, $127,000.
An understanding of data science is necessary for a career in machine learning. Noble Desktop offers a Data Science Certificate, which allows students to gain all the knowledge required to enter this lucrative field. In this program, students learn how to analyze tabular data with NumPy and Pandas, create graphs and visualizations with Matplotlib, make predictions using linear regression, and apply machine learning algorithms to datasets. 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.
Noble’s Python for Machine Learning bootcamp expands students’ Python skills to include a comprehensive understanding of machine learning algorithms that independently recognize patterns and make decisions. Students start with linear and logistic regression and then move on to algorithms like k-nearest neighbors, decision trees, and random forests. They also learn important statistical concepts like bias, variance, and overfitting, as well as how to evaluate model accuracy and choose effective features and algorithms.
Another Noble option is the Python Programming Certificate for Data Science and Machine Learning, which teaches essential programming skills to manipulate databases and perform various levels of analysis. Students use NumPy, Pandas, and Matplotlib to analyze data and build predictive models with machine learning libraries like scikit-learn. They also learn how to read and write complex database queries—a vital skill, as a significant portion of a data professional’s time is spent cleaning and preparing data for analysis in Python.
Students can explore more data science, Python, and machine learning through programs at NYIM Training and NYC Career Centers.
High school students can get a head start in machine learning skills by attending NextGen Bootcamp’s Summer Data Science Bootcamp for high school students. This comprehensive program provides real-world skills that students can apply immediately. Mastering these skills early is an invaluable investment in their future.
Machine learning is one of the fastest-growing areas in technology today. It makes sense to enhance your team’s skills through an onsite corporate machine learning training session. Noble Desktop, the creator of this tool, can send an expert instructor to your workplace or arrange a live video session. If it’s more convenient, vouchers can be purchased so employees can join public classes on their own schedule. Bulk voucher purchases come with discounts. Contact Noble Desktop for more information.
A city bursting with innovation and energy, Orlando is becoming one of Florida’s most exciting places to build a career. Long recognized for its world-class tourism and entertainment industries, the city is now gaining a lot of traction in fields related to tech, data, business, and design. Industries like tech, entertainment, healthcare, and aerospace reign supreme, which means there are ample job and professional development opportunities. Start-ups, research institutes, and global corporations alike call Orlando home, creating countless opportunities for professionals eager to expand their skills and make a real impact. Machine learning focuses on building algorithms that can do everything from analyze data and recognize patterns to power automated customer service chatbots and detect fraud. The Orlando professional landscape, consisting of tech, aerospace, healthcare, and entertainment sectors, makes it a perfect place to study machine learning. Through Noble Desktop’s training from experienced instructors, you’ll be able to access the most updated industry-standard information that will help you get right to work in the field. This fast-growing region is worth exploring, and the new skills that you can learn in the region will help you get your foot in the door sooner and are beyond worthwhile.
Dr. Cheryl McCloud brings over 35 years of experience in global supply chain management, with expertise in transportation, inventory systems, trade compliance, and regulatory affairs. She’s earned a Bachelor’s in International Studies from Old Dominion University, along with an MBA in Project Management from DeVry University and a DBA in Global Supply Chain Management from Walden University. Throughout her career, Dr. McCloud has owned a global transportation business, served as a federal government contractor, and provided trade compliance oversight for various shippers. She currently teaches project management courses and, as a licensed U.S. Customs Broker, she also holds certifications in project management and federal maritime law.