Experiment with machine learning through beginner and advanced bootcamps. You’ll discover how algorithms and data create intelligent automation.
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 a subset of artificial intelligence, with computers taking the directions they’ve been given, combining them with data analysis to predict what should be done next. 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 been successful. The result can be seen online every day as movies, music, and products 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. Any task that relies upon a set of data points or rules can be automated using machine learning, even things such as responding to customer service calls and reviewing resumes.
There are extraordinary 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 for a human to handle alone. The way machines can interact with technology to process and draw insights through machine learning makes doing business at an optimal level possible. Smart devices are the most familiar form of machine learning people come across daily. Machine learning drives everything from wearable devices that track fitness to self-driving cars and smart cities with infrastructure to reduce energy waste. The Internet of Things (IoT) continues to add more need for machine learning processes. Finally, one of the biggest reasons that machine learning helps progress is how rich it can make consumer experiences. Machine learning enables search engines, web apps, and other technology to customize results and make recommendations to match user preferences, creating streamlined and satisfying personalized experiences for consumers.
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 the creation of 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 Engineers are a specialized role responsible for designing, building, and deploying machine learning models. They often work in finance, tech, cybersecurity, healthcare, and logistics -- all of which are among the strongest industries in the Tampa region. Glassdoor shares that a Machine Learning Engineer in Tampa can earn an average of $142,000, but the range is realistically anywhere from $115,000 to $176,000, depending on expertise and the company.
Data Scientists are tasked with a variety of data-related tasks, including machine learning model development. They conduct research and work on large-scale datasets to uncover information that can lead to more improvement across the organization. Glassdoor suggests Tampa-based Data Scientists earn around $138,000 on average, but can expect a realistic range of $86,000 to $137,000, which is based on level of experience and the company or industry.
Some Data Engineers specialize in machine learning models. They build the infrastructure that’s used to create machine learning models, such as pipelines and databases. They often work with other machine learning and data science professionals and can be found across a variety of industries in Tampa. According to Glassdoor, Data Engineers earn an average of $122,000 and, depending on experience, speciality, and the hiring company, the range could be anywhere from $97,000 to $155,000.
Smart cities like Tampa are exactly where a machine learning pro can thrive. The definition of a “smart city” aims to reduce pollution, solve transportation issues, and provide a natural feeling to human-centered technology, such as automated vendors and services that can be run by machines. Tampa was named one of 21 Smart Cities to Watch after it demonstrated commitment to AI with the $3 billion Water Street Tampa development and a $21 million grant to study connected vehicle technology. Forward-thinking investments like these show relatively small, everyday benefits to residents like free high-speed wi-fi and smart parking. It’s no wonder this sunshine-filled city is a draw for anyone involved in machine learning.
Examples of just a few fields that rely on those who work with ML demonstrate that there is a vast expanse of job opportunities. Besides industry-specific knowledge or experience, traits that those in roles involving machine learning tend to share include expertise in applied mathematics, physics, data modeling and evaluation, natural language processes, and reinforcement learning. It is a field that can be difficult to understand as it evolves and grows as fast as any modern technology, so those in ML professions must be willing to keep up with advancements and change.
As a subset of artificial intelligence, the actions that machine learning performs are an area that directly impacts lives in tech-forward advancements. 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. Artificial intelligence is the technology that enables a machine to simulate human behavior, and the niche of machine learning within AI is what allows a machine to learn from past data without explicit programming automatically. The goal is to make a smart computer system that is human-relatable to solve complex problems.
Artificial intelligence is a technology that enables a machine to simulate human behavior. Typical career fields associated with machine learning (ML) include machine learning engineering, data science, human-centered machine learning design, computational linguistics, and software development.
Real-world examples of how enterprises use machine learning can be seen across vertical industries, providing organizations with tangible, actionable results. For instance, in financial services, banks use ML predictive models that look across a massive array of interrelated measures to better understand and meet customer needs and limit risk exposure to risk. Top use cases in banking include fraud detection and mitigation, personal financial adviser services, credit scoring, and loan analysis. In cybersecurity, ML can be applied to identify cyber threats, track and document fraudulent customer behavior, and better predict risk for new products.
Manufacturing is another key area that requires ML as companies have embraced automation and are now instrumenting both equipment and processes. Machine learning is used to reorganize and optimize production that is responsive to current demand and alert for future change. In the manufacturing sector, top uses identified include yield improvements, root cause analysis, and supply chain and inventory management.
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 of sharing their computer screen with the instructor for extra assistance.
An understanding of data science is necessary for a career in machine learning. Noble Desktop offers a Data Science Certificate that allows students an opportunity to gain all of 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.
The Python Developer Certificate teaches the essential programming skills to manipulate databases and perform various levels of analysis on the data to be able to enter the workforce upon completion. Students learn how to use NumPy, Pandas, and Matplotlib to analyze data and create predictive models from the data using machine learning packages such as scikit-learn. Additionally, students learn how to read and write complex queries in a database, which is a necessary skill since a significant amount of daily effort in the workplace includes spending time cleaning data so that it can be imported and analyzed in Python.
Additionally, the Python for Data Science & 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 and decision trees. 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.
Artificial intelligence is one of the fastest-developing areas in technology today. It makes sense to boost your team’s abilities in the field by providing a focused look at machine learning by investing in an onsite corporate machine learning training session. Noble Desktop, the creator of this tool, will send an expert instructor to your Tampa-based workplace to provide training or offer the training via live video conferencing. If it is more convenient for employees to attend sessions on their own time, you can purchase vouchers to register for a public open enrollment session. There are discounts on the purchase of multiple vouchers. Contact Noble Desktop for more information.
Tampa is one of the most diverse areas in Florida, making it an ideal place to develop skills in technology, business, design, or data through training courses. The city’s economy spans industries such as finance and cybersecurity, with prominent companies and startups throughout the Tampa Bay area. Tampa offers professionals the opportunity to apply what they learn in a real-world setting, from the executive-driven Water Street district to the Channelside areas. Noble Desktop’s instructors bring decades of experience to each class, meshing practical training with hands-on learning. The training courses in subjects ranging from coding to Excel, instructors help students gain the practical experience needed to succeed in Tampa’s competitive job market.
Machine learning helps Tampa organizations automate analysis, identify patterns, and improve decision-making. With Noble Desktop, students learn foundational modeling techniques from instructors who make advanced concepts accessible and practical.
Dr. Cheryl McCloud is a seasoned expert with over 35 years of experience in global supply chain management, spanning across industries like transportation, trade compliance, and inventory management. She earned her Bachelor’s in International Studies from Old Dominion University before pursuing an MBA in Project Management from Devry University and a DBA in Global Supply Chain Management from Walden University. Dr. McCloud currently teaches project management and marketing classes at Graduate School USA and has the background to help others reach the next step in their careers as well. She previously owned a global transportation business and served as a federal government contractor. Additionally, she provided global trade compliance oversight for major shippers across the world. She’s also a licensed U.S. Customs Broker with certification in project management and federal maritime law. Between her extensive career and numerous accolades, Dr. McCloud serves as a fantastic asset and resource for students.
Edward (Scott) Dillion is a retired Senior Financial Manager with over 30 years of experience in the Department of Defense, specializing in financial management, budgeting, auditing, and cost analysis, just to name a few subjects. He holds an MBA from Southern Illinois University and a B.A. in Business Administration from Grove City College. After retiring from civil service in 2014, he transitioned to a career as an instructor and consultant. He has worked as an adjunct instructor at Graduate School USA since 2015 and teaches a variety of courses, including project management and marketing. Dillon is also a Subject Matter Expert (SME) for Management Concepts Inc., where he contributes to financial management course material. In addition to his accomplishments in the professional world, he holds a lifetime membership of the American Society of Military Comptrollers and has a Top Secret security clearance. His career positions him as an excellent source of knowledge for all his students.